OA18985A - Calculating individual carbon footprints - Google Patents

Abstract

Behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least orîe predefmed carbon-saving quantity quantization algorithm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbon-saving quantity associated with the user.

Description

Alibaba Group Holding Limited

CALCULATINGINDIVIDUAL CARBON FOOTPRINTS

CLAIM OF PRIORITY

[0001] This application claims priority to Chinese Application No. 201610717756.7, filed on August 24, 2016, and U.S. Application No. 15/684,603, fïled on August 23, 2017, the entire contents of which are hereby incorporated by reference.

TECHNICAL FIELD

[0002] , The présent disclosure relates to computer-implemented methods, software, and

Systems for calculating individual carbon footprints.

BACKGROUND

[0003] Various human activities generate carbon émissions (such as, greenhouse gases) that can hâve négative effects on the Earth’s environment. For example, driving a gasolinepowered car or operating a thermal power station generates carbon émissions. To control carbon émissions, it is important for an individual to be aware of their measured carbon footprint based on daily behaviors.

SUMMARY

[0004] The présent disclosure describes methods and Systems, including computerimplemented methods, computer program products, and computer Systems for calculating individual carbon footprints, and particularly for calculating how many carbon footprints can be saved (that is, a carbon-saving quantity) from an individual engaging in environment-friendly behaviors.

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[0005] In an implémentation, behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least one predefined carbonsaving quantity quantization algorilhm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbonsaving quantity associated with the user.

[0006] The previously described implémentation is implementable using a computerimplemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perfonn the computer-implemented method; and a computer-implemented system comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method/instructions stored on the non-transitory, computerreadable medium.

[0007] The subject matter described in this spécification can be implemented in particular implémentations, so as to realize one or more of the following advantages. First, the described approach can be used to make individual people aware of their associated carbon footprints, carbon-saving quantities, or both from their daily behaviors. For example, fragmented behavior information associated with a person (a user) within a particular period of time (for example, a day, a month, or a year) can be aggregated. Based on the aggregated behavior data and in combination with a corresponding carbon-saving quantity quantization algorithm, a measurement of carbon footprints reduced by the user (that is, a carbon-saving quantity) can be calculated and provided to the user. Second, a service provider can provide a particular service, such as a point accumulation, an account upgrade, or other service, for the user based on the carbon-saving quantity associated with the user. The particular service can also provide incentives to the user to encourage réduction of carbon footprints by, for example, adopting more environmentally-friendly behaviors. Other advantages will be apparent to those of ordinary skill in the art.

[0008] The details of one or more implémentations of the subject matter of this spécification are set forth in the detailed description, the claims, and the accompanying drawings. Other features, aspects, and advantages of the subject matter will become apparent from the detailed description, the claims, and the accompanying drawings.

DESCRIPTION OF DRAWINGS

[0009] FIG. 1 is a flowchart illustrating an example method for calculating individual carbon footprints, according to an implémentation of the present disclosure.

[0010] FIGS. 2A-2E are schematic diagrams illustrating methods for génération of user behavior data in different scénarios, according to an implémentation of the present disclosure.

[0011] FIG. 3 is a block diagram illustrating a computing-based architecture for calculating individual carbon footprints, according to an implémentation of the present disclosure.

[0012] FIGS. 4A-4C are illustrative screenshots related to point accumulation, according to an implémentation of the present disclosure.

[0013] FIGS. 5A-5B are schematic diagrams of point acquisition between users, according to an implémentation of the present disclosure.

[0014] FIG. 6 is a block diagram illustrating an example data processing system for calculating individual carbon footprints, according to an implémentation of the present disclosure, [0015] FIG. 7 is a block diagram illustrating an example computer system used to provide computational functionalities associated with described algorithms, methods, functions, processes, flows, and procedures as described in the instant disclosure, according to an implémentation ofthe présent disclosure.

[0016] Like reference numbers and désignations in the various drawings indicate like éléments.

DETAILED DESCRIPTION

[0017] The following detailed description describes calculating individual carbon footprints, particularly calculating a carbon-saving quantity associated with a user based on collecting and aggregating fragmented behavior data associated with the user within a particuiar period of time, and is presented to enable any person skiiled in the art to make and use the I0 disclosed subject matter in the context of one or more particuiar implémentations. Various modifications, alterations, and permutations of the disclosed implémentations can be made and will be readily apparent to those of ordinary skill in the art, and the general principles defined may be applied to other implémentations and applications, without departing from the scope of the disclosure. In some instances, details unnecessary to obtain an understanding of the described 15 subject matter may be omitted so as to not obscure one or more described implémentations with unnecessary detail and as such details are within the skill of one of ordinary skill in the art. The présent disclosure is not intended to be limited to the described or illustrated implémentations, but to be accorded the widest scope consistent with the described principles and features.

[0018] Human activities can generate carbon émissions. To reduce carbon émissions, it is 20 important to make people aware of their carbon footprints from their daily behaviors. In addition, incentives can be provided to encourage enterprises or individuals to take initiative to control their carbon émissions by adopting environment-friendly behaviors. For enterprises, since enterprise behaviors, in general, are relatively closely related to the goals of the enterprise, each enterprise can calculate and control its carbon footprints and carbon-saving quantities. However, for 25 individuals, as individual behaviors are often unrelated to each other (that is, fragmented), carbon émissions can be generated from many different unrelated human activities. As a resuit, it is diffîcult for individual persons to calculate their associated carbon footprints.

[0019] At a high-level, the described approach provides a mechanism to automatically collect and aggregate behavior data associated with a user within a period of time. Based on ³⁰ aggregated behavior data and a particuiar carbon-saving quantity quantization algorithm, carbon footprints associated with the user, a carbon-saving quantity associated with the user, or a combination of carbon footprints and a carbon-saving quantity associated with the user can be calculated and provided to the user. The carbon-saving quantity associated with the user can be further processed by a service provider to provide a particuiar service, such as point accumulation 35 or account upgrade, for the user.

[0020] FIG. I is a flowchart illustrating an example method 100 for calculating individual carbon footprints, according to an implémentation of the present disclosure. For clarity of présentation, the description that follows generally describes method 100 in the context of the other figures in this description. However, it will be understood that method 100 may be performed, for example, by any suitable system, environment, software, and hardware, or a combination of Systems, environments, software, and hardware, as appropriate. In some implémentations, various steps of method 100 can be run in parallel, in combination, in loops, or in any order.

[0021] At 105, behavior data associated with a user is acquired. For example, the acquired behavior data can be generated when the user uses an Internet service. In some implémentations, the behavior data can include a user identification (such as a user ID or a user account) and identification information that indicates the Internet service used when the behavior data is generated. The Internet service can include, for example, at least one of an Intemet-based (or “online”) electronic payment service, a réservation service, a ticketing service, a payment service, a health service, or other Internet service consistent with this disclosure. In some implémentations, the health service can be a service associated with a mobile phone system or an application for monitoring user movement behavior. In some implémentations, the health service can include, for example, at least one of a step-counting service and a distance calculation service. In some implémentations, different Internet services can hâve different identification information, which can include, for example, at least one of a service type identification and a type identification bit in an order number. As a resuit, a type of an Internet service corresponding to the behavior data can be determined based on the identification information in the behavior data. In some implémentations, behavior data from different Internet services can be differentiated based on the identification information included in the behavior data from the different Internet services. [0022] In some implémentations, the acquired behavior data can include fragmented behavior data. Each fragment of the behavior data can include a user identification (such as a user ID or a user account) and identification information indicating the Internet service corresponding to the particular fragment of the behavior data. To aggregate the fragmented behavior data, ail the fragments of the behavior data are toned to include identification related to the same user in order to correlate the fragments of the behavior data. In some implémentations, a user can use different Internet services through different applications or servers when generating behavior data. For example, the user can use an online payment service through a payment application on a mobile computing device and use an online meal-ordering service through a meal-ordering application. In some implémentations, a user can use different accounts when using the Internet services. To ensure that the acquired behavior data is associated with the same user, the different accounts (that is, user identifications) related to the same user may be acquired. For example, the user can first input information related to their different accounts to be stored. Then, behavior data associated with an account can be acquired from a corresponding application or server through, for example, an account name of the user. In some implémentations, data or combinations of data identifying the user can be used to acquire the behavior data. Note that the previously described method is not limited to acquisition of different accounts related to a same user, but also applicable to acquisition of different accounts related to different users.

[0023] In some implémentations, after the behavior data is acquired, a field, representing a type of an Internet service, in the behavior data can be determined based on a predefined rule. Based on content in the field, the type of Internet service corresponding to the behavior data can be determined. In some implémentations, types of Internet services provided by some applications or servers are relatively fixed. For example, a ticketing website server only provides a ticketing service. If behavior data is acquired from such applications or servers, types of Internet services corresponding to the behavior data can be identified directly based on, for example, at least one of names, domain names, Universal Resource Locators (URLs), and other information associated with the applications or servers.

[0024] In some implémentations, method 100 can be performed by an application. In some implémentations, method 100 can be performed by a server. When performed by an application, the application may be capable of providing various Internet services to the user. In that case and in some implémentations, the application can be configured to generate behavior data for the user and to also calculate carbon footprints for the user directly based on the generated behavior data. In other words, by registering an account in the application, behavior data generated by the user through use of various Internet services in the application can be associated with the user s registered account. As a resuit, the application only needs to acquire behavior data related to the account to calculate, for example, carbon footprints for the user.

[0025] However, if the application cannot itself provide an Internet service to the user, the application can initiale a request for acquiring behavior data from a third-party application or a third-party server capable of providing an Internet service. Then, the application may receive the behavior data from the third-party application, or synchronize data with the third-party application to receive the behavior data generated by the third-party application. In that case, the user may input, in the application, different third-party accounts associated with the user, as well as thirdparty applications or third-party servers corresponding to the different third-party accounts. The application can then associate the third-party accounts with an account registered by the user in the application. For example, to acquire behavior data from a third-party application, the application can détermine, based on a third-party account, a third-party application corresponding to the thirdparty account, and send an acquisition request that carries the third-party account to the third-party application. In response, the third-party application can find behavior data related to the third5 party account and retum the behavior data to the requesting application. As a resuit, the application can acquire the user behavior data.

[0026] In some implémentations, when a third-party application is involved in calculating individual carbon footprints, the application that performs method 100 can register, in advance, with the third-party application. By registering with the third-party application, the application can receive behavior data from the third-party application. In some implémentations, when a thirdparty server is involved in calculating individual carbon footprints, the application that performs method 100 can acquire behavior data from the third-party server through a data transfer protocol that both the application and the third-party server agréé upon.

[0027] In some implémentations, behavior data is generated, by a third-party application or a third-party server, in a common data format. For example, the behavior data can be generated in a two-dimensional table format, a HyperText Markup Language (HTML) format, or an Extensible Markup Language (XML) format. After acquiring the behavior data, the application or server that performs method 100 can read, analyze, or read and analyze the behavior data based on the corresponding data format. In some implémentations, for a particular data format, the application that performs method 100 and a third-party application can agréé upon a data transmission format (for example, a JavaScript Object Notation (JSON) format). In addition, different methods for analyzing different data formats can be added, in advance, to an Application Programming Interface (API) of the application. In some implémentations, the acquired behavior data can be stored locally or remotely. From 105, method 100 proceeds to 110.

[0028] At 110, at least one preset carbon-saving quantity quantization algorithm is determined according to the identification information of the Internet service in the acquired behavior data. In some implémentations, relationships between Internet services and carbonsaving quantity quantization algorithms are pre-established. Based on a particular Internet service and the pre-established relationships, at least one carbon-saving quantity quantization algorithm can be determined. The at least one carbon-saving quantity quantization algorithm includes, for example, a quantization formula, a quantization model, or a combination of a quantization formula and a quantization model.

[0029] In some implémentations, behavior data including different identification information from different Internet services can be associated with different carbon-saving quantity quantization algorithms. For example, an electronic payment service can save paper products, and a walking trip can save carbon émissions because a vehicle was not driven (such as a gasoline-powered car). In some implémentations, an Internet service can be associated with multiple carbon-saving quantity quantization algorithms (that is, multiple carbon-saving quantity quantization algorithms can be used with one Internet service). For example, when a user uses an online ticketing service, the user can buy a ticket without leaving, for example, the user’s home.

As a resuit, carbon émissions caused by a trip to a ticketing site by driving a vehicle can be saved. In addition, buying tickets online can avoid printing paper products, such as tickets, receipts, and réservation lists, during online payment. As a resuit, carbon émissions caused by the used paper products can be saved. To calculate a carbon-saving quantity associated with the user by using the 5 online ticketing service, both a carbon-saving quantity quantization algorithm associated with trips using a vehicle and a carbon-saving quantity quantization algorithm associated with the use of paper products are used.

[0030] In some implémentations, the carbon-saving quantity quantization algorithms can include a first preset algorithm and a second preset algorithm. For example, the first preset (0 algorithm can be a carbon-saving quantity quantization algorithm associated with the use of paper products (such as, a carbon-saving quantity quantization algorithm for savings related to avoidance of printing paper bills). The second preset algorithm can be a carbon-saving quantity algorithm associated with use of a vehicle (such as, a carbon-saving quantity quantization algorithm for savings related to walking as opposed to driving).

I5 [0031] For the first preset algorithm, a carbon-saving quantity can be calculated based on a carbon émission corresponding to a paper product. For example, the following formula can be used:

ERy = Σί(Λ ^x X EF_y X 10’⁶(l) (I), where ER_y is a carbon-saving quantity (unit: tons of CO2) of a paper bill saved by each online 20 payment in the y¹¹¹ year. In other words, ERy represents, in essence, a carbon footprint corresponding to a paper bill printed for each ofïline payment. Since printing of a paper bill can be avoided if the user uses online payment, the value of ER can be used as a carbon-saving quantity of a paper bill saved by each online payment. i is a merchant type of offline payment. F] is a proportion (that is, percentage) of /-type merchants using a point of service (POS) machine for 25 payment. A£)t. y is the number of times (unit: times) that the user makes payment ofïline at the itype merchants in the y¹¹¹ year. EFy is a baseline émission factor (unit: g CO2/time) of ofïline payment in the y”¹ year. In some implémentations, EF_y can be determined based on émission intensities of bill paper manufacturera in different régions. For example, Table 1 shows émission intensities of bill paper manufacturera in several provinces in China.

	Yunnan	Zhejiang	Shanxi	Other provinces
Emission intensities (tons of CO2/ton of paper)	1.9296	2.0072	1.8834	1.4622

Table l

[0032] In some implémentations, since the value of a carbon-saving quantity corresponding to saving of a paper bill in each online payment service (that is, ER) is too small, the carbon-saving quantity is calculated on an annual basis (that is, ER_V as in Equation ( l )). In some implémentations, a threshold number can be predefined to avoid calculating a carbon-saving quantity each time the online payment service is being used. For example, after using the online payment service by more than the threshold number, a total carbon-saving quantity for using the online payment service the threshold number of times can be calculated.

[0033] For the second preset algorithm, a carbon-saving quantity can be calculated based on a carbon émission corresponding to a trip by driving a vehicle to a service location (for example, a bank, a shop, a restaurant). For example, the following formula can be used:

P = L X IV; (2), where Z. is a geographical distance (unit: miles) between a user location when using an online service and a nearest service location, W is a mean value of carbon footprints generated by driving a vehicle for a mile, and P is the carbon footprints generated by driving the vehicle for the distance L. From 110, method 100 proceeds to 115.

[0034] At 115, a carbon-saving quantity associated with the user is calculated according to the behavior data and the determined at least one preset carbon-saving quantity quantization algorithm. For the first preset algorithm, production of paper products can be reduced each time the user uses an online Internet service. As a resuit, the carbon-saving quantity is related to the number of times that the user uses the online Internet service. In addition, since carbon émission standards are different in different régions, the carbon-saving quantity is also related to the user’s geographical location. In some implémentations, when the first predefined algorithm is used to calculate a user carbon-saving quantity, at least a number of times that the user uses an Internet service and a user’s geographical location when the user uses the Internet service are first determined. Then, the carbon-saving quantity is calculated based on the determined number of times that the user uses the Internet service, the determined geographical position of the user when the user uses the Internet service, and the first predefïned algorithm.

[0035] For the second preset algorithm, the carbon-saving quantity associated with the user is related to, for example, a number of walking steps or a walking distance associated with the user. In some implémentations, when the second predefïned algorithm is used to calculate a user carbon-saving quantity, at least a number of walking steps or a walking distance associated with the user is determined. Then, the carbon-saving quantity is calculated based on the determined number of walking steps or walking distance, and the second predefïned algorithm.

[0036] In some implémentations, when the Internet services and the carbon-saving quantity quantization algorithms are in a one-to-one relationship, a single carbon-saving quantity quantization algorithm can be used to calculate a user carbon-saving quantity by using a corresponding Internet service.

[0037] In some implémentations, when the Internet services and the carbon-saving quantity quantization algorithms are in a one-to-many relationship, multiple carbon-saving quantity quantization algorithms, corresponding to a particular Internet service, can be used to calculate a user carbon-saving quantity by using the particular Internet service.

[0038] In some implémentations, the acquired behavior data may include redundant or irrelevant data, such as data not required to calculate individual carbon footprints. For example, acquired behavior data for a user using an online ticketing service can include data related to the amount of money the user paid. In some implémentations, the acquired behavior data may not be used directly. For example, when a carbon-saving quantity is calculated according to behavior data associated with a user using an online ticketing service, the calculation may require a number of times the user uses the online ticketing service. In some implémentations, the behavior data is processed to determine an exact number of times the user uses the online ticketing service. In other implémentations, an approximate number of times the user uses the online ticketing service can be used. As a resuit, before calculating a carbon-saving quantity, data collating operations, such as statistical collection, screening, and removal, can be performed on the acquired behavior data. In some implémentations, an application or server that performs method 100 may perform the data collating operations on the behavior data. In some implémentations, an application or server that performs method I00 and a behavior data provider can agréé upon behavior data required for calculation. As a resuit, the behavior data provider can perform the data collating operations on behavior data associated with a user before providing the processed behavior data to the application or server.

[0039] In some implémentations, a quantized value, calculated based on the behavior data and the carbon-saving quantity quantization algorithm, can represent a carbon footprint reduced by a user (that is, a carbon-saving quantity associated with the user). In some implémentations, a carbon-saving quantity can be calculated on a predefined cycle perîod. In some implémentations, a carbon-saving quantity can be calculated based on the number of times that the user uses an Internet service. From 115, method 100 proceeds to 120.

[0040] At 120, spécifie user data is processed according to the calculated carbon-saving quantity and the user identification. The spécifie user data is related to a carbon-saving quantity.

In some implémentations, after the carbon-saving quantity associated with the user is calculated, data processing operations, such as statistical collection and analysis, can be performed on the carbon-saving quantity within a period of time (for example, a day, a month, or a year). In some implémentations, the calculated carbon-saving quantity can be converted into points based on, for example, a predefined conversion rule. The newly converted points can be added to total points associated with the user to obtain an updated total points value. As the value of the total points increase, the carbon-saving quantity associated with the user increases. Accordingly, a service provider can provide different services to the user based on the value of the total points. For example, virtual goods corresponding to the total points can be assigned to the user. In some implémentations, the virtual goods hâve different display States corresponding to differing total point values.

[0041] In some implémentations, user identification can include a user account. The spécifie user data can include data, such as carbon-saving points, a carbon-saving level, a carbonsaving badge, and carbon-saving related virtual goods, in the user account. After 120, method 100 stops.

[0042] FIGS. 2A-2E are schematic diagrams of methods 200, 210, 220, 230, and 240 for génération of user behavior data in different scénarios, according to an implémentation of the present disclosure. Methods 200, 210, 220, 230, and 240 are presented as detailed views ofthe operations of method 100 described in FIG. 1 in different scénarios. For clarity of présentation, the description that follows generally describes methods 200, 210, 220, 230, and 240 in the context of the other figures in this description. However, it will be understood that methods 200, 210, 220, 230, and 240 may be performed, for example, by any suitable system, environment, software, and hardware, or a combination of Systems, environments, software, and hardware, as appropriate. In some implémentations, varions steps of methods 200, 210, 220, 230, and 240 can be run in parallel, in combination, in loops, or in any order.

[0043] Scénario 1 : a user uses an online ticketing service.

[0044] In some implémentations, the online ticketing service can include at least one of online booking, purchasing, and refunding services for train tickets, plane tickets, ship tickets, movie tickets, admission tickets, and other tickets consistent with this disclosure. Compared to the traditional ticketing service (that is, a user goes to a physical ticketing site to obtain a ticket), the online ticketing service can save the user a trip to the physical ticketing site. If the trip is taken to the physical ticketing site, for example, by driving a vehicle, data related to carbon émissions generated by the trip can be saved. In addition, by using the online ticketing service, paper products (for example, printed paper statements or receipts) used during ticket purchase or refund can be reduced or eliminated.

[0045] After the user uses the online ticketing service, a service provider that provides the online ticketing service (for example, a ticketing website) can generate online ticketing data based on the user’s online ticketing behavior. The online ticketing data can be used as behavior data for the user in using the online ticketing service. A carbon-saving quantity associated with using the online ticketing service can be calculated based on the behavior data.

[0046] The calculation of a carbon-saving quantity can be performed by an application client having a carbon-saving quantity computing fiinction (hereinafter referred to as a computing 5 application), or a server having a carbon-saving quantity computing function. As an example, FIGS. 2A-2E are described with the computing application performing the carbon-saving quantity calculation. In general, the online ticketing service is provided by a ticketing website. The user can use the online ticketing service through an application corresponding to the ticketing website (hereinafter referred to as a ticketing application). Behavior data generated while the user is using 10 the online ticketing service can be generated by a server of the ticketing website (hereinafter referred to as a ticketing server).

[0047] FIG. 2A shows an example method 200 of acquiring and calculating a user carbon-saving quantity purchasing a ticket online. In general, when a user purchases a ticket online, the user sends a ticket purchase request to a ticketing server through a corresponding 15 ticketing application. The ticket purchase request can include user information (for example, user’s ID card number, naine, a ticketing account registered in the ticketing application) and ticket purchase information (for example, type, time, place of a ticket to be purchased). After receiving the ticket purchase request, the ticketing server can issue a ticket according to the online ticket purchase request, generate ticketing data associated with the user, and record the ticketing data as 20 behavior data.

[0048] At 201, the computing application sends an acquisition request, including user information to the ticketing server, to acquire ticketing data associated with the user. In some implémentations, the acquisition request can include time information indicating ticketing data associated with the user within a predefined cycle period (for example, a day). In some 25 implémentations, the acquisition request can include an account registered by the user in the computing application (hereinafter referred to as a computing account) and a ticketing account associated with the user to the ticketing server. The ticketing server, then, can dynamically acquire, according to the ticketing account, ticketing data related to the ticketing account, and actively push, according to the computing account, the ticketing data related to the ticketing 30 account to the computing application. In some implémentations, if the computing application itself has an online ticketing service, and the user uses the online ticketing service provided by the computing application, the computing application can acquire ticketing data generated by the computing application. From 201, method 200 proceeds to 202.

[0049] At 202, the ticketing server receives the acquisition request, déterminés ticketing 35 data corresponding to the user information included in the acquisition request, and sends back the determined ticketing data to the computing application. The ticketing data includes at least a user H

ID, and identification information that reflects a type of the ticketing service. In some implémentations, if the acquisition request includes time information, the ticketing server can acquire, according to the time information, ticketing data associated with the user matching the time information. In some implémentations, the ticketing server can perform data collating operations on the ticketing data before sending the collated ticketing data to the computing application. For example, the ticketing data stored by the ticketing server may include the amount of money for a purchased ticket, an origin of the purchased ticket, and a destination of the purchased ticket. The ticketing server can remove the amount of money for the purchased ticket, the origin of the purchased ticket, and the destination of the purchased ticket, from the ticketing data and send the processed ticketing data to the computing application. From 202, method 200 proceeds to 203.

[0050] At 203, after acquiring the ticketing data from the ticketing server, the computing application déterminés, according to the user ID included in the ticketing data, that the ticketing data is associated with a user account. In addition, the computing application détermines, according to the identification information included in the ticketing data, at least one carbonsaving quantity quantization algorithm for calculating a carbon-saving quantity of the ticketing data. The at least one carbon-saving quantity quantization algorithm can be a carbon-saving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle, a carbon-saving quantity quantization algorithm spécifie to savings related to the use of paper products, or a combination of a carbon-saving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle and a carbon-saving quantity quantization algorithm spécifie to savings related to the use of paper products. From 203, method 200 proceeds to 204.

[0051] At 204, a carbon-saving quantity associated with the user using the online ticketing service is calculated according to the determined carbon-saving quantity quantization algorithm and the acquired ticketing data. In addition, spécifie user data can be processed according to the calculated carbon-saving quantity associated with the user. In some implémentations, the ticketing application includes a locating function capable of determining the user’s location information (for example, by using global positioning system (GPS) or WIFI/cellular-triangulation information) when the user sends an online ticketing instruction. The computing application can determine, according to a ticketing order number in the acquired ticketing data, the number of times that the user uses the online ticketing service. The ticketing order number uniquely identifies, for example, one online ticketing service. In addition, the computing application can acquire, through the ticketing application, user location information when the user uses the online ticketing service, and determine EF_y in Equation (!) according to a géographie région corresponding to the user location information. Accordingly, a carbon-saving quantity spécifie to savings with respect to use of a printed paper bill each time the user uses the online ticketing service can be calculated. If the user uses the online ticketing service n times in a same géographie région, corresponding to the same EF_yi a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills can be calculated as η X ER . If the user uses the online ticketing service multiple times in different géographie régions, corresponding to different EF_y, a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills is an accumulation of carbon-saving quantîties associated with the user in the different géographie régions.

[0052] In some implémentations, the computing application can détermine, according to the user location information when the user uses the online ticketing service, a ticketing site location (for example, a railway station) closest to the user location. The computing application, then, calculâtes a distance L between the user location and the ticketing site location, and uses Equation (2) to calculate a carbon-saving quantity spécifie to avoidance of a trip by driving a vehicle for the distance L. In some implémentations, the calculated carbon-saving quantity associated with the user can include both a carbon-saving quantity spécifie to avoidance of a trip by driving a vehicle, and a carbon-saving quantity spécifie to savings related to using printed paper bills.

[0053] In some implémentations, the calculated carbon-saving quantity associated with the user using the online ticketing service can be converted into points. After the user logs into the computing application, the points, indicating reduced carbon footprints by using an online ticketing service, can be presented to the user. After 204, method 200 stops.

[0054] Scénario 2: a user uses an online payment service.

[0055] In some implémentations, the online payment service can include at least one of a face-to-face online payment service and an online transfer service. Compared to the traditional payment service, the online payment service can reduce consumption of paper products (for example, printed paper bills), and thus can reduce carbon footprints.

[0056] After the user uses the online payment service, a service provider that provides the online payment service can generate online payment data based on the user’s online payment behavior. The online payment data ca be used as behavior data for the user in using the online payment service. A carbon-saving quantity associated with using the online payment service can be calculated based on the behavior data.

[0057] Similar to scénario 1, the calculation of a carbon-saving quantity can be performed by a computing application or a server having a carbon-saving quantity computing fonction. In some implémentations, a service provider capable of providing the online payment service includes a commodity website, a payment platform, and a bank. By taking the payment platform as an example, the user can use the online payment service through an application corresponding to the payment platform (hereinafter referred to as a payaient application). Behavior data generated while the user is using the online payment service can be generated by a server of the payment platform (hereinafter referred to as a payment server).

[0058] FIG. 2B shows an example method 210 of acquiring and calculating a user carbon-saving quantity making a payment online. In general, when a user makes an online payment, the user sends a payment request to a payment server through a corresponding payment application. The payment request can include user information (for example, a payment account registered by the user on the payment platform), target user information (for example, a target account registered by the target user on the payment platform), and payment information (for example, the amount of payment). After receiving the payment request, the payment server can acquire, according to the receîved payment request, a fond matching the amount of payment from the payment account associated with the user, assign the fond to the target account of the target user, generate payment data associated with the user, and record the payment data as behavior data.

[0059] At 211, the computing application sends an acquisition request, including user information to the payment server, to acquire payment data associated with the user. In some implémentations, when a user pays a target user online through the payment platform, the user and the target user each has a corresponding account registered on the payment platform. In some implémentations, the acquisition request can include a payment account registered by the user on the payment platform to acquire payment data related to the payment account. In some implémentations, the acquisition request can include time information indicating payment data associated with the user within a predefmed cycle period (for example, a day). In some implémentations, the computing application can send, in advance, both a computing account registered by the user in the computing application and the payment account associated with the user to the payment server. The payment server, then, can dynamically acquire, according to the payment account, payment data related to the payment account, and actively push, according to the computing account, the payment data related to the payment account to the computing application. In some implémentations, if the computing application itself has an online payment service and the user uses the online payment service provided by the computing application, the computing application can acquire payment data generated by the computing application. From 211, method 210 proceeds to 212.

[0060] At 212, the payment server receives the acquisition request, détermines payment data corresponding to the user information included in the acquisition request, and sends back the determined payment data to the computing application. The payment data includes at least a user

ID, and identification information that reflects a type of the payment service. In some implémentations, if the acquisition request includes time information, the payment server can acquire, according to the time information, payment data associated with the user matching the time information. In some implémentations, the payment server can perform data collating operations on the payment data before sending the collated payment data to the computing application. For example, the payment data stored by the payment server may include the amount of payment, and the payment time. The payment server can remove the amount of payment and the payment time from the payment data and send the processed payment data to the computing application. From 212, method 210 proceeds to 213.

[0061] At 213, after acquiring the payment data from the payment server, the computing application détermines, according to the user ID included in the payment data, that the payment data is associated with a user account. In addition, the computing application déterminés, according to the identification information included in the payment data, a carbon-saving quantity quantization algorithm for calculating a carbon-saving quantity of the payment data. The carbonsaving quantity quantization algorithm can be a carbon-saving quantity quantization algorithm spécifie to savings related to the use of paper products. From 213, method 210 proceeds to 214.

[0062] At 214, a carbon-saving quantity associated with the user using the online payment service is calculated according to the determined carbon-saving quantity quantization algorithm and the acquired payment data. In addition, spécifie user data can be processed according to the calculated carbon-saving quantity associated with the user. In some implémentations, the payment application includes a locating function capable of determining the user’s location information (for example, by using GPS or WIFI/cellular-triangulation information) when the user sends an online payment instruction. The computing application can détermine, according to a payment order number in the acquired payment data, the number of times that the user uses the online payment service. The payment order number uniquely identifies one online payment service. In addition, the computing application can acquire, through the payment application, user location information when the user uses the online payment service, and détermine EF_y in Equation (1 ) according to a géographie région corresponding to the user location information. Accordingly, a carbon-saving quantity spécifie to savings with respect to use of a printed paper bill each time the user uses the online payment service can be calculated. If the user uses the online payment service n times in a same géographie région, corresponding to the same EF_y, a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills can be calculated as η X ER_y. If the user uses the online payment service multiple times in different géographie régions, corresponding to different EF_V, a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills is an accumulation of carbon-saving quantities associated with the user in the different géographie régions.

[0063] In some implémentations, the calculated carbon-saving quantity associated with the user using the online payment service can be converted into points. After the user logs into the computing application, the points, indicating reduced carbon footprints by using an online payment service, can be presented to the user. After 214, method 211 stops.

[0064] Scénario 3 : a user uses an online réservation service.

[0065] In some implémentations, the online réservation service can include at least one of online restaurant réservation, hôtel réservation, venue booking, and hospital registration services. Compared to the traditional réservation service (that is, a user goes to a physical service site to make a réservation), the online réservation service can save the user a trip to the physical service site. If the trip is taken to the physical service site, for example, by driving a vehicle, data related to carbon émissions generated by the trip can be saved.

[0066] After the user uses the online réservation service, a service provider that provides the online réservation service (for example, a hospital website) can generate online réservation data based on the user’s online réservation behavior. The online réservation data can be used as behavior data for the user in using the online réservation service. A carbon-saving quantity associated with using the online réservation service can be calculated based on the behavior data.

[0067] Similar to scénario l, the calculation of a carbon-saving quantity can be performed by a computing application or a server having a carbon-saving quantity computing function. In some implémentations, a service provider capable of providing the online réservation service includes a réservation platform, a hospital, a hôtel, and a restaurant. By taking the réservation platform as an example, the user can use the online réservation service through an application of the réservation platform (hereinafter referred to as a réservation application). Behavior data generated while the user is using the online réservation service can be generated by a server of the réservation platform (hereinafter referred to as a réservation server).

[0068] FIG. 2C shows an example method 220 of acquiring and calculating a user carbon-saving quantity making a réservation online. In general, when a user makes an online réservation, the user sends a réservation request to a réservation server through a corresponding réservation application. The réservation request can include user information (for example, medical Insurance information of the user, user name, ID card number, a réservation account registered by the user in the réservation application), registration type information (for example, a specialist number, an ordinaiy doctor number), and hospital information selected by the user (for example, hospital level, hospital name). After receiving the réservation request, the réservation server can register, according to the received réservation request, a corresponding hospital. After the registration succeeds, the réservation server sends back an electronic registration form to the réservation application, generates réservation data associated with the user, and records the réservation data as behavior data.

[0069] At 221, the computing application sends an acquisition request, including user information to the réservation server, to acquire réservation data associated with the user. In some implémentations, the acquisition request can include a réservation account registered by the user on the réservation platform to acquire réservation data related to the réservation account. In some 5 implémentations, the acquisition request can include medical Insurance information of the user, user name, ID card number, and a réservation account registered by the user in the réservation application. In some implémentations, the acquisition request can include time information indicating réservation data associated with the user within a predefmed cycle period (for example, a day). In some implémentations, the computing application can send both a computing account 10 registered by the user in the computing application and the réservation account of the user to the réservation server. The réservation server, then, can dynamically acquire, according to the réservation account, réservation data related to the réservation account, and actively push, according to the computing account, the réservation data related to the réservation account to the computing application. In some implémentations, if the computing application itself has an online 15 réservation service and the user uses the online réservation service provided by the computine application, the computing application can acquire réservation data generated by the computing application. From 221, method 220 proceeds to 222.

[0070] At 222, the réservation server receives the acquisition request, détermines réservation data corresponding to the user information included in the acquisition request, and 20 sends back the determined réservation data to the computing application. The réservation data includes at least a user ID, and identification information that reflects a type of the réservation service. In some implémentations, the réservation server can perform data collating operations on the réservation data before sending the collated réservation data to the computing application. For example, the réservation data stored by the réservation server may include a réservation type, and a 25 date of hospital visit. The réservation server can remove the réservation type and the date of hospital visit from the réservation data, and send the processed réservation data to the computing application. From 222, method 220 proceeds to 223.

[0071] At 223, after acquiring the réservation data from the réservation server, the computing application déterminés, according to the user ID included in the réservation data, that 30 the réservation data is associated with a user account. In addition, the computing application détermines, according to the identification information included in the réservation data, a carbonsaving quantity quantization algorithm for calculating a carbon-saving quantity of the réservation data. The carbon-saving quantity quantization algorithm can be a carbon-saving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle. From 223, method 220 35 proceeds to 224.

[0072] At 224, a carbon-saving quantity associated with the user using the online réservation service is calculated according to the determined carbon-saving quantity quantization algorithm and the acquired réservation data. In addition, spécifie user data can be processed according to the calculated carbon-saving quantity associated with the user. In some implémentations, the réservation application includes a locating function capable of determining the user’s location information (for example, by using GPS or WIFI/celluIar-triangulation information) when the user sends an online réservation instruction. The réservation data acquired by the computing application can include the location of the user when the user uses the online réservation service. Based on a hospital address included in the réservation data, the computing application can détermine the location of the hospital, calculate a distance L between the user location and the hospital location, and uses Equation (2) to calculate a carbon-saving quantity spécifie to avoidance of a trip by driving a vehicle for the distance L.

[0073] In some implémentations, the calculated carbon-saving quantity associated with the user using the online réservation service can be converted into points. After the user logs into the computing application, the points, indicating reduced carbon footprints by using an online réservation service, can be presented to the user. After 224, method 220 stops.

[0074] Scénario 4: a user uses an online bill payment service.

[0075] In some implémentations, the online bill payment service can include at least one of paying water fees, electricity fees, natural gas fees, and trafïïc fines online. Compared to the traditional bill payment service, the online bill payment service can save the user a trip to the physical bill payment site. If the trip is taken to the physical bill payment site, for example, by driving a vehicle, data related to carbon émissions generated by the trip can be saved.

[0076] After the user uses the online bill payment service, a service provider that provides the online bill payment service can generate online bill payment data based on the user’s online bill payment behavior. The online bill payment data can be used as behavior data for the use in using the online bill payment service. A carbon-saving quantity associated with the user using the online bill payment service can be calculated based on the behavior data,

[0077] Similar to scénario l, the calculation of a carbon-saving quantity can be performed by a computing application or a server having a carbon-saving quantity computing function. In some implémentations, a service provider capable of providing the online bill payment service includes an online bill payment platform, a bill payment website, and a bank. By taking the bill payment platform as an example, the user can use the online bill payment service through an application corresponding to the bill payment platform (hereinafter referred to as a bill payment application). Behavior data generated while the user is using the online bill payment service can be generated by a server of the bill payment platform (hereinafter referred to as a bill payment server).

[0078] FIG. 2D shows an example method 230 of acquiring and calculating a user carbon-saving quantity making a bill payment online. In general, when a user makes an online bill payment, the user sends a bill payment request to a bill payment server through a corresponding bill payment application. The bill payment request can include user information (for example, driver’s license number, ID card number, a penalty ticket number of the user, a bill payment account registered by the user on the bill payment platform). After receiving the bill payment request, the bill payment server can deduct, according to the received bill payment request, a corresponding amount of ftind from the account of the user, and pay the bill to the corresponding bill payment website. After the bill payment succeeds, the bill payment server sends back an electronic payment voucher to the bill payment application, generates bill payment data associated with the user, and records the bill payment data as behavior data.

[0079] At 231, the computing application sends an acquisition request, including user information to the bill payment server, to acquire bill payment data associated with the user. In some implémentations, when a user makes an online bill payment, the user first registers a corresponding account on the bill payment platform. The account needs to hâve sufficient amount of money to make the online bill payment successful. In some implémentations, the acquisition request can include at least one of a driver’s license number, ID card number, a penalty ticket number of the user, and a bill payment account registered by the user on the bill payment platform. In some implémentations, the acquisition request can include time information indicating bill payment data associated with the user within a predefined cycle period (for example, a day). In some implémentations, the computing application can send both a computing account registered by the user in the computing application and the bill payment account associated with the user to the bill payment server. The bill payment server, then, can dynamically acquire, according to the bill payment account, bill payment data related to the bill payment account, and actively push, according to the computing account, the bill payment data related to the bill payment account to the computing application. In some implémentations, if the computing application itself has an online bill payment service and the user uses the online bill payment service provided by the computing application, the computing application can acquire bill payment data generated by the computing application. From 231, method 230 proceeds to 232,

[0080] At 232, the bill payment server receives the acquisition request, détermines bill payment data corresponding to the user information included in the acquisition request, and sends back the determined bill payment data to the computing application. The bill payment data includes at least a user DD, and identification information that reflects a type of the bill payment service. In some implémentations, the bill payment server can perform data collating operations on the bill payment data before sending the collated bill payment data to the computing application. From 232, method 230 proceeds to 233.

[0081] At 233, after acquiring the bill payment data from the bill payment server, the computing application détermines, according to the user ID included in the bill payment data, that the bill payment data is associated with a user account. In addition, the computing application détermines, according to the identification information included in the bill payment data, at least one carbon-saving quantity quantization algorithm for calculating a carbon-saving quantity of the bill payment data. The at least one carbon-saving quantity quantization algorithm can be a carbonsaving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle, a carbonsaving quantity quantization algorithm spécifie to savings related to the use of paper products, or a combination of a carbon-saving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle and a carbon-saving quantity quantization algorithm spécifie to savings related to the use of paper products. From 233, method 230 proceeds to 234.

[0082] At 234, a carbon-saving quantity associated with the user using the online bill payment service is calculated according to the determined carbon-saving quantity quantization algorithm and the acquired bill payment data. In addition, spécifie user data can be processed according to the calculated carbon-saving quantity associated with the user. In some implémentations, the bill payment application includes a locating function capable of determining the user’s location information (for example, by using GPS or WIFI/cellular-triangulation information) when the user sends an online bill payment instruction. The computing application can détermine, according to a bill payment order number in the acquired bill payment data, the number of times that the user uses the online bill payment service. The bill payment order number uniquely identifies one online bill payment service. In addition, the computing application can acquire, through the bill payment application, user location information when the user uses the online bill payment service, and détermine EF_y in Equation (l) according to a géographie région corresponding to the user location information. Accordingly, a carbon-saving quantity spécifie to savings with respect to use of a printed paper bill each time the user uses the online bill payment service can be calculated. If the user uses the online bill payment service n times in a same géographie région, corresponding to the same EF_y, a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills can be calculated as η X ER_y. If the user uses the online bill payment service multiple times in different géographie régions, corresponding to different EF_y, a carbon-saving quantity associated with the user spécifie to savings related to using printed paper bills is an accumulation of carbon-saving quantities associated with the user in the different géographie régions.

[0083] In some implémentations, the computing application can détermine, according to the user location information when the user uses the online bill payment service, a bill payment site location (for example, a bank) closest to the user location. The computing application, then, calculâtes a distance L between the user location and the bill payment site location, and uses Equation (2) to calculate a carbon-saving quantity spécifie to avoidance of a trip by driving a vehicle for the distance L. In some implémentations, the calculated carbon-saving quantity associated with the user can include both a carbon-saving quantity spécifie to avoidance of a trip 5 by driving a vehicle, and a carbon-saving quantity spécifie to savings related to using printed paper bills.

[0084] In some implémentations, the calculated carbon-saving quantity associated with the user using the online bill payment service can be converted into points. After the user logs into the computing application, the points, indicating reduced carbon footprints by using an online bill 10 payment service, can be presented to the user. After 234, method 230 stops.

[0085] Scénario 5: a user goes out on foot, and walking data is monitored by a health service.

[0086] In some implémentations, walking can reduce carbon footprints of a user. The user can walk to a physical service site. For example, the user can walk to a hospital to register, 15 walk to a ticketing site to purchase a ticket, and walk to a bill payment site to pay related fees.

[0087] Walking data can be produced by a health service application (for example, a walking application) having a walking data collection function. The walking data can be used as behavior data for walking. A carbon-saving quantity associated with the user can be calculated based on the behavior data. In some implémentations, the walking data can include at least one of 20 the number of steps, location information during walking, and a walking distance. In some implémentations, the walking data can include user information (for example, an account registered by the user in the walking application).

[0088] Similar to scénario l, the calculation of a carbon-saving quantity can be performed by a computing application or a server having a carbon-saving quantity computing function. In 25 some implémentations, the walking data can be obtained by a walking application through a corresponding collection algorithm, a model, or a sensing device (for example, a smart bracelet, a smart watch).

[0089] FIG. 2E shows an example method 240 of acquiring and calculating a user carbonsaving quantity by walking. At 241, the computing application sends an acquisition request, 30 including user information to the walking application, to acquire walking data associated with the user. In some implémentations, the acquisition request can include an account registered by the user on the walking application. In some implémentations, the walking application can actively push, according to the registered account, walking data related to the user information to the computing application. In some implémentations, if the computing application itself has a walking 35 data collection function, the computing application can acquire walking data generated by the computing application. From 241, method 240 proceeds to 242.

[0090] At 242, the walking application receives the acquisition request, détermines walking data corresponding to the user information included in the acquisition request, and sends back the determined walking data to the computing application. The walking data includes at least a user ID, and identification information that reflects a type of a walking behavior. From 242, method 240 proceeds to 243.

[0091] At 243, after acquiring the walking data from the walking application, the computing application détermines, according to the user ID included in the walking data, that the walking data is associated with a user account. In addition, the computing application détermines, according to the identification information included in the walking data, a carbon-saving quantity quantization algorithm for calculating a carbon-saving quantity of the walking data. The carbonsaving quantity quantization algorithm can be a carbon-saving quantity quantization algorithm spécifie to réduction of trips by driving a vehicle. From 243, method 240 proceeds to 244.

[0092] At 244, a carbon-saving quantity associated with the user by walking is calculated according to the determined carbon-saving quantity quantization algorithm and the acquired walking data. In addition, spécifie user data can be processed according to the calculated carbonsaving quantity associated with the user. In some implémentations, if the walking data includes location information of the user during walking, the computing application can determine, based on the location information in the walking data, a walking distance ofthe user. The carbon-saving quantity associated with the user by walking, then, can be determined based on the walking distance and the determined carbon-saving quantity quantization algorithm. After 244, method 240 stops.

[0093] FIG. 3 is a block diagram illustrating a computing-based architecture 300 for calculating individual carbon footprints, according to an implémentation of the present disclosure. As illustrated in FIG. 3, an application client 301 acquires fragmented user behavior data associated with a user 302, a third-party application 303, a third-party server 304, or a combination of a third-party application 303 and a third-party server 304. The behavior data includes behavior data generated when the user 302 uses different Internet services. After acquiring the behavior data, the application client 301 sends the acquired behavior data to an application server 305. The application server 305 calculâtes a carbon-saving quantity associated with the user 302, and retums the carbon-saving quantity to the application client 301 for présentation to the user 302.

[0094] FIGS. 4A-4C are illustrative screenshots 400, 410, and 420 related to point accumulation, according to an implémentation of the present disclosure. For clarity of présentation, the description that follows generally describes screenshots 400, 410, and 420 in the context of the other figures in this description. In some implémentations, point accumulation can be made in response to a confîrmîng instruction sent by a user. For example, a control component configured to accumulate points can be provided to the user. The control component can be a 22 suspension control component, an embedded control component, or a popup window control component, which can be implemented in hardware, software, or both.

[0095] In FIG 4A, a control component is embedded in an application interface 401. The user can request point accumulation by clicking an “Accumulate button 402. Based on this, 5 accumulating the converted points and total points of the user may include: after receiving a confirming instruction (that is, clicking the “Accumulate” button 402) sent by the user, points that can be accumulated 403 are added to the total points 404 associated with the user.

[0096] Total points 404 can be calculated and displayed respectively according to different types of human behavior. As shown in FIG. 4B, the application interface includes I0 different types of behavior items (for example, payment 4ll, ticketing 412, walking 413, bill payment 414, réservation 415), and total points for each type of behavior item is displayed in each type of behavior item. In addition, total points for ail types of behavior items can be displayed, for example, by clicking “Click to view total points” 416.

[0097] After clicking “Click to view total points” 416 in FIG. 4B, the total points 421 for 15 ail types of behavior items is displayed as shown in FIG. 4C.

[0098] In some implémentations, different users can acquire non-accumulated points from each other. For example, a user can send an acquisition instruction to acquire at least part of non-accumulated points of other users. As a resuit, the at least part of non-accumulated points of other users are deducted from accounts associated with the other users, and added to the total 20 points of the user. In some implémentations, the other users are related to the user. For example, the other users are listed in a user’s contact list.

[0099] FIGS. 5A-5B are schematic diagrams 500 and 510 of point acquisition between users, according to an implémentation of the present disclosure. For clarity of présentation, the description that follows generally describes diagrams 500 and 510 in the context of the other 25 figures in this description. As shown in FIG. 5A, non-accumulated points are displayed for each contact in a user’s contact list (Address list) 501. For example, contact Xiaoming 502 has 50 nonaccumulated points, contact Xiaohong 503 has 150 non-accumulated points 503, contact Xiaogang 504 has 360 non-accumulated points, and contact Er’ya 505 has 0 non-accumulated points. The user can click on any contact in the contact list to acquire non-accumulated points of the clicked 30 contact. As shown in FIG. 5B, after the user clicks on contact Xiaogang 504 in the contact list 501, the user may be presented with a detailed view 511 of contact Xiaogang 504. The detailed view 511 shows non-accumulated points corresponding to different types of behaviors of contact Xiaogang 504. For example, Xiaogang 504 has 100 non-accumulated points in Payment 512, 50 non-accumulated points in Ticking 513, 100 non-accumulated points in Walking 514, 50 non35 accumulated points in Bill payment 515, and 60 non-accumulated points in Réservation 516. The user can click on a particular behavior item (for example, Réservation) to acquire non-accumulated 23 points corresponding to the particular behavior item (for example, 60 non-accumulated points in

Réservation).

[00100] In some implémentations, virtual goods matching total points associated with a user can be assigned to the user. The Virtual goods can include a virtual tree, a virtual badge, and a virtual medal. The virtual goods hâve different display States according to differing total points. For example, according to pre-divided point intervals, a point interval within which the total points fall can be determined, and a display State of the virtual goods associated with the user can be determined based on a predefined relationship between the point intervals and display States ofthe virtual goods. The display States of the virtual goods include, for example, a size, a shape, and a color of the virtual goods. For example, a virtual medal can be a bronze medal, a silver medal, or a gold medal.

[OOlOl] FIG. 6 is a block diagram illustrating an example data processing System 600 for calculating individual carbon footprints, according to an implémentation. For clarity of présentation, the description that follows generally describes System 600 in the context of the other figures in this description. The System 600 can include an acquisition unit 601, a détermination unit 602, a calculation unit 603, a processing unit 604, a point acquisition unit 605, and an assignment unit 606, which can be implemented in hardware, software, or both.

[00102] The acquisition unit 601 can acquire behavior data associated with a user, as discussed in step 105 of FIG. 1. The détermination unit 602 can détermine at least one preset carbon-saving quantity quantization algorithm based on identification information of an Internet service, as discussed in step 110 of FIG. 1 and steps 203, 213, 223, 233, and 243 of FIGS. 2A-2E. The calculation unit 603 can calculate a carbon-saving quantity based on the acquired behavior data and the determined preset carbon-saving quantity quantization algorithm, as discussed in step 115 of FIG. 1 and steps 204, 214, 224, 234, and 244 of FIGS. 2A-2E. The processing unit 604 can process spécifie user data based on the calculated carbon-saving quantity and user identification, as discussed in step 120 of FIG. 1. In addition, the processing unit 604 can convert the calculated carbon-saving quantity associated with the user into points based on a preset conversion rule, and accumulate the converted points and total points of the user to obtain updated total points of the user. The point acquisition unit 605 can receive an acquisition instruction sent by a user for nonaccumulated points of other users, acquire ali or some points in the non-accumulated points of other users, and accumulate the acquired ail or some points and total points of the user to obtain updated total points of the user. The assignment unit 606 can détermine updated total points ofthe user, and assign virtual goods matching the updated total points to the user.

[00103] FIG. 7 is a block diagram of an example computer system 700 used to provide computational functionalities associated with described algorithms, methods, fonctions, processes, flows, and procedures, as described in the instant disclosure, according to an implémentation. The illustrated computer 702 is intended to encompass any computing device such as a server, desktop computer, laptop/notebook computer, wireless data port, smart phone, personal data assistant (PDA), tablet computing device, one or more processors within these devices, or any other suitable

Processing device, including physical or virtual instances (or both) of the computing device.

Additionally, the computer 702 may comprise a computer that includes an input device, such as a keypad, keyboard, touch screen, or other device that can accept user information, and an output device that conveys information associated with the operation of the computer 702, including digital data, visual, or audio information (or a combination of information), or a graphical user interface (GUI).

[00104] The computer 702 can serve in a rôle as a client, network component, a server, a database or other persistency, or any other component (or a combination of rôles) of a computer system for performing the subject matter described in the instant disclosure. The illustrated computer 702 is communicably coupled with a network 730. In some implémentations, one or more components of the computer 702 may be configured to operate within environments, 15 including cloud-computing-based, local, global, or other environment (or a combination of environments).

[00105] At a high level, the computer 702 is an electronic computing device opérable to receive, transmit, process, store, or manage data and information associated with the described subject matter. According to some implémentations, the computer 702 may also include or be 20 communicably coupled with an application server, e-mail server, web server, caching server, streaming data server, or other server (or a combination of servers).

[00106] The computer 702 can receive requests over network 730 from a client application (for example, executing on another computer 702) and respond to the received requests by Processing the received requests using an appropriate software application(s). In addition, requests 25 may also be sent to the computer 702 from internai users (for example, from a command console or by other appropriate access method), extemal or third-parties, other automated applications, as well as any other appropriate entities, individuals, Systems, or computers.

[00107] Each ofthe components of the computer 702 can communicate using a System bus

703. In some implémentations, any or ail of the components of the computer 702, hardware or 30 software (or a combination of both hardware and software), may interface with each other or the interface 704 (or a combination of both), over the system bus 703 using an application programming interface (API) 712 or a service layer 713 (or a combination of the API 712 and service layer 713). The API 712 may include spécifications for routines, data structures, and object classes. The API 712 may be either computer-language independent or dépendent and refer 35 to a complété interface, a single function, or even a set of APIs. The service layer 713 provides software services to the computer 702 or other components (whether or not illustrated) that are 25 communicably coupled to the computer 702. The fùnctionality of the computer 702 may be accessible for ail service consumers using this service layer. Software services, such as those provided by the service layer 713, provide reusable, defined functionalities through a defined interface. For example, the interface may be software written in JAVA, C++, or other suitable language providing data in extensible markup language (XML) format or other suitable format.

While illustrated as an integrated component of the computer 702, alternative implémentations may illustrate the API 712 or the service layer 713 as stand-alone components in relation to other components of the computer 702 or other components (whether or not illustrated) that are communicably coupled to the computer 702. Moreover, any or ail parts of the API 712 or the 10 service layer 713 may be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of this disclosure.

[00108] The computer 702 includes an interface 704. Although illustrated as a single interface 704 in FIG. 7, two or more interfaces 704 may be used according to particular needs, desires, or particular implémentations of the computer 702. The interface 704 is used by the 15 computer 702 for communicating with other Systems that are connected to the network 730 (whether illustrated or not) in a distributed environment. Generally, the interface 704 comprises logic encoded in software or hardware (or a combination of software and hardware) and is opérable to communicate with the network 730. More specifically, the interface 704 may comprise software supporting one or more communication protocols associated with communications such 20 that the network 730 or interface’s hardware is opérable to communicate physical signais within and outside of the illustrated computer 702.

[00109] The computer 702 includes a processor 705. Although illustrated as a single processor 705 in FIG. 7, two or more processors may be used according to particular needs, desires, or particular implémentations of the computer 702. Generally, the processor 705 executes 25 instructions and manipulâtes data to perform the operations of the computer 702 and any algorithms, methods, functions, processes, flows, and procedures as described in the instant disclosure.

[00110] The computer 702 also includes a database 706 that can hold data for the computer 702 or other components (or a combination of both) that can be connected to the network 730 30 (whether illustrated or not). For example, database 706 can be an in-memory, conventional, or other type of database storing data consistent with this disclosure. In some implémentations, database 706 can be a combination of two or more different database types (for example, a hybrid in-memory and conventional database) according to particular needs, desires, or particular implémentations of the computer 702 and the described functionality. Although illustrated as a 35 single database 706 in FIG. 7, two or more databases (of the same or combination of types) can be used according to particular needs, desires, or particular implémentations of the computer 702 and the described functionality. While database 706 is illustrated as an intégral component of the computer 702, in alternative implémentations, database 706 can be external to the computer 702.

[00111 ] The computer 702 also includes a memory 707 that can hold data for the computer 702 or other components (or a combination of both) that can be connected to the network 730 (whether illustrated or not). Memory 707 can store any data consistent with this disclosure. In some implémentations, memory 707 can be a combination of two or more different types of memory (for example, a combination of semiconductor and magnetic storage) according to particular needs, desires, or particular implémentations of the computer 702 and the described functionality. Although illustrated as a single memory 707 in FIG. 7, two or more memories 707 (of the same or combination of types) can be used according to particular needs, desires, or particular implémentations of the computer 702 and the described functionality. While memory 707 is illustrated as an intégral component of the computer 702, in alternative implémentations, memory 707 can be external to the computer 702.

[00112] The application 708 is an algorithmic software engine providing functionality according to particular needs, desires, or particular implémentations of the computer 702, particularly with respect to functionality described in this disclosure. For example, application 708 can serve as one or more components, modules, or applications. Further, although illustrated as a single application 708, the application 708 may be implemented as multiple applications 708 on the computer 702. In addition, although illustrated as intégral to the computer 702, in alternative implémentations, the application 708 can be external to the computer 702.

[00113] The computer 702 can also include a power supply 714. The power supply 714 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or nonuser-replaceable. In some implémentations, the power supply 714 can include power-conversion or management circuits (including recharging, standby, or other power management functionality). In some implémentations, the power-supply 714 can include a power plug to allow the computer 702 to be plugged into a wall socket or other power source to, for example, power the computer 702 or recharge a rechargeable battery.

[00114] There may be any number of computers 702 associated with, or external to, a computer system containing computer 702, each computer 702 communicating over network 730. Further, the terrn “client, “user, and other appropriate terminology may be used interchangeably, as appropriate, without departing from the scope of this disclosure. Moreover, this disclosure contemplâtes that many users may use one computer 702, or that one user may use multiple computers 702.

[00115] Described implémentations of the subject matter can include one or more features, alone or in combination.

[00116] For example, in a first implémentation, a computer-implemented method, comprising: obtaining behavior data associated with a user, wherein the behavior data is generated when the user uses an Internet service, and the behavior data comprises a user identification and identification information indicating the Internet service; determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service; calculating a carbon-saving quantity associated with the user based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm; and based on the calculated carbon-saving quantity associated with the user and the user identification, processing user data, wherein the user data is related to the carbonsaving quantity associated with the user.

[00117] The foregoing and other described implémentations can each, optionally, include one or more of the following features:

[00118] A first feature, combinable with any of the following features, wherein the at least one predefined carbon-saving quantity quantization algorithm comprises: a first predefined algorithm, wherein the first predefined algorithm is a carbon-saving quantity quantization algorithm for targeting savings of paper products; and a second predefined algorithm, wherein the second predefined algorithm quantizes a carbon-saving quantity of réduction of trips by taking vehicles.

[00 H 9] A second feature, combinable with any of the previous or following features, wherein, when the first predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of times that the user uses the Internet service and a geographical location of the user when the user uses the Internet service; and calculating the carbon-saving quantity associated with the user based on the determined number of times that the user uses the Internet service, the determined geographical position of the user when the user uses the Internet service, and the first predefined algorithm.

[00120] A third feature, combinable with any of the previous or following features, wherein, when the second predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of walking steps or a walking distance of the user; and calculating the carbon-saving quantity associated with the user based on the determined number of walking steps or walking distance of the user and the second predefined algorithm.

[00121] A fourth feature, combinable with any of the previous or following features, wherein determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service comprises determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information ofthe Internet service and a plurality of pre-stored corresponding relationships between a plurality of Internet services and a plurality of carbon-saving quantity quantization algorithms.

[00122] A fifth feature, combinable with any of the previous or following features, wherein the Internet service comprises at least one of an electronic payment service, an online réservation service, an online ticketing service, an online bill payment service, and a health service.

[00123] A sixth feature, combinable with any of the previous or following features, wherein processing user data comprises: obtaining a plurality of carbon-saving quantities associated with the user corresponding to a plurality of Internet services within a predefined period; accumulating the obtained plurality of carbon-saving quantities; and processing the user data based on the accumulaied carbon-saving quantity associated with the user.

[00124] A seventh feature, combinable with any of the previous or following features, wherein processing the user data based on the accumulated carbon-saving quantity associated with the user comprises: adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbonsaving quantity associated with the user; and processing the user data based on the updated total carbon-saving quantity associated with the user.

[00125] An eighth feature, combinable with any of the previous or following features, wherein adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbon-saving quantity associated with the user comprises: converting the accumulated carbon-saving quantity associated with the user into points based on a predefined conversion rule; and adding the converted points and total points of the user together to obtain updated total points of the user.

[00126] A ninth feature, combinable with any of the previous or following features, wherein a control component configured to accumulate points is provided to the user, and adding the converted points and total points of the user together to obtain updated total points of the user comprises: receiving an instruction sent by the user through the control component confirming points accumulation; and adding the converted points and the total points ofthe user together.

[00127] A tenth feature, combinable with any of the previous or following features, further comprising: receiving an instruction sent by the user to obtain non-accumulated points of other users; obtaining at least part of the non-accumulated points of other users in response to receiving the instruction sent by the user to obtain non-accumulated points of other users; and adding the obtained at least part of the non-accumulated points of other users and the updated total points of the user together to obtain second updated total points of the user.

[00128] An eleventh feature, combinable with any of the préviens or following features, further comprising determining the updated total points of the user; and based on the updated total points of the user, assigning, to the user, a Virtual goods corresponding to the updated total points of the user.

[00129] A twelfth feature, combinable with any of the previous or following features, wherein the virtual goods has different display States corresponding to different total points.

[00130] In a second implémentation, a non-transitory, computer-readable medium storing one or more instructions exécutable by a computer system to perform operations comprising: obtaining behavior data associated with a user, wherein the behavior data is generated when the user uses an Internet service, and the behavior data comprises a user identification and identification information indicating the Internet service; determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service; calculating a carbon-saving quantity associated with the user based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm; and based on the calculated carbon-saving quantity associated with the user and the user identification, processing user data, wherein the user data is related to the carbonsaving quantity associated with the user.

[00131] The foregoing and other described implémentations can each, optionally, include one or more of the following features:

[00132] A first feature, combinable with any of the following features, wherein the at least one predefined carbon-saving quantity quantization algorithm comprises: a first predefined algorithm, wherein the first predefined algorithm is a carbon-saving quantity quantization algorithm for targeting savings of paper products; and a second predefined algorithm, wherein the second predefined algorithm quantizes a carbon-saving quantity of réduction of trips by taking vehicles.

[00133] A second feature, combinable with any of the previous or following features, wherein, when the first predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of times that the user uses the Internet service and a geographical location of the user when the user uses the Internet service; and calculating the carbon-saving quantity associated with the user based on the determined number of times that the user uses the Internet service, the determined geographical position ofthe user when the user uses the Internet service, and the first predefined algorithm.

[00134] A third feature, combinable with any of the previous or following features, wherein, when the second predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of walking steps or a walking distance of the user; and calculating the carbon-saving quantity associated with the user based on the determined number of walking steps or walking distance of the user and the second predefined algorithm.

£00135] A fourth feature, combinable with any of the previous or following features, wherein determining at least one predefmed carbon-saving quantity quantization algorithm based on the identification information of the Internet service comprises determining at least one predefmed carbon-saving quantity quantization algorithm based on the identification information of the Internet service and a plurality of pre-stored corresponding relationships between a plurality of Internet services and a plurality of carbon-saving quantity quantization algorithms.

[00136] A fifth feature, combinable with any of the previous or following features, wherein the Internet service comprises at least one of an electronic payment service, an online réservation service, an online ticketing service, an online bill payment service, and a health service.

[00137] A sixth feature, combinable with any of the previous or following features, wherein processing user data comprises: obtaining a plurality of carbon-saving quantities associated with the user corresponding to a plurality of Internet services within a predefmed period; accumulating the obtained plurality of carbon-saving quantities; and processing the user data based on the accumulated carbon-saving quantity associated with the user.

[00138] A seventh feature, combinable with any of the previous or following features, wherein processing the user data based on the accumulated carbon-saving quantity associated with the user comprises: adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbonsaving quantity associated with the user; and processing the user data based on the updated total carbon-saving quantity associated with the user.

[00139] An eighth feature, combinable with any of the previous or following features, wherein adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbon-saving quantity associated with the user comprises: converting the accumulated carbon-saving quantity associated with the user into points based on a predefined conversion rule; and adding the converted points and total points of the user together to obtain updated total points of the user. [00140] A ninth feature, combinable with any of the previous or following features, wherein a control component configured to accumulate points is provided to the user, and adding the converted points and total points of the user together to obtain updated total points of the user comprises, receiving an instruction sent by the user through the control component confïrming points accumulation; and adding the converted points and the total points ofthe user together.

[00141 ] A tenth feature, combinable with any of the previous or following features, further comprising: receiving an instruction sent by the user to obtain non-accumulated points of other users; obtaining at least part of the non-accumulated points of other users in response to receiving the instruction sent by the user to obtain non-accumulated points of other users; and adding the obtained at least part of the non-accumulated points of other users and the updated total points of the user together to obtain second updated total points ofthe user.

[00142] An eleventh feature, combinable with any of the previous or following features, further comprising: determining the updated total points of the user; and based on the updated total points of the user, assigning, to the user, a Virtual goods corresponding to the updated total points of the user.

[00143] A twelfth feature, combinable with any of the previous or following features, wherein the virtual goods has different display States corresponding to different total points.

[00144] In a third implémentation, a computer-implemented system, comprising: one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing instructions, that when executed by the one or more computers, perform operations comprising: obtaining behavior data associated with a user, wherein the behavior data is generated when the user uses an Internet service, and the behavior data comprises a user identification and identification information indicating the Internet service; determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service; calculating a carbon-saving quantity associated with the user based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm; and based on the calculated carbon-saving quantity associated with the user and the user identification, processing user data, wherein the user data is related to the carbon-saving quantity associated with the user.

[00145] The foregoing and other described implémentations can each, optionally, include one or more of the following features:

[00146] A first feature, combinable with any of the following features, wherein the at least one predefined carbon-saving quantity quantization algorithm comprises: a first predefined algorithm, wherein the first predefined algorithm is a carbon-saving quantity quantization algorithm for targeting savings of paper products; and a second predefined algorithm, wherein the second predefmed algorithm quantizes a carbon-saving quantity of réduction of trips by taking vehicles.

[00147] A second feature, combinable with any of the previous or following features, wherein, when the first predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of times that the user uses the Internet service and a geographical location of the user when the user uses the Internet service; and calculating the carbon-saving quantity associated with the user based on the determined number of times that the user uses the Internet service, the determined geographical position ofthe user when the user uses the Internet service, and the first predefined algorithm.

[00148] A third feature, combinable with any of the previous or following features, wherein, when the second predefined algorithm is used to calculate the carbon-saving quantity, calculating a carbon-saving quantity associated with the user comprises: based on the behavior data, determining at least a number of walking steps or a walking distance of the user; and calculating the carbon-saving quantity associated with the user based on the determined number of walking steps or walking distance of the user and the second predefined algorithm.

[00149] A fourth feature, combinable with any of the previous or following features, wherein determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service comprises determining at least one predefined carbon-saving quantity quantization algorithm based on the identification information of the Internet service and a plurality of pre-stored corresponding relationships between a plurality of Internet services and a plurality of carbon-saving quantity quantization algorithms.

[00150] A fifth feature, combinable with any of the previous or following features, wherein the Internet service comprises at least one of an electronic payment service, an online réservation service, an online ticketing service, an online bill payment service, and a health service.

[00151] A sixth feature, combinable with any of the previous or following features, wherein processing user data comprises: obtaining a plurality of carbon-saving quantifies associated with the user corresponding to a plurality of Internet services within a predefined period; accumulating the obtained plurality of carbon-saving quantities; and processing the user data based on the accumulated carbon-saving quantity associated with the user.

[00152] A seventh feature, combinable with any of the previous or following features, wherein processing the user data based on the accumulated carbon-saving quantity associated with the user comprises: adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbonsaving quantity associated with the user; and processing the user data based on the updated total carbon-saving quantity associated with the user.

[00153] An eighth feature, combinable with any of the previous or following features, wherein adding the accumulated carbon-saving quantity associated with the user and a total carbon-saving quantity associated with the user together to obtain an updated total carbon-saving quantity associated with the user comprises: converting the accumulated carbon-saving quantity associated with the user into points based on a predefined conversion ruie; and adding the converted points and total points of the user together to obtain updated total points of the user.

[00154] A ninth feature, combinable with any of the previous or following features, 5 wherein a control component configured to accumulate points is provided to the user, and adding the converted points and total points of the user together to obtain updated total points of the user comprises: receiving an instruction sent by the user through the control component confirming points accumulation; and adding the converted points and the total points of the user together.

[00155] A tenth feature, combinable with any of the previous or following features, further 10 comprising: receiving an instruction sent by the user to obtain non-accumulated points of other users; obtaining at least part of the non-accumulated points of other users in response to receiving the instruction sent by the user to obtain non-accumulated points of other users; and adding the obtained at least part of the non-accumulated points of other users and the updated total points of the user together to obtain second updated total points of the user.

I5 [00156] An eleventh feature, combinable with any of the previous or following features, further comprising: determining the updated total points of the user; and based on the updated total points of the user, assigning, to the user, a virtual goods corresponding to the updated total points of the user.

[00157] A twelfth feature, combinable with any of the previous or following features, 20 wherein the virtual goods has different display States corresponding to different total points.

[00158] Implémentations of the subject matter and the functional operations described in this spécification can be implemented in digital electronic circuitry, in tangibly embodied computer software or firmware, in computer hardware, including the structures disclosed in this spécification and their structural équivalents, or in combinations of one or more of them. Software 25 implémentations of the described subject matter can be implemented as one or more computer programs, that is, one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable computer-storage medium for execution by, or to control the operation of, data processing apparatus. Altematively, or additionally, the program instructions can be encoded in/on an artificially generated propagated signal, for example, a machine-generated 30 electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus. The computer-storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage médiums. Configuring one or more computers means that the one or more computers hâve 35 installed hardware, firmware, or software (or combinations of hardware, firmware, and software) so that when the software ts executed by the one or more computers, particular computing operations are performed.

[00159] The terrn “real-time,” “real time,” “realtime,” “real (fast) time (RFT),” “near(ly) real-time (NRT),” “quasi real-time,” or similar terms (as understood by one of ordinary skill in the art), means that an action and a response are temporally proximate such that an individual perceives the action and the response occurring substantially simultaneously. For example, the time différence for a response to display (or for an initiation of a display) of data following the individual’s action to access the data may be less than l ms, less than l sec., or less than 5 secs. While the requested data need not be displayed (or initiated for display) instantaneously, it is displayed (or initiated for display) without any intentional delay, taking into account processing limitations of a described computing system and time required to, for example, gather, accurately measure, analyze, process, store, or transmit the data.

[00160] The terms “data processing apparatus,” “computer,” or “electronic computer device” (or équivalent as understood by one of ordinary skill in the art) refer to data processing hardware and encompass ail kinds of apparatus, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The apparatus can also be, or further include spécial purpose logic circuitry, for example, a central processing unit (CPU), an FPGA (field programmable gâte array), or an ASIC (application-specific integrated circuit). In some implémentations, the data processing apparatus or spécial purpose logic circuitry (or a combination of the data processing apparatus or spécial purpose logic circuitry) may be hardware- or software-based (or a combination of both hardwareand software-based). The apparatus can optionally include code that créâtes an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplâtes the use of data processing apparatuses with or without conventional operating Systems, for example LINUX, UNIX, WINDOWS, MAC OS, ANDROID, IOS, or any other suitable conventional operating system.

[00161] A computer program, which may also be referred to or described as a program, software, a software application, a module, a software module, a script, or code can be written in any form of programming language, including compiled or interpreted languages, or déclarative or procédural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files, for example, files that store one or more modules, sub-programs, or portions of code. A computer program can be deployed to be executed on one computer or on 35 multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[00162] While portions of the programs illustrated in the various figures are shown as individual modules that implement the various features and functionality through various objects, 5 methods, or other processes, the programs may instead include a number of sub-modules, thirdparty services, components, libraries, and such, as appropriate. Conversely, the features and functionality of various components can be combined into single components, as appropriate. Thresholds used to make computational déterminations can be statically, dynamically, or both statically and dynamically determined.

I0 [00163] The methods, processes, or logic flows described in this spécification can be performed by one or more programmable computers executing one or more computer programs to perform fonctions by operating on input data and generating output. The methods, processes, or logic flows can also be performed by, and apparatus can also be implemented as, spécial purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.

I5 [00164] Computers suitable for the execution of a computer program can be based on general or spécial purpose microprocessors, both, or any other kind of CPU. Generally, a CPU will receive instructions and data from and Write to a memory. The essential éléments of a computer are a CPU, for performing or executing instructions, and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively 20 coupled to, receive data from or transfer data to, or both, one or more mass storage devices for storing data, for example, magnetic, magneto-optical disks, or optical disks. However, a computer need not hâve such devices. Moreover, a computer can be embedded in another device, for example, a mobile téléphoné, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device, for 25 example, a universal serial bus (USB) flash drive, to name just a few.

[00165] Computer-readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data includes ail forms of permanent/non-permanent or volatile/non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, for example, random access memory (RAM), read-only memory 30 (ROM), phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPR.OM), and flash memory devices; magnetic devices, for example, tape, cartridges, cassettes, intemal/removable disks; magneto-optical disks; and optical memory devices, for example, digital video dise (DVD), CD-ROM, DVD+/-R, DVD35 RAM, DVD-ROM, HD-DVD, and BLURAY, and other optical memory technologies. The memory may store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories storing dynamic information, and any other appropriate information including any parameters, variables, algorithms, instructions, rules, constraints, or référencés thereto. Additionally, the memory may include any other appropriate data, such as logs, policies, security or access data, reporting files, as well as others. The processor and the memory can be supplemented by, or incorporated in, spécial purpose logic circuitry.

[00166] To provide for interaction with a user, implémentations of the subject matter described in this spécification can be implemented on a computer having a display device, for exampie, a CRT (cathode ray tube), LCD (liquid crystal display), LED (Light Emitting Diode), or plasma monitor, for displaying information to the user and a keyboard and a pointing device, for example, a mouse, trackball, or trackpad by which the user can provide input to the computer. Input may also be provided to the computer using a touchscreen, such as a tablet computer surface with pressure sensitivity, a multi-touch screen using capacitive or electric sensing, or other type of touchscreen. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, for example, visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can internet with a user by sending documents to and receiving documents from a device that is used by the user; for example, by sending web pages to a web browser on a user’s client device in response to requests received from the web browser.

[00167] The term graphical user interface,” or “GUI,” may be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particuiar graphical user interface. Therefore, a GUI may represent any graphical user interface, including but not limited to, a web browser, a touch screen, or a command line interface (CLI) that processes information and efficiently présents the information results to the user. In general, a GUI may include a plurality of user interface (UI) éléments, some or ail associated with a web browser, such as interactive fields, pull-down lists, and buttons. These and other UI éléments may be related to or represent the functions of the web browser.

£00168] Implémentations of the subject matter described in this spécification can be implemented in a computing system that includes a back-end component, for example, as a data server, or that includes a middleware component, for example, an application server, or that includes a front-end component, for example, a client computer having a graphical user interface or a Web browser through which a user can interact with an implémentation of the subject matter described in this spécification, or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data 37 communication), for example, a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) using, for example, 802.H a/b/g/n or 802.20 (or a combination of 802.1 Ix and 802.20 or other protocols consistent with this disclosure), ail or a portion ofthe Internet, or any other communication system or Systems at one or more locations (or a combination of communication networks). The network may communicate with, for example, Internet Protocol (IP) packets, Frame Relay frames, Asynchronous Transfer Mode (ATM) cells, voice, video, data, or other suitable information (or a combination of communication types) between network addresses.

[00169] The computing system can include clients and servers. A client and server are generally remote from each other and typically internet through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[00170] While this spécification contains many spécifie implémentation details, these should not be construed as limitations on the scope of any invention or on the scope of what may be claimed, but rather as descriptions of features that may be spécifie to particular implémentations of particular inventions. Certain features that are described in this spécification in the context of separate implémentations can also be implemented, in combination, in a single implémentation. Conversely, various features that are described in the context of a single implémentation can also be implemented in multiple implémentations, separately, or in any suitable sub-combination. Moreover, although previously described features may be described as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

[00171] Particular implémentations of the subject matter hâve been described. Other implémentations, alterations, and permutations of the described implémentations are within the scope of the following claims as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that ail illustrated operations be performed (some operations may be considered optional), to achieve désirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and performed as deemed appropriate.

[00172] Moreover, the séparation or intégration of various system modules and components in the previously described implémentations should not be understood as requiring 38 such séparation or intégration în ail implémentations, and it should be understood that the described program components and Systems can generally be integrated together in a single software product or packaged into multiple software products.

[00173] Accordingly, the previously described example implémentations do not define or 5 constrain this disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of this disclosure.

[00174] Furthermore, any claimed implémentation is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computerreadable instructions to perform the computer-implemented method; and a computer system 10 comprising a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium.

Claims (14)

1. Amended Claims (EPO)

   l. A method for processing data, the method comprising:

   receiving a request for an Internet service, the request comprising a user identification that indicates a user identity and identification information that indicates the Internet service (S20l,

   S202, S2ll, S212);

   acquiring behavior data of a user, the behavior data being generated based on the request, when the user uses the Internet service (S 101 );

   determining at least one preset carbon-saving quantity quantization algorithm according to the identification information of the Internet service (SI02);

   calculating, using the determined preset carbon-saving quantity quantization algorithm, a carbon-saving quantity of the user according to the behavior data (S 103);

   aggregating the carbon-saving quantity with a stored carbon-saving quantity of the user according to fragmented behavior data corresponding to different types of behavior data;

   processing user data corresponding to the user according to the aggregated carbon-saving quantity of the user and the user identification, wherein the user data is related to the aggregated carbon-saving quantity (S 104); and providing instructions to display the user data on a user device.
2. 2. The method according to claim 1, wherein the at least one preset carbon-saving quantity quantization algorithm comprises:

   a first preset algorithm, the first preset algorithm corresponding to saving of paper products; and a second preset algorithm, the second preset algorithm corresponding to réduction of trips by vehicle.
3. 3. The method according to claim 2, wherein, when the first preset algorithm is used to calculate the carbon-saving quantity and calculating the carbon-saving quantity of the user according to the behavior data and the determined preset carbon-saving quantity quantization algorithm comprises:

   at least determining, according to the behavior data, the number of times that the user perforais the Internet service, and a geographical position of the user when the user perforais the Internet service; and calculating the carbon-saving quantity of the user is based on the determined number of times that the user perforais the Internet service, the determined geographical position, and the first preset algorithm.
4. 4. The method according to claim 2, wherein, when the second preset algorithm is used to calculate a carbon-saving quantity, calculating the carbon-saving quantity of the user according to the behavior data and the determined preset carbon-saving quantity quantization algorithm comprises:

   at least determining, according to the behavior data, the number of walking steps or a walking distance of the user; and calculating the carbon-saving quantity of the user according to the determined number of walking steps or walking distance of the user and the second preset algorithm.
5. 5. The method according to claim l or 2, wherein determining the at least one preset carbon-saving quantity quantization algorithm according to the identification information of the Internet service comprises:

   determining at least one preset carbon-saving quantity quantization algorithm according to the identification information of the Internet service and a pre-stored corresponding relationship between Internet services and carbon-saving quantity quantization algorithms.
6. 6. The method according to any one of claims l to 5, wherein the Internet service comprises:

   at least one of an electronic payment service, an online réservation service, an online ticketing service, an online bill payment service, and a health service.
7. 7. The method according to any one of claims l to 6, wherein processing the user data corresponding to the user according to the calculated carbon-saving quantity of the user comprises:

   acquiring carbon-saving quantities of the user in multiple Internet services within a preset cycle time, accumulating the acquired carbon-saving quantities, and processing the user data according to an accumulated carbon-saving quantity.
8. 8. The method according to claim 7, wherein processing the user data according to an accumulated carbon-saving quantity comprises:

   accumulating the calculated accumulated carbon-saving quantity of the user within the preset cycle and a total carbon-saving quantity of the user, to obtain an updated total carbon-saving quantity, and processing the user data according to the updated total carbon-saving quantity.
9. 9. The method according to claim 8, wherein accumulating the calculated accumulated carbon-saving quantity of the user within the preset cycle and the total carbon-saving quantity of the user comprises:

   converting the calculated carbon-saving quantity of the user into points according to a preset conversion rule; and accuinulating the converted points and total points of the user, to obtain updated total points.
10. 10. The method according to claim 9, further comprising:

    providing a control configured to accumulate points for the user; and wherein accumulating the converted points and total points of the user comprises:

    receiving a confirming instruction sent by the user through the control, and accumulating the converted points and the total points of the user.
11. 11. The method according to claim 9, wherein the method further comprises:

    receiving an acquisition instruction sent by the user for non-accumulated points of other users;

    acquiring ail or some points in the non-accumulated points of other users according to the acquisition instruction; and accumulating the acquired ail or some points and the total points of the user.
12. 12. The method according to claim 9, wherein the method further comprises:

    'determining the updated total points of the user; and assigning, according to the updated total points, a virtual good matching the updated total points to the user.
13. 13. The method according to claim 12, wherein the virtual good has different display States according to different total points.
14. 14. An apparatus for data processing, the apparatus comprising a plurality of modules configured to perform the method of any one of claims 1 to 13.