CN115941716A - Device control method, electronic device, and computer-readable storage medium - Google Patents
Device control method, electronic device, and computer-readable storage medium Download PDFInfo
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Abstract
The application discloses a device control method, an electronic device, and a computer-readable storage medium, the device control method including: the cloud platform acquires data sent by target equipment or terminal application; the cloud platform is used for storing a product model corresponding to the target equipment; the product model is used for defining the capabilities supported by the target equipment; the data includes device characteristic data or control instructions; analyzing the data to obtain an identification result; in response to the recognition result not matching the product model, the data is filtered. According to the method and the device, the invalid instruction exceeding the set range of the product model can be controlled, so that the waste of network resources caused by invalid instruction interaction is avoided, and the cloud resources are fully utilized.
Description
Technical Field
The present application relates to the field of internet of things technology, and in particular, to an apparatus control method, an electronic apparatus, and a computer-readable storage medium.
Background
At present, the application of a cloud technology in the internet of things is a main direction of the development of the internet of things, a cloud internet of things platform (cloud platform) is used as a middle part for connecting internet of things equipment (intelligent equipment) and user terminal application, and before the internet of things equipment is connected to the cloud platform, a set of abstract product models corresponding to the internet of things equipment are formed on the cloud platform and used for defining services, attributes, commands and the like supported by the internet of things equipment, so that the cloud platform understands data reported by the internet of things equipment and instructions sent by the user terminal application, and the interaction between the user terminal application and the internet of things equipment is realized.
In the prior art, the interaction between the user terminal application and the intelligent device is to simply convert a control instruction sent by the user terminal application into a specific operation instruction based on a product model through a cloud platform, and directly issue the operation instruction to the corresponding intelligent device so that the intelligent device executes an operation, or directly report device data to the user terminal application after the cloud platform receives the device data reported by the intelligent device.
However, the above method interacts with each device data and each control command, and if there is an invalid command, for example, the control command or the device data exceeds the set range of the product model, network resources are wasted during the interaction, and cloud resources cannot be fully utilized.
Disclosure of Invention
The technical problem mainly solved by the application is to provide a device control method, an electronic device and a computer readable storage medium, which can solve the problem that invalid instructions cannot be controlled in the prior art.
In order to solve the above technical problem, a first technical solution adopted by the present application is to provide an apparatus control method, including: the cloud platform acquires data sent by target equipment or terminal application; the cloud platform is used for storing a product model corresponding to the target equipment; the product model is used for defining the capabilities supported by the target equipment; the data comprises device characteristic data or control instructions; analyzing the data to obtain an identification result; in response to the recognition result not matching the product model, the data is filtered.
The step of analyzing the data to obtain the identification result comprises the following steps: analyzing the data to extract each data field in the data; matching each extracted data field with the data field included in the product model to obtain an identification result; in response to the recognition result not matching the product model, a step of filtering the data, comprising: and responding to the data field which is not matched with the product model in the data, determining that the identification result is not matched with the product model, and filtering the data.
The cloud platform is also stored with a configuration rule table generated based on the product model, and the configuration rule table is used for managing the capability supported by the target equipment; the step of analyzing the data to obtain the identification result comprises the following steps: analyzing the data to extract each data field in the data; matching each extracted data field with a product model and data fields included in a configuration rule table to obtain an identification result; in response to the recognition result not matching the product model, a step of filtering the data, comprising: and responding to the data field which is not matched with the product model or the configuration rule table in the data, determining that the identification result is not matched with the product model or the configuration rule table, and filtering the data.
Wherein, in response to the data having a data field that does not match the product model or the configuration rule table, determining that the identification result does not match the product model or the configuration rule table, and filtering the data, comprises: filtering the data in response to a presence of at least one data field in the data that does not match a data field included in the product model; or, filtering the data in response to each data field in the data matching a data field included in the product model but there being at least one data field in the data that does not match a data field included in the configuration rule table.
If the data is the equipment characteristic data, after the step of analyzing the data to obtain the identification result, the method further comprises the following steps: reporting the equipment characteristic data to a terminal application in response to the fact that each data field in the equipment characteristic data is matched with a data field included in a configuration rule table; if the data is the control instruction, after the step of analyzing the data to obtain the identification result, the method further comprises the following steps: and responding to the fact that each data field in the control instruction is matched with the data field included in the configuration rule table, and issuing the control instruction to the target equipment so that the target equipment can execute the control instruction.
In order to solve the above technical problem, a second technical solution adopted by the present application is to provide an apparatus control method, including: the target equipment acquires a product model corresponding to the target equipment sent by the cloud platform; wherein the product model is used to define capabilities supported by the target device; the target equipment acquires data; wherein the data comprises device characteristic data or control instructions; analyzing the data to obtain an identification result; in response to the recognition result not matching the product model, the data is filtered.
Before the step of acquiring the product model corresponding to the target device sent by the cloud platform, the target device comprises: the target device sends a login request to the cloud platform, so that the cloud platform verifies the target device based on the login request, and sends the stored product model to the target device after the verification is passed.
If the data is the equipment characteristic data, analyzing the data to obtain an identification result, and then, the method comprises the following steps: reporting the equipment characteristic data to a cloud platform in response to the matching of the identification result and the product model; if the data is the control instruction, after the step of analyzing the data to obtain the identification result, the method comprises the following steps: and executing the control instruction in response to the recognition result being matched with the product model.
In order to solve the above technical problem, a third technical solution adopted by the present application is to provide an apparatus control method, including: the terminal application receives data input by a user based on target equipment; wherein, the data is a control instruction; and sending the data to the cloud platform so that the cloud platform analyzes the data to obtain an identification result, and determining whether to filter the data based on the identification result.
In order to solve the above technical problem, a fourth technical solution adopted by the present application is to provide an electronic device, including: a memory for storing program data which, when executed, implements the steps in the apparatus control method as in any one of the above; a processor for executing program instructions stored in the memory to implement the steps in the apparatus control method as claimed in any one of the above.
In order to solve the above technical problem, a fifth technical solution adopted by the present application is to provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps in the apparatus control method according to any one of the above descriptions are implemented.
The beneficial effect of this application is: different from the prior art, the device control method, the electronic device and the computer-readable storage medium provided by the application are characterized in that the product model corresponding to the target device is stored on the cloud platform, the obtained data sent by the target device or the terminal application is analyzed, and when the identification result is not matched with the product model, the data are filtered, so that invalid instructions exceeding the set range of the product model can be controlled, the waste of network resources caused by invalid instruction interaction is avoided, and the full utilization of cloud resources is realized.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a functional block diagram of an embodiment of a control system of the subject application;
FIG. 2 is a signal flow diagram of a first embodiment of the plant control system of FIG. 1;
FIG. 3 is a signal flow diagram of a second embodiment of the plant control system of FIG. 1;
FIG. 4 is a schematic flow chart of a first embodiment of the control method of the apparatus of the present application;
FIG. 5 is a schematic flow chart of a second embodiment of the apparatus control method of the present application;
FIG. 6 is a schematic flow chart of a third embodiment of the apparatus control method of the present application;
FIG. 7 is a schematic flow chart diagram of a fourth embodiment of the apparatus control method of the present application;
FIG. 8 is a flowchart of a first application scenario of the apparatus control method of the present application;
FIG. 9 is a flowchart illustrating a second application scenario of the device control method of the present application;
FIG. 10 is a schematic structural diagram of an embodiment of a cloud platform of the present application;
FIG. 11 is a schematic block diagram of an embodiment of a target device of the present application;
FIG. 12 is a schematic block diagram of an embodiment of a terminal application of the present application;
FIG. 13 is a schematic diagram of an embodiment of an electronic device of the present application;
FIG. 14 is a schematic structural diagram of an embodiment of a computer-readable storage medium according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the examples of this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, the "plurality" typically includes at least two, but does not exclude the presence of at least one.
It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
It should be understood that the terms "comprises," "comprising," or any other variation thereof, as used herein, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.
The present application first provides an appliance control system.
Specifically, referring to fig. 1, fig. 1 is a schematic block diagram of an embodiment of an apparatus control system according to the present application. In this embodiment, the device control system 100 includes a target device 101, a cloud platform 102, and a terminal application 103, which are connected in sequence.
In this embodiment, the target device 101 refers to an internet of things device registered and bound on the cloud platform 102, and the target device 101 is configured to report the acquired device feature data to the cloud platform 102 or receive a control instruction forwarded by the cloud platform 102.
The target device 101 is generally an intelligent device having a certain capability in a certain industry, and data obtained by the target device 101 using the capability is device characteristic data.
The target device 101 may be an alarm, a camera, a street lamp, a household water meter, a household thermometer, or the like, which is not limited in this application.
In a specific implementation scenario, if the target device 101 is a camera, the device characteristic data is a video image captured by the camera. In another specific implementation scenario, if the target device 101 is a smoke alarm, the device characteristic data is a smoke concentration collected by the smoke alarm, which is not limited in this application.
In this embodiment, the cloud platform 102 is an internet of things platform based on cloud computing, the cloud platform 102 is used as a middle part for connecting the target device 101 and the terminal Application 103, the cloud platform 102 is connected to the mass target device 101 downward, collects device characteristic data collected by the target device 101, and provides an Application Programming Interface (API) for the terminal Application 103 upward, and the terminal Application 103 issues a control command to the target device 101 by calling the API, so as to implement remote control. The cloud platform 102 supports endpoint management, connection and network management, data processing and analysis, security access control, and the like, and the present application relates generally to connection and network management functions of the cloud platform 102.
The cloud platform 102 stores a product model corresponding to the target device 101. Wherein, a product model (Profile) is written by the user for describing the capabilities and characteristics of the target device 101. An abstract model corresponding to the target device 101 is built on the cloud platform 102, so that the cloud platform 102 can understand information such as services, attributes, commands and the like supported by the target device 101 (i.e., capabilities supported by the target device 101).
In this embodiment, the terminal application 103 is a computer program running on an operating system, and interacts with the cloud platform 102 through an API provided by the cloud platform 102 to issue a control instruction or receive device characteristic data forwarded by the cloud platform 102.
In a specific implementation scenario, the terminal application 103 is a traffic management system, runs on a computer of a traffic administration staff, receives a User instruction through a UI (User Interface) Interface, and presents device characteristic data (video image) acquired by the target device 101 (here, the target device 101 is a camera) to a User. In another specific implementation scenario, the terminal Application 103 is an Application APP (Application), runs on a mobile phone of a user, receives a user instruction through a UI interface, and presents device characteristic data (smoke concentration) collected by the target device 101 (here, the target device 101 is a smoke alarm) to the user.
Referring to fig. 2, fig. 2 is a signal flow diagram of a first embodiment of the device control system of fig. 1. In this embodiment, the target device 101 sends a login request to the cloud platform 102, so that the cloud platform 102 authenticates the target device 101 based on the login request, and sends the stored product model corresponding to the target device 101 after the authentication is passed. After the target device 101 acquires the data, the data is analyzed to obtain an identification result, and the data is filtered in response to the fact that the identification result is not matched with the product model. Responding to the matching of the recognition result and the product model, and if the data is the equipment characteristic data, sending the equipment characteristic data to the cloud platform 102; and if the data is the control instruction, executing the control instruction. The terminal application 103 receives data input by the user based on the target device 101, and sends the data to the cloud platform 102, where the data is a control instruction. After receiving the data sent by the target device 101 or the terminal application 103, the cloud platform 102 analyzes the data to obtain an identification result, and filters the data in response to the fact that the identification result is not matched with the product model. Responding to the matching of the recognition result and the product model, and if the data is equipment characteristic data, sending the equipment characteristic data to the terminal application 103; in response to the data being a control instruction, the control instruction is sent to the target apparatus 101 to cause the target apparatus 101 to execute the control instruction.
Optionally, the cloud platform 102 further stores a configuration rule table generated based on the product model, and the configuration rule table is used for managing the capabilities supported by the target device 101. Referring to fig. 3, fig. 3 is a signal flow diagram of a second embodiment of the device control system of fig. 1.
In this embodiment, the target device 101 sends a login request to the cloud platform 102, so that the cloud platform 102 authenticates the target device 101 based on the login request, and sends the stored product model corresponding to the target device 101 after the authentication is passed. After the target device 101 acquires the data, the data is analyzed to obtain an identification result, and the data is filtered in response to the fact that the identification result is not matched with the product model. Responding to the matching of the recognition result and the product model, and if the data is the equipment characteristic data, sending the equipment characteristic data to the cloud platform 102; and if the data is the control instruction, executing the control instruction. The terminal application 103 receives data input by the user based on the target device 101, and sends the data to the cloud platform 102, where the data is a control instruction. After receiving the data sent by the target device 101 or the terminal application 103, the cloud platform 102 analyzes the data to obtain an identification result, and filters the data in response to the fact that the identification result is not matched with the product model; alternatively, the data is filtered in response to the recognition result matching the product model but the recognition result not matching the configuration rule table. Responding to the matching of the identification result and the configuration rule table, and if the data is the equipment characteristic data, sending the equipment characteristic data to the terminal application 103; in response to the data being a control instruction, the control instruction is transmitted to the target apparatus 101 to cause the target apparatus 101 to execute the control instruction.
Referring to fig. 4, fig. 4 is a schematic flow chart of a first embodiment of an apparatus control method according to the present application. In this embodiment, the execution subject of the method is a cloud platform, and the method includes:
s41: the cloud platform acquires data sent by target equipment or terminal application; the cloud platform is used for storing a product model corresponding to target equipment; the product model is used for defining the capabilities supported by the target equipment; the data includes device characteristic data or control instructions.
In this embodiment, the product model refers to an abstract model written by a user for describing capabilities and characteristics of a target device. An abstract model corresponding to the target device is built on the cloud platform in advance, so that the cloud platform can understand information such as services, attributes, commands and the like supported by the target device (namely, capabilities supported by the target device).
The product model may be a JSON-formatted file, such as a Service Type (Service Type), a Service identifier (Service ID), and the like. The product model may also be XML or binary, and the like, which is not limited in this application.
For example, taking a product model developed by a Smoke Alarm as an example, the product model has a Smoke concentration Alarm function, and is converted into a JSON format file to be stored in a cloud platform, so that the cloud platform can understand the capability supported by the Smoke Alarm, and then when the Smoke Alarm reports data, if the data includes a "Smoke concentration Alarm" field, the cloud platform can identify that the device has the Alarm capability according to a prestored product model file, so as to realize device control.
In this embodiment, the device feature data is data acquired by the target device using the capability of the target device.
Wherein the device characteristic data is generally written in the form of key-value pairs. Key and value can specify contents at will, as long as one-to-one correspondence is ensured. For example, if the target device is a thermometer, the reported device characteristic data may include "Temp:32 "(" temperature: 27 degrees "), where" Temp "is the field name and" 27 "is the field value.
The file format of the device feature data may be JSON, XML, binary, or the like, as long as the cloud platform can recognize the fields and the corresponding values therein, which is not limited in the present application.
In this embodiment, the control instruction is a user instruction received by the terminal application through the UI interface.
S42: and analyzing the data to obtain an identification result.
In this embodiment, after receiving the data, the cloud platform analyzes the data to extract each data field in the data, and matches each extracted data field with a data field included in the product model to obtain an identification result.
In a specific implementation scenario, if the data is device feature data sent by the target device, the cloud platform analyzes the device feature data to extract each data field in the device feature data, and matches each extracted data field with a data field included in the product model to obtain an identification result.
In another specific implementation scenario, if the data is a control instruction sent by the terminal application, the cloud platform analyzes the control instruction to extract each data field in the control instruction, and matches each extracted data field with a data field included in the product model to obtain an identification result.
S43: in response to the recognition result not matching the product model, the data is filtered.
In this embodiment, in response to the data field that does not match the product model being present in the data, it is determined that the identification result does not match the product model, and the data is filtered.
In one specific implementation scenario, in response to the presence of a data field in the device characteristic data that does not match the product model, the device characteristic data is filtered by determining that the identification result does not match the product model.
In another specific implementation scenario, the control instructions are filtered in response to the control instructions having data fields that do not match the product model, and the identification result is determined to not match the product model.
In another specific implementation scenario, if the data is device feature data, reporting the device feature data to the terminal application in response to each data field in the device feature data being matched with a data field included in the product model.
In another specific implementation scenario, if the data is a control instruction, in response to that each data field in the control instruction matches with a data field included in the product model, the control instruction is issued to the target device, so that the target device executes the control instruction.
It can be understood that if a data field unmatched with the product model exists in certain data, the data is shown to exceed the setting range of the product model and belong to an invalid instruction, the cloud platform is used for filtering the invalid instruction, so that a control instruction exceeding the setting range of the product model can be prevented from being issued to a target device, or device characteristic data exceeding the setting range of the product model can be prevented from being reported to a terminal for application, and therefore waste of network resources is avoided.
Different from the prior art, the embodiment stores the product model corresponding to the target device on the cloud platform, analyzes the acquired data sent by the target device or the terminal application, and filters the data when the identification result is not matched with the product model, so that the invalid instruction exceeding the set range of the product model can be controlled, the waste of network resources caused by invalid instruction interaction is avoided, and the full utilization of the cloud resources is realized.
Referring to fig. 5, fig. 5 is a flowchart illustrating a second embodiment of the apparatus control method according to the present application. In this embodiment, the execution subject of the method is a cloud platform, and the method includes:
s51: the cloud platform acquires data sent by target equipment or terminal application; the cloud platform is used for storing a product model corresponding to the target equipment and a configuration rule table generated based on the product model; the product model is used for defining the capabilities supported by the target equipment; the data includes device characteristic data or control instructions.
In this embodiment, the product model includes all capabilities supported by the target device, and may generate a multi-service scenario based on different capabilities, where the service scenario is used to describe a scenario when the target device applies the capabilities supported by the target device, and the configuration rule is an execution rule formulated by the user based on the corresponding service scenario, and the configuration rule table is a capability control table formed by combining multiple configuration rules.
In one specific implementation scenario, if the target device is a smoke alarm installed in a kitchen, the target device has the following capabilities: 1) Detecting the smoke concentration of the kitchen; 2) Reporting the detected smoke concentration; 3) And when the detected smoke concentration exceeds a set threshold value, triggering an alarm device to give an alarm. The service scenario generated based on the above capability may include: 1) "controlling smoke concentration reporting according to time"; 2) "trigger alarm device according to time control", the user can set 2 configuration rules based on the above two scene models: 1) (ii) not reporting the detected smoke concentration for a fixed period of time (11-12 or 5-00; 2) In a fixed time period (11.
It can be understood that, in a fixed time period (11-12 or 5-00.
In another specific implementation scenario, if the target device is a street lamp disposed on a roadside, the target device has the following capabilities: 1) Illuminating; 2) The brightness is automatically adjusted. The service scenario generated based on the above capability may include: 1) "turn on illumination according to time"; 2) "adjust brightness according to time", the user can set 2 configuration rules based on the above two scene models: 1) Turning on the illumination for a fixed period of time (19; 2) And in a fixed time period (23.
It can be understood that in a fixed time period (19 to 6). Further, in a fixed time period (23.
In this embodiment, the configuration rule is set by the user based on the control requirement, and in other embodiments, the configuration rule may also be directly set by the cloud platform according to the big data analysis, and the relevant rule is automatically executed without user intervention, which is not limited in this application.
Compared with the single control method in the prior art, the configuration rule table is set in the embodiment, the target equipment can be controlled based on different service scenes in the set range of the product model, and therefore the control requirement of the user on the target equipment is met.
S52: and analyzing the data to obtain an identification result.
In this embodiment, after receiving the data, the cloud platform analyzes the data to extract each data field in the data, and matches each extracted data field with the data fields included in the product model and the configuration rule table to obtain the identification result.
In a specific implementation scenario, if the data is device feature data sent by a target device, the cloud platform analyzes the device feature data to extract each data field in the device feature data, and matches each extracted data field with data fields included in a product model and a configuration rule table to obtain an identification result.
In another specific implementation scenario, if the data is a control instruction sent by the terminal application, the cloud platform analyzes the control instruction to extract each data field in the control instruction, and matches each extracted data field with the data fields included in the product model and the configuration table to obtain an identification result.
S53: and responding to the data field which is not matched with the product model or the configuration rule table in the data, determining that the identification result is not matched with the product model or the configuration rule table, and filtering the data.
In this embodiment, in response to the data having a data field that does not match the product model or the configuration rule table, it is determined that the identification result does not match the product model or the configuration rule table, and the data is filtered.
In one particular implementation scenario, data is filtered in response to the presence of at least one data field in the data that does not match a data field included in the product model.
It can be understood that if a data field unmatched with the product model exists in certain data, the data is shown to exceed the setting range of the product model and belong to an invalid instruction, the cloud platform is used for filtering the invalid instruction, so that a control instruction exceeding the setting range of the product model can be prevented from being issued to a target device, or device characteristic data exceeding the setting range of the product model can be prevented from being reported to a terminal for application, and therefore waste of network resources is avoided.
In another particular implementation scenario, the data is filtered in response to each data field in the data matching a data field included in the product model but at least one data field in the data not matching a data field included in the configuration rule table.
It can be understood that if the data fields in a certain data all match the product model, but there is at least one data field that does not match the data fields included in the configuration rule table, it indicates that the data does not exceed the set range of the product model, but exceeds the configuration rule, and belongs to the limited instruction. Taking the above street lamp as an example, the configuration rule is "turn on the lighting in a fixed time period (19 00-6).
In another specific implementation scenario, if the data is the device feature data, reporting the device feature data to the terminal application in response to that each data field in the device feature data matches with a data field included in the configuration rule table.
In another specific implementation scenario, if the data is a control instruction, in response to that each data field in the control instruction matches with a data field included in the configuration rule table, the control instruction is issued to the target device, so that the target device executes the control instruction.
It can be understood that, by filtering the data beyond the setting range of the configuration rule table, the control instruction which does not satisfy the configuration rule can be limited to be issued to the target device or the device characteristic data which does not satisfy the configuration rule can be limited to be reported to the terminal application under the condition that the data does not exceed the setting range of the product model, so that only the instruction which satisfies the configuration rule can be executed, and the purposes of saving the hardware cost of the target device and saving the network resources can be achieved.
Different from the prior art, in the embodiment, the product model corresponding to the target device and the configuration rule table generated based on the product model are stored on the cloud platform, the acquired data sent by the target device or the terminal application are analyzed, and the data are filtered when the identification result is not matched with the product model or the configuration rule table, so that invalid instructions exceeding the set range of the product model can be controlled, and instructions which do not meet the configuration rule can be limited under the condition that the identification result does not exceed the set range of the product model, thereby avoiding the waste of network resources caused by invalid instruction interaction, realizing the full utilization of cloud resources, and saving hardware cost.
Referring to fig. 6, fig. 6 is a schematic flow chart of a third embodiment of the apparatus control method according to the present application. In this embodiment, the subject of the execution of the method is a target device, and the method includes:
s61: the target equipment acquires a product model corresponding to the target equipment sent by the cloud platform; wherein the product model is used to define capabilities supported by the target device.
In this embodiment, before the step of acquiring, by the target device, the product model corresponding to the target device sent by the cloud platform, the method includes: the target device sends a login request to the cloud platform, so that the cloud platform verifies the target device based on the login request, and sends the stored product model to the target device after the verification is passed.
And when the target equipment is offline, the product model is not stored, and only when the target equipment logs in again, the product model sent by the cloud platform is obtained online.
The target device can acquire the product model and the control instruction forwarded by the cloud platform only after the authentication is passed, so that the device which is not registered on the cloud platform can be prevented from acquiring relevant information.
S62: the target equipment acquires data; wherein the data comprises device characteristic data or control instructions.
In this embodiment, the device characteristic data is data acquired by the target device by applying the capability of the target device, and the control instruction is a user instruction which is forwarded by the cloud platform and received by the terminal application through the UI interface.
S63: and analyzing the data to obtain an identification result.
In this embodiment, the target device analyzes the data to extract each data field in the data, and matches each extracted data field with a data field included in the product model to obtain an identification result.
S64: in response to the recognition result not matching the product model, the data is filtered.
In one specific implementation scenario, in response to the presence of a data field in the device characteristic data that does not match the product model, the device characteristic data is filtered by determining that the identification result does not match the product model.
In another specific implementation scenario, the control instructions are filtered in response to the control instructions having data fields that do not match the product model, and the identification result is determined to not match the product model.
In another specific implementation scenario, if the data is device feature data, reporting the device feature data to the cloud platform in response to each data field in the device feature data being matched with a data field included in the product model.
In another specific implementation scenario, if the data is a control instruction, the control instruction is executed in response to each data field in the control instruction matching a data field included in the product model.
It can be understood that if a data field unmatched with the product model exists in certain data, it indicates that the data exceeds the setting range of the product model and belongs to an invalid instruction, and the invalid instruction is filtered by using the target device, so that the target device can be prevented from reporting the device feature data exceeding the setting range of the product model to the cloud platform, or the target device is prevented from executing a control instruction exceeding the setting range of the product model, and thus hardware cost is saved and waste of network resources is avoided.
Referring to fig. 7, fig. 7 is a schematic flow chart illustrating a fourth embodiment of a device control method according to the present application. In this embodiment, the execution subject of the method is a terminal application, and the method includes:
s71: the terminal application receives data input by a user based on target equipment; wherein the data is a control command.
In this embodiment, the terminal application receives a control instruction input by the user based on the target device through the UI interface.
S72: and sending the data to the cloud platform so that the cloud platform analyzes the data to obtain an identification result, and determining whether to filter the data based on the identification result.
In a specific implementation scenario, if only the product model is stored in the cloud platform, the cloud platform determines that the identification result is not matched with the product model, and filters the control instruction. Or the cloud platform determines that the recognition result is matched with the product model, and issues the control command to the target device.
In another specific implementation scenario, if the cloud platform stores the product model and the configuration rule table, the cloud platform determines that the identification result is not matched with the product model or the configuration rule table, and filters the control instruction. Or the cloud platform determines that the identification result is matched with the configuration rule table, and issues the control instruction to the target device.
The product model corresponding to the target device is stored on the cloud platform, the acquired data sent by the terminal application are analyzed, and when the identification result is not matched with the product model, the data are filtered, and the invalid instruction exceeding the set range of the product model can be controlled, so that the waste of network resources caused by invalid instruction interaction is avoided, and the full utilization of cloud resources is realized.
Referring to fig. 8, fig. 8 is a flowchart illustrating a first application scenario of the device control method according to the present application. In this embodiment, after the target device obtains the device characteristic data, the data is analyzed to obtain an identification result, and the data is filtered in response to a mismatch between the identification result and the product model. And responding to the matching of the recognition result and the product model, and sending the equipment characteristic data to the cloud platform. And after receiving the data sent by the target equipment, the cloud platform analyzes the data to obtain an identification result, and filters the data in response to the fact that the identification result is not matched with the product model. And reporting the equipment characteristic data to the terminal application in response to the matching of the identification result and the product model.
Referring to fig. 9, fig. 9 is a flowchart illustrating a second application scenario of the device control method according to the present application. In this embodiment, the terminal application receives a control instruction input by a user based on the target device, and then issues the data to the cloud platform. After receiving the data sent by the terminal application 103, the cloud platform analyzes the data to obtain an identification result, and filters the data in response to the fact that the identification result is not matched with the product model. In response to the recognition result matching the product model but the recognition result not matching the configuration rule table, filtering the data. And responding to the matching of the identification result and the configuration rule table, and sending the data to the target equipment. And after receiving the data, the target equipment analyzes the data to obtain an identification result, and filters the data in response to the mismatching of the identification result and the product model. And executing the control instruction in response to the recognition result being matched with the product model.
Correspondingly, the application provides a related device of the equipment control method.
Referring to fig. 10, fig. 10 is a schematic structural diagram of an embodiment of a cloud platform of the present application. In this embodiment, the cloud platform 1000 includes a first storage module 1001, a first obtaining module 1002, a first analyzing module 1003, and a first filtering module 1004.
A first storage module 1001, configured to store a product model corresponding to a target device; the product model is used to define the capabilities supported by the target device.
A first obtaining module 1002, configured to obtain data sent by a target device or a terminal application; the data includes device characteristic data or control instructions.
The first parsing module 1003 is configured to parse the data to obtain an identification result.
A first filtering module 1004 for filtering the data in response to the recognition result not matching the product model.
For details, please refer to the related text descriptions in S41 to S43 and S51 to S53, which are not described herein again.
Referring to fig. 11, fig. 11 is a schematic structural diagram of an embodiment of a target device according to the present application. As shown in fig. 11, in the present embodiment, the target device 1100 includes a product model acquisition module 1101, a second acquisition module 1102, a second parsing module 1103, and a second filtering module 1104.
A product model obtaining module 1101, configured to obtain a product model corresponding to a target device sent by a cloud platform; wherein the product model is used to define capabilities supported by the target device.
A second obtaining module 1102, configured to obtain data; wherein the data comprises device characteristic data or control instructions.
The second parsing module 1103 is configured to parse the data to obtain an identification result.
A second filtering module 1104 for filtering the data in response to the recognition result not matching the product model.
For a specific process, please refer to the description of the relevant text in S61 to S64, which is not described herein again.
Referring to fig. 12, fig. 12 is a schematic structural diagram of an embodiment of a terminal application according to the present application. As shown in fig. 12, in the present embodiment, terminal application 1200 includes a receiving module 1201 and a transmitting module 1202.
A receiving module 1201, configured to receive data input by a user based on a target device; wherein the data is a control command.
The sending module 1202 is configured to send the data to the cloud platform, so that the cloud platform analyzes the data to obtain an identification result, and determines whether to filter the data based on the identification result.
For details, please refer to the description of the relevant text in S71-S72, which is not described herein again.
Different from the prior art, the product model corresponding to the target device 1100 is stored on the cloud platform 1000, the obtained data sent by the target device 1100 or the terminal application 1200 are analyzed, and when the identification result is not matched with the product model, the data are filtered, so that the invalid instruction exceeding the set range of the product model can be controlled, the waste of network resources caused by invalid instruction interaction is avoided, and the full utilization of cloud resources is realized.
Referring to fig. 13, fig. 13 is a schematic structural diagram of an embodiment of an electronic device according to the present application. As shown in fig. 13, in this embodiment, an electronic device 1300 includes a memory 1301 and a processor 1302.
In the present embodiment, the memory 1301 is used to store program data, which when executed implement the steps in the device control method as described above; the processor 1302 is configured to execute program instructions stored in the memory 1301 to implement the steps in the device control method as described above.
Specifically, the processor 1302 is configured to control itself and the memory 1301 to implement the steps in the device control method as described above. Processor 1302 may also be referred to as a CPU (Central Processing Unit). The processor 1302 may be an integrated circuit chip having signal processing capabilities. The Processor 1302 may also be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. In addition, processor 1302 may be implemented collectively by multiple integrated circuit chips.
Different from the prior art, in the embodiment, the processor 1302 stores the product model corresponding to the target device on the cloud platform, analyzes the acquired data sent by the target device or the terminal application, and filters the data when the identification result is not matched with the product model, so that the invalid instruction exceeding the set range of the product model can be controlled, thereby avoiding the waste of network resources caused by invalid instruction interaction, and further realizing the full utilization of cloud resources.
Correspondingly, the application provides a computer readable storage medium.
Referring to fig. 14, fig. 14 is a schematic structural diagram of an embodiment of a computer-readable storage medium according to the present application.
The computer-readable storage medium 1400 includes a computer program 1401 stored on the computer-readable storage medium 1400, and the computer program 1401 implements the steps in the device control method as described above when executed by the processor described above. In particular, the integrated unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in one computer-readable storage medium 1400. Based on such understanding, the technical solutions of the present application, which are essential or contribute to the prior art, or all or part of the technical solutions may be embodied in the form of a software product, which is stored in a computer-readable storage medium 1400 and includes several instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the methods of the embodiments of the present application. And the aforementioned computer-readable storage medium 1400 includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a module or a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some interfaces, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
If the technical scheme of the application relates to personal information, a product applying the technical scheme of the application clearly informs personal information processing rules before processing the personal information, and obtains personal independent consent. If the technical scheme of the application relates to sensitive personal information, a product applying the technical scheme of the application obtains individual consent before processing the sensitive personal information, and simultaneously meets the requirement of 'express consent'. For example, at a personal information collection device such as a camera, a clear and significant identifier is set to inform that the personal information collection range is entered, the personal information is collected, and if the person voluntarily enters the collection range, the person is considered as agreeing to collect the personal information; or on the device for processing the personal information, under the condition of informing the personal information processing rule by using obvious identification/information, obtaining personal authorization by modes of popping window information or asking a person to upload personal information of the person by himself, and the like; the personal information processing rule may include information such as a personal information processor, a personal information processing purpose, a processing method, and a type of personal information to be processed.
Claims (11)
1. An apparatus control method characterized by comprising:
the cloud platform acquires data sent by target equipment or terminal application; the cloud platform is used for storing a product model corresponding to the target equipment; the product model is used for defining the capabilities supported by the target device; the data comprises device characteristic data or control instructions;
analyzing the data to obtain an identification result;
filtering the data in response to the recognition result not matching the product model.
2. The apparatus control method according to claim 1,
the step of analyzing the data to obtain an identification result comprises the following steps:
analyzing the data to extract each data field in the data;
matching each extracted data field with the data fields included in the product model to obtain the identification result;
the step of filtering the data in response to the recognition result not matching the product model comprises:
and in response to the data field which does not match the product model existing in the data, determining that the identification result does not match the product model, and filtering the data.
3. The apparatus control method according to claim 2,
the cloud platform is also stored with a configuration rule table generated based on the product model, and the configuration rule table is used for managing the capability supported by the target equipment;
the step of analyzing the data to obtain an identification result comprises the following steps:
analyzing the data to extract each data field in the data;
matching each extracted data field with the product model and the data fields included in the configuration rule table to obtain the identification result;
the step of filtering the data in response to the recognition result not matching the product model comprises:
in response to a data field in the data that does not match the product model or the configuration rule table, determining that the identification result does not match the product model or the configuration rule table, filtering the data.
4. The apparatus control method according to claim 3,
the step of filtering the data in response to the data having a data field that does not match the product model or the configuration rule table determining that the identification result does not match the product model or the configuration rule table comprises:
filtering the data in response to a presence of at least one data field in the data that does not match a data field included in the product model; or the like, or, alternatively,
filtering the data in response to each data field in the data matching a data field included in the product model but at least one data field in the data not matching a data field included in the configuration rule table.
5. The apparatus control method according to claim 4,
if the data is the device characteristic data, after the step of analyzing the data to obtain the identification result, the method further comprises the following steps:
reporting the equipment characteristic data to the terminal application in response to that each data field in the equipment characteristic data is matched with a data field included in the configuration rule table;
if the data is the control instruction, after the step of analyzing the data to obtain the identification result, the method further comprises:
and responding to the fact that each data field in the control instruction is matched with the data field included in the configuration rule table, and issuing the control instruction to the target equipment so that the target equipment executes the control instruction.
6. An apparatus control method characterized by comprising:
the method comprises the steps that target equipment obtains a product model corresponding to the target equipment sent by a cloud platform; wherein the product model is used to define capabilities supported by the target device;
the target device acquires data; wherein the data comprises device characteristic data or control instructions;
analyzing the data to obtain an identification result;
filtering the data in response to the recognition result not matching the product model.
7. The apparatus control method according to claim 6,
before the step of acquiring, by the target device, the product model corresponding to the target device sent by the cloud platform, the method includes:
the target device sends a login request to the cloud platform so that the cloud platform verifies the target device based on the login request, and sends the stored product model to the target device after the verification is passed.
8. The apparatus control method according to claim 6 or 7,
if the data is the equipment characteristic data, after the step of analyzing the data to obtain the identification result, the method comprises the following steps:
reporting the equipment characteristic data to the cloud platform in response to the recognition result being matched with the product model;
if the data is the control instruction, after the step of analyzing the data to obtain the identification result, the method comprises the following steps:
and executing the control instruction in response to the recognition result being matched with the product model.
9. An apparatus control method characterized by comprising:
the terminal application receives data input by a user based on target equipment; wherein the data is a control instruction;
and sending the data to a cloud platform so that the cloud platform analyzes the data to obtain an identification result, and determining whether to filter the data based on the identification result.
10. An electronic device, comprising:
a memory for storing program data which when executed implements the steps in the apparatus control method of any one of claims 1 to 5 or the apparatus control method of any one of claims 6 to 8 or the apparatus control method of claim 9;
a processor for executing the program instructions stored by the memory to implement the steps in the device control method of any one of claims 1 to 5 or the device control method of any one of claims 6 to 8 or the device control method of claim 9.
11. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements the steps in the device control method of any one of claims 1 to 5 or the device control method of any one of claims 6 to 8 or the device control method of claim 9.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117061588A (en) * | 2023-10-11 | 2023-11-14 | 深圳麦格米特电气股份有限公司 | Device access method, electronic device, and computer-readable storage medium |
| CN117857608A (en) * | 2024-03-07 | 2024-04-09 | 安徽慕京信息技术有限公司 | Method and system for collecting equipment data based on Internet of things platform |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117061588A (en) * | 2023-10-11 | 2023-11-14 | 深圳麦格米特电气股份有限公司 | Device access method, electronic device, and computer-readable storage medium |
| CN117061588B (en) * | 2023-10-11 | 2024-03-12 | 深圳麦格米特电气股份有限公司 | Device access method, electronic device, and computer-readable storage medium |
| CN117857608A (en) * | 2024-03-07 | 2024-04-09 | 安徽慕京信息技术有限公司 | Method and system for collecting equipment data based on Internet of things platform |
| CN117857608B (en) * | 2024-03-07 | 2024-05-03 | 安徽慕京信息技术有限公司 | Method and system for collecting equipment data based on Internet of things platform |
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