WO2021217665A1 - 一种座椅调节方法、装置及*** - Google Patents

一种座椅调节方法、装置及*** Download PDF

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Publication number
WO2021217665A1
WO2021217665A1 PCT/CN2020/088516 CN2020088516W WO2021217665A1 WO 2021217665 A1 WO2021217665 A1 WO 2021217665A1 CN 2020088516 W CN2020088516 W CN 2020088516W WO 2021217665 A1 WO2021217665 A1 WO 2021217665A1
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WO
WIPO (PCT)
Prior art keywords
information
user
historical data
historical
seat
Prior art date
Application number
PCT/CN2020/088516
Other languages
English (en)
French (fr)
Inventor
金舟
张�荣
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN202210153275.3A priority Critical patent/CN114435196A/zh
Priority to PCT/CN2020/088516 priority patent/WO2021217665A1/zh
Priority to KR1020227041449A priority patent/KR20230003085A/ko
Priority to EP20933281.6A priority patent/EP4134271A4/en
Priority to BR112022021990A priority patent/BR112022021990A2/pt
Priority to CN202080004933.1A priority patent/CN112638703B/zh
Publication of WO2021217665A1 publication Critical patent/WO2021217665A1/zh

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/0224—Non-manual adjustments, e.g. with electrical operation
    • B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
    • B60N2/0268—Non-manual adjustments, e.g. with electrical operation with logic circuits using sensors or detectors for adapting the seat or seat part, e.g. to the position of an occupant
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/02—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles the seat or part thereof being movable, e.g. adjustable
    • B60N2/0224—Non-manual adjustments, e.g. with electrical operation
    • B60N2/0244—Non-manual adjustments, e.g. with electrical operation with logic circuits
    • B60N2/0248—Non-manual adjustments, e.g. with electrical operation with logic circuits with memory of positions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/002—Seats provided with an occupancy detection means mounted therein or thereon
    • B60N2/0021—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement
    • B60N2/0022—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement for sensing anthropometric parameters, e.g. heart rate or body temperature
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/002—Seats provided with an occupancy detection means mounted therein or thereon
    • B60N2/0021—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement
    • B60N2/0023—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement for detection of driver fatigue
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2/00—Seats specially adapted for vehicles; Arrangement or mounting of seats in vehicles
    • B60N2/002—Seats provided with an occupancy detection means mounted therein or thereon
    • B60N2/0021—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement
    • B60N2/0024—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement for identifying, categorising or investigation of the occupant or object on the seat
    • B60N2/0027—Seats provided with an occupancy detection means mounted therein or thereon characterised by the type of sensor or measurement for identifying, categorising or investigation of the occupant or object on the seat for detecting the position of the occupant or of occupant's body part
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60N—SEATS SPECIALLY ADAPTED FOR VEHICLES; VEHICLE PASSENGER ACCOMMODATION NOT OTHERWISE PROVIDED FOR
    • B60N2220/00—Computerised treatment of data for controlling of seats
    • B60N2220/10—Computerised treatment of data for controlling of seats using a database

Definitions

  • This application relates to the field of automobile technology, and in particular to a seat adjustment method, device and system.
  • the parameters of the seat are often adjusted to preset parameters, so as to avoid the user from manually adjusting the seat and realize the liberation of the user's hands.
  • the preset parameters are fixed parameters set by the manufacturer in advance. Therefore, this seat adjustment method is relatively rigid, not flexible enough, and cannot meet the needs of differentiated users.
  • the embodiments of the present application provide a seat adjustment method, device and system, which can meet the needs of differentiated users, avoid adjusting the seat according to the fixed parameters set in advance by the manufacturer, and also provide users with a more flexible seat adjustment method. , To better enhance the user experience.
  • a seat adjustment method including: obtaining user information and status information corresponding to the user; determining the seat parameters corresponding to the user according to the user information and the status information; Adjust the seat corresponding to the seat parameters.
  • the user’s corresponding user information and status information are used to configure the corresponding seat parameters for the user, which meets the needs of differentiated users, avoids adjusting the seat according to the fixed parameters set by the manufacturer in advance, and also It provides users with more flexible seat adjustment methods and better improves user experience.
  • the obtaining user information corresponding to the user includes: recognizing the identity information of the user through a camera, or recognizing the identity information input by the user; Identity information to obtain the user information.
  • the status information includes at least one of the following: environmental information, time information, or geographic location information, and the environmental information includes environmental information in the vehicle and/or environment outside the vehicle information.
  • the determining the seat parameters corresponding to the user according to the user information and the status information includes: sending the user information and the status to a cloud server Information; receiving the seat parameters corresponding to the user sent by the cloud server; or, obtaining N pieces of historical data according to the user information and the status information, where N is an integer greater than 0; according to the N Pieces of historical data to determine the seat parameters corresponding to the user.
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • the obtaining N pieces of historical data according to the user information and the status information includes: sending the user information and the status information to the cloud server; Receiving the N pieces of historical data sent by the cloud server.
  • the cloud server can determine the historical data based on the user information and the status information to prepare for the subsequent determination of the seat parameters based on the historical data.
  • the obtaining N pieces of historical data according to the user information and the status information includes: obtaining historical data belonging to different categories from a database according to the user information
  • the historical data includes historical state information, and the category is determined according to the similarity of the historical state information; and the N pieces of historical data belonging to the same category are determined from the historical data according to the state information.
  • each piece of historical data in the N pieces of historical data includes a historical score and a historical seat parameter
  • the corresponding piece of the user is determined according to the N pieces of historical data.
  • Seat parameters include: obtaining M pieces of historical data from the N pieces of historical data according to preset conditions, and the preset conditions include one of the following: the highest score, the score higher than the threshold, or the highest score
  • the M is an integer greater than 0 and less than the N
  • the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • the user's corresponding seat parameters can be determined based on the score, so that the user's needs can be better controlled, and the user's needs can also be provided with seat parameters that meet their needs.
  • each piece of historical data in the N pieces of historical data further includes historical state information, and the historical state information includes historical time information.
  • the method further includes:
  • the N weights corresponding to the N pieces of historical data wherein the smaller the difference is , The greater the weight; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined, and any one of the N scoring coefficients A is based on the The weight corresponding to the scoring coefficient A and the historical score corresponding to the scoring coefficient A are determined; the N scoring coefficients are updated to the N historical scorings, and the N scoring coefficients are one-to-one with the N historical scorings. correspond.
  • a seat adjustment device including: a transceiver module for obtaining user information and status information corresponding to the user; a processing module for determining the user information and status information corresponding to the user The seat parameters; the processing module is also used to adjust the seat according to the user's corresponding seat parameters.
  • the processing module when obtaining user information corresponding to the user, is configured to identify the identity information of the user through a camera, or identify the identity information input by the user; The identity information, and obtain the user information.
  • the status information includes at least one of the following: environmental information, time information, or geographic location information, and the environmental information includes environmental information in the vehicle and/or environmental information outside the vehicle.
  • the transceiver module when determining the seat parameters corresponding to the user based on the user information and the status information, is configured to send the user information and the user information to the cloud server. Status information; receiving the seat parameters corresponding to the user sent by the cloud server; or, the processing module is configured to obtain N pieces of historical data according to the user information and the status information, where N is greater than An integer of 0; the seat parameter corresponding to the user is determined according to the N pieces of historical data.
  • the acquiring N pieces of historical data according to the user information and the status information includes: the transceiver module, configured to send the user information and the user information to the cloud server Status information; receiving the N pieces of historical data sent by the cloud server.
  • the processing module when obtaining N pieces of historical data according to the user information and the status information, is specifically configured to obtain information belonging to different categories from the database according to the user information.
  • Historical data where the historical data includes historical status information, and the category is determined according to the similarity of the historical status information; according to the status information, the N pieces of history belonging to the same category are determined from the historical data data.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processing module is specifically configured to obtain M pieces of historical data from the N pieces of historical data according to preset conditions.
  • the preset conditions include one of the following: the highest score, the score is higher than a threshold, or the score goes from high to high.
  • the M is an integer greater than 0 and less than the N; the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • each of the N pieces of historical data further includes historical state information
  • the historical state information includes historical time information.
  • the processing module is specifically configured to determine according to the difference between the historical time information corresponding to each of the N pieces of historical data and the time information
  • the N weights corresponding to the N pieces of historical data where the smaller the difference, the greater the weight; according to the N weights and the N pieces of historical scores corresponding to the N pieces of historical data, N pieces of historical data are determined
  • the score coefficient any one of the N score coefficients A is determined according to the weight corresponding to the score coefficient A and the historical score corresponding to the score coefficient A; the N score coefficients are updated to the N pieces of historical scores, and the N pieces of scoring coefficients correspond to the N pieces of historical scores in a one-to-one correspondence.
  • a seat adjustment system in a third aspect, includes a processor, a memory, and a seat adjustment device, wherein the processor is configured to obtain user information and status information corresponding to the user from the memory; The seat parameter corresponding to the user is determined according to the user information and the state information; the seat adjustment device is configured to adjust the seat according to the seat parameter corresponding to the user.
  • the system further includes an identity recognition device.
  • the identity recognition device When obtaining user information and status information corresponding to the user from the memory, the identity recognition device is used to identify the user through a camera. Identity information, or identifying the identity information input by the user; the processor is configured to obtain the user information according to the identity information.
  • the status information includes at least one of the following: environmental information, time information, or geographic location information, and the environmental information includes environmental information in the vehicle and/or environmental information outside the vehicle.
  • the system further includes a communication device, and when determining the seat parameter corresponding to the user according to the user information and the status information,
  • the processor is configured to send the user information and the status information to a cloud server through the communication device; receive the seat parameters corresponding to the user sent by the cloud server through the communication device; or,
  • the processor is configured to obtain N pieces of historical data from the memory according to the user information and the status information, where N is an integer greater than 0; and determine the user according to the N pieces of historical data The corresponding seat parameters.
  • the processor is configured to send the user information and the status information to the cloud server through the communication device; and receive the N pieces of historical data sent by the cloud server.
  • the processor is configured to obtain historical data belonging to different categories from the memory according to the user information, the historical data including historical state information, and the category is determined according to the similarity of the historical state information ; According to the state information, the N pieces of historical data belonging to the same category are determined from the historical data.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processor is configured to obtain M pieces of historical data from the N pieces of historical data according to preset conditions, and the preset conditions include one of the following: the highest score, the score is higher than a threshold, or the score goes from high to low
  • the M is an integer greater than 0 and less than the N; the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • each of the N pieces of historical data further includes historical state information
  • the historical state information includes historical time information.
  • the processor is further configured to determine the N weights corresponding to the N pieces of historical data according to the difference between the historical time information corresponding to each piece of the N pieces of historical data and the time information, Wherein, the smaller the difference, the greater the weight; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined, any of the N scoring coefficients A scoring coefficient A is determined according to the weight corresponding to the scoring coefficient A and the historical score corresponding to the scoring coefficient A; the N scoring coefficients are updated to the N historical scores, and the N scoring coefficients are equal to The N historical scores correspond one-to-one.
  • a seat adjustment system in a fourth aspect, includes a car, the car includes a processor, a memory, a communication device, and a seat adjustment device, wherein:
  • the processor is configured to obtain user information and status information corresponding to the user from the memory; determine the seat parameters corresponding to the user according to the user information and the status information;
  • the seat adjusting device is used to adjust the seat according to the seat parameters corresponding to the user.
  • the vehicle further includes an identity recognition device, and when obtaining user information and status information corresponding to the user from the memory,
  • the identity recognition device is used for recognizing the identity information of the user through a camera, or recognizing the identity information input by the user;
  • the processor is configured to obtain the user information according to the identity information.
  • the status information includes at least one of the following: environmental information, time information, or geographic location information, and the environmental information includes environmental information in the vehicle and/or environmental information outside the vehicle.
  • the system further includes a cloud server, and the vehicle further includes a communication device.
  • the processor is configured to send the user information and the status information to a cloud server through the communication device; the cloud server is configured to determine the user's corresponding information according to the user information and the status information Seat parameters; send the seat parameters corresponding to the user to the communication device; or,
  • the processor is configured to obtain N pieces of historical data from the memory according to the user information and the status information, where N is an integer greater than 0; and determine the user according to the N pieces of historical data The corresponding seat parameters.
  • the cloud server is configured to receive the user information and the status information sent by the communication device;
  • the processor is configured to receive the N pieces of historical data sent by the cloud server through the communication device.
  • the processor is configured to obtain historical data belonging to different categories from the memory according to the user information, the historical data including historical state information, and the category is determined according to the similarity of the historical state information ; According to the state information, the N pieces of historical data belonging to the same category are determined from the historical data.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processor is configured to obtain M pieces of historical data from the N pieces of historical data according to preset conditions, and the preset conditions include one of the following: the highest score, the score is higher than a threshold, or the score goes from high to low
  • the M is an integer greater than 0 and less than the N; the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • each of the N pieces of historical data further includes historical state information
  • the historical state information includes historical time information.
  • the processor is further configured to determine the N weights corresponding to the N pieces of historical data according to the difference between the historical time information corresponding to each piece of the N pieces of historical data and the time information, Wherein, the smaller the difference, the greater the weight; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined, any of the N scoring coefficients A scoring coefficient A is determined according to the weight corresponding to the scoring coefficient A and the historical score corresponding to the scoring coefficient A; the N scoring coefficients are updated to the N historical scores, and the N scoring coefficients are equal to The N historical scores correspond one-to-one.
  • an electronic device including a processor and a memory, the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, So that the device executes the method according to the first aspect or any one of the first aspect.
  • an in-vehicle device including the electronic device as described in the fifth aspect.
  • a computer-readable storage medium is provided, and a computer program is stored in the computer-readable storage medium.
  • the computer program is executed, the computer program described in the first aspect or any one of the first aspect method.
  • a computer program product including computer instructions, which when the computer instructions run on the electronic device as described in the fifth aspect, cause the electronic device to execute any one of the first aspect or the first aspect. The method described in the item.
  • FIG. 1 is a schematic structural diagram of a seat adjustment system provided by an embodiment of the application
  • Figure 2 is a schematic diagram of a seat provided by an embodiment of the application.
  • FIG. 3 is a schematic flowchart of a seat adjustment method provided by an embodiment of the application.
  • FIG. 4 is a schematic structural diagram of a seat adjusting device provided by an embodiment of the application.
  • FIG. 5 is a schematic structural diagram of an electronic device provided by an embodiment of the application.
  • FIG. 1 is a schematic structural diagram of a seat adjustment system provided by an embodiment of the application.
  • the seat adjustment system 10 includes an in-vehicle device 11, a seat adjustment device 12 and a seat parameter acquisition device 13.
  • the in-vehicle equipment 11 includes an electronic device 110, a user information management module 111, a state information management module 112, an evaluation module 113, and a learning module 114.
  • the electronic device 110 can communicate with the user information management module 111, the status information management module 112, the evaluation module 113, and the learning module 114, and the learning module 114 can communicate with the user information management module 111, the status information management module 112, and the evaluation module 113.
  • the electronic device 110 may be a chip, for example.
  • the user information management module 111 is used to process user information.
  • the user information of the user is identified and verified, and the user information is transmitted to the electronic device 110 or the learning module 114 after the verification is successful.
  • biometric information such as fingerprints, palm prints, iris, etc. can be used to identify and verify the user information of the user, or the car key, login interface, etc. can be used to identify and verify the user information of the user.
  • the identification and verification of information is not restricted in this application.
  • the components or modules involved in the identification and verification of user information are not limited in this application. For example, when using the iris to complete the identification and verification of the user's user information, a camera may be required; when using the fingerprint to complete the identification and verification of the user's user information, a corresponding sensor may be required.
  • the status information management module 112 is used to process status information. For example, when the user enters the first state or is in the first state, the state information is acquired and the state information is transmitted to the electronic device 110 or the learning module 114.
  • the first state may be, for example, a resting state, a driving state, or the like.
  • methods such as interface interaction or voice can be used to detect that the user enters the first state or the user exits the first state, such as an instruction for the user to enter the first state or an instruction for the user to exit the first state, which is not limited in this application.
  • the status information management module 112 can communicate with at least one sensor, so that status information can be acquired.
  • the status information includes environmental information. When the environmental information is the temperature information in the vehicle, the state information management module 112 may obtain the temperature information in the vehicle from the temperature sensor.
  • the evaluation module 113 includes a first evaluation sub-module 1131 and a second evaluation sub-module 1132.
  • the first evaluation submodule 1131 is configured to score based on the evaluation parameters obtained when the user is in the first state to obtain the first score.
  • the evaluation parameters may include, for example, duration, number of posture changes, and physiological parameters.
  • the duration is the length of time the user uses the seat when the seat parameter is the first seat parameter, and the number of posture changes is the user’s posture change during the duration.
  • the physiological parameter is the physiological parameter when the seat parameter of the user using the seat is the first seat parameter. It is understandable that the physiological parameters may include, for example, heartbeat statistics, heart rate variability, respiration statistics, body temperature statistics, and the number of blinks.
  • the components or modules involved in obtaining the evaluation parameters are not limited in this application.
  • the duration can be obtained by a timer
  • the number of posture changes can be calculated by the acceleration sensor of the wearable device, or the number of posture changes can be obtained by visual signal analysis
  • the heart rate statistics or heart rate can be obtained by the heart rate sensor of the wearable device.
  • Denaturation also obtains heartbeat statistics through visual signals, respiration statistics through sound sensors, respiration statistics, blinks, etc. through visual signal analysis, and body temperature statistics through wearable devices.
  • the second evaluation submodule 1132 is used to obtain the second score when the user exits the first state.
  • the second score can be obtained through interface interaction, the second score can also be obtained by voice inquiry, or the second score can be obtained by sending a message to a mobile phone.
  • the specific method for obtaining the second score is not limited in this application.
  • the evaluation module 113 obtains the first score and the second score
  • the first score and the second score may be used as the score corresponding to the user, or the average value of the first score and the second score may be used as the score corresponding to the user.
  • the highest score among the first score and the second score can be used as the score corresponding to the user.
  • the weighted score can be used as the corresponding score for the user. Scoring, there is no restriction here.
  • the score is transmitted to the electronic device 110 or the learning module 114. It should be noted that if the user does not feedback the second score, the second evaluation sub-module 1132 may determine the second score as an invalid score. That is, when the evaluation module 113 obtains the first score, the first score can be used as the score corresponding to the user, and the score is transmitted to the electronic device 110 or the learning module 114.
  • the learning module 114 is used to process user information, status information, and scoring. Specifically, the learning module 114 may use user information, status information, and scores for model training. For example, user information, status information, and scores can be used to implement clustering model training. At the end of the model training, the trained clustering model can also be used to obtain historical seat parameters based on user information and status information.
  • the seat adjusting device 12 is used to adjust the seat according to the seat parameters transmitted by the in-vehicle equipment 11 or the electronic device 110.
  • the seat parameter acquisition device 13 is used to feed back the changed seat parameters when the user detects a change in the seat parameters when the user is in the first state. It can be understood that the seat parameter acquisition device may be a variety of sensors.
  • FIG. 2 is a schematic diagram of a seat provided by an embodiment of the application.
  • the seat is mainly related to the angle of the seat back, the height of the seat, and the front and rear position of the seat. Of course, it can also be related to the seat temperature.
  • the specific parameters of the seat that can be adjusted are not limited in this application.
  • the parameters of the seat are often adjusted to preset parameters, so as to avoid the user from manually adjusting the seat and realize the liberation of the user's hands.
  • the preset parameters are fixed parameters set by the manufacturer in advance. For example, manufacturers can set a fixed seat back angle in advance, and can also set a fixed seat height in advance. Therefore, this seat adjustment method is relatively rigid, not flexible enough, and cannot meet the needs of differentiated users.
  • the present application provides a seat adjustment method to solve the above-mentioned technical problems.
  • the following describes the embodiments of the present application in detail.
  • the seat adjustment method provided by the embodiment of the present application may be applied to an in-vehicle device, and the in-vehicle device may be an electronic device or a device including the electronic device.
  • the in-vehicle device may be an electronic device or a device including the electronic device.
  • FIG. 3 is a schematic flowchart of a seat adjustment method according to an embodiment of the application. As shown in Figure 3, the method includes:
  • the electronic device acquires user information and status information corresponding to the user.
  • the electronic device may receive an instruction from the user to enter the first state.
  • the electronic device may obtain user information corresponding to the user through the user information management module. Specifically, the electronic device can recognize the user's identity information through a camera, or recognize the identity information input by the user; then, the electronic device can obtain user information based on the identity information.
  • the identity information of the user is recognized through the camera, and the identity information may be, for example, an image including the user or a video including the user. For example, the user's face image, the user's iris image, and so on. Identify the identity information entered by the user, the identity information may be, for example, a login account and a login password.
  • the electronic device can also obtain state information corresponding to the user through the state information management module.
  • the status information includes at least one of the following: environmental information, time information, or geographic location information, and the environmental information includes environmental information in the vehicle and/or environmental information outside the vehicle.
  • the in-vehicle environment information may include the number of people in the vehicle, the location where each person sits, the in-vehicle decibel information, and the in-vehicle temperature information.
  • the outside-in-vehicle environment information may include, for example, outside temperature information and outside brightness information.
  • the time information may be, for example, time stamp information at the current time, season label information, time label information, and the like.
  • the season label information may include four labels of "spring", “summer”, “autumn”, and "winter” and the time label information may include four labels of "morning", "afternoon", “evening", and "early morning”.
  • the time label information may also include two labels of "working day” and "weekend".
  • the geographic location information may include, for example, indoor parking lots, outdoor parking lots, homes, companies, service areas, outdoor parks, mountainous areas, and so on.
  • the electronic device may also obtain user information corresponding to the user through the user information management module, or obtain state information corresponding to the user through the state information management module. Since the electronic device receives the user's instruction to enter the state for the first time, it indicates that there is no historical data corresponding to the user. Therefore, the electronic device cannot obtain historical data based on user information and status information. At this time, the electronic device can obtain the preset seat parameters and adjust the seat according to the preset seat parameters, that is, the electronic device adjusts the seat according to the preset seat parameters through the seat adjustment device.
  • the preset seat parameters may include, for example, the seat back angle, the seat height, the front and rear position of the seat, and the seat temperature.
  • the seat back angle is R 0 degrees
  • the seat height is H 0 cm from the origin
  • the front and rear position of the seat is L 0 cm from the origin
  • the seat temperature is T 0 degrees Celsius.
  • the electronic device determines the seat parameter corresponding to the user according to the user information and the status information.
  • the electronic device may send the user information and status information to the cloud server, and when the cloud server receives the user information and In the case of status information, the cloud server determines the seat parameters corresponding to the user based on the user information and the status information, so that the seat parameters corresponding to the user can be sent to the electronic device.
  • the seat parameters corresponding to the user may include, for example, the seat back angle, the seat height, the front and rear position of the seat, and the seat temperature.
  • the electronic device may also obtain N pieces of historical data based on the user information and status information, so as to determine the seat parameters corresponding to the user based on the N pieces of historical data.
  • N is an integer greater than 0, and N can be, for example, 1, 2, 3, 4, 5, 6, 10, 12 and the like.
  • each piece of historical data in the N pieces of historical data also includes historical status information, historical scores, and historical seat parameters.
  • the historical state information includes at least one of the following: historical environment information, historical time information, or historical geographic location information.
  • the historical environment information includes historical environmental information inside the vehicle and/or historical environmental information outside the vehicle.
  • the historical status information please refer to the status information involved in step 301 in FIG. 3, which will not be repeated here.
  • each piece of historical data in the N pieces of historical data is data associated with a historical sample point.
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • the electronic device may send the user information and status information to the cloud server.
  • the cloud server receives user information and status information
  • the cloud server can obtain N pieces of historical data according to the user information and status information, so that the N pieces of historical data can be sent to the electronic device.
  • the cloud server can determine the historical data based on the user information and the status information to prepare for the subsequent determination of the seat parameters based on the historical data.
  • the electronic device can obtain historical data belonging to different categories from the database according to the user information.
  • the historical data includes historical status information, and the category is based on the historical status. The similarity of the information is determined. Further, the electronic device can also determine N pieces of historical data belonging to the same category from the historical data according to the state information.
  • the electronic device can obtain the user's corresponding information through the user information management module.
  • the status information corresponding to the user can also be obtained through the status information management module.
  • the electronic device can obtain the score K1 through the evaluation module.
  • the score K1 may be the sum of the first score K1 and the second score K1, or the average value of the first score K1 and the second score K1, or the first score K1.
  • the score with the highest score among the score K1 and the second score K1 may also be a score obtained by weighting the first score K1 and the second score K1 according to a preset weighting formula, which is not limited here.
  • the score K1 is the first score K1.
  • the first score K1 is determined according to the evaluation parameter L1
  • the evaluation parameter L1 includes the duration L1, the number of posture changes L1, and the physiological parameter L1.
  • the duration L1 is the length of time the user uses the seat when the seat parameter is the seat parameter P1
  • the number of posture changes L1 is the number of times the user changes posture during the duration L1
  • the physiological parameter L1 is the user’s seat using the seat
  • the seat parameter is the physiological parameter when the seat parameter P1.
  • the physiological parameter L1 may be, for example, the heartbeat statistical value, the heart rate variability, the respiratory statistical value, the body temperature statistical value, the number of blinks, etc. when the seat parameter of the user using the seat is the seat parameter P1.
  • the seat parameter P1 may be a preset seat parameter.
  • the duration L1 is the length of time the user uses the seat when the seat parameter is the preset seat parameter
  • the number of posture changes L1 is the number of times the user changes posture during the duration L1
  • the physiological parameter L1 is the user’s use
  • the seat parameters of the seat are physiological parameters when the seat parameters are preset.
  • the electronic device before the electronic device receives the user's instruction to exit the first state each time, if the seat parameter acquisition device detects a change in the seat parameter, the seat parameter acquisition device feeds back the changed seat parameter to the electronic device. Then, before the electronic device receives the user's instruction to exit the first state each time, whenever the seat parameter acquisition device detects a change in the seat parameter, the electronic device obtains the first score before the seat parameter change through the evaluation module And the first score after the seat parameter changes, and the electronic device will obtain the changed seat parameters through the seat parameter acquisition device. That is, the electronic device acquires at least one seat parameter and at least one first score, and the at least one seat parameter and at least one first score are in a one-to-one correspondence.
  • the evaluation parameter L2 includes the duration L2, the number of posture changes L2, and the physiological parameter L2.
  • the duration L2 is the length of time the user uses the seat parameter of the seat as the seat parameter corresponding to the first score K2
  • the number of posture changes L2 is the number of times the user changes posture within the duration L2
  • the physiological parameter L2 is the user
  • the physiological parameter when the seat parameter of the seat in use is the seat parameter corresponding to the first score K2.
  • the physiological parameter L2 may be, for example, the statistical value of heartbeat, the variability of heart rate, the statistical value of breathing, the statistical value of body temperature, the number of blinks, etc.
  • the electronic device may determine the seat parameter corresponding to the first score K3 with the highest score from the at least one seat parameter according to the at least one first score.
  • the electronic device may obtain the second score K2 through the evaluation module. At the same time, the electronic device can determine the score K2 corresponding to the user according to the first score K3 and the second score K2.
  • the score K2 can be the sum of the first score K3 and the second score K2, or the average of the first score K3 and the second score K2, or the highest score of the first score K3 and the second score K2.
  • the score of may also be a score obtained by weighting the first score K3 and the second score K2 according to a preset weighting formula, which is not limited here. If the user does not feedback the second score K2, then the score K2 corresponding to the user is the first score K3.
  • the electronic device can also use the user information, status information, score, and seat parameters acquired each time as information associated with a sample point.
  • the electronic device may use user information, status information, score K1, and seat parameter P1 as information associated with a sample point.
  • the electronic device may also use user information, status information, score K2, and seat parameters corresponding to the first score K3 as information associated with a sample point.
  • the electronic device can also use a clustering model to cluster the information associated with the sample points through the learning module, so as to use the similarity between the state information to determine the category to which the sample points belong.
  • the similarity between at least one type of information included in the state information can be used to determine which sample point belongs to. category.
  • the similarity between the environmental information can be used to determine the category to which the sample point belongs.
  • the similarity between the environmental information and the time information can be used. The similarity between the two determines the category to which the sample point belongs.
  • the electronic device obtains historical data belonging to different categories from the database according to the user information, the electronic device has completed the clustering. Therefore, the electronic device can locally acquire N pieces of historical data according to user information and status information.
  • the electronic device adjusts the seat according to the seat parameter corresponding to the user.
  • the electronic device can adjust the seat according to the seat parameter corresponding to the user through the seat adjustment device.
  • the user’s corresponding user information and status information are used to configure the corresponding seat parameters for the user, which meets the needs of differentiated users, avoids adjusting the seat according to the fixed parameters set by the manufacturer in advance, and also It provides users with more flexible seat adjustment methods and better improves user experience.
  • the electronic device determines the seat parameters corresponding to the user according to the N pieces of historical data, including: the electronic device obtains M pieces of historical data from the N pieces of historical data according to preset conditions, The preset conditions include one of the following: the highest score, the score is higher than the threshold, or the order of the score from high to low, M is an integer greater than 0 and less than N; the electronic device corresponds to M historical seat parameters according to M historical data , To determine the seat parameters corresponding to the user.
  • M can be, for example, 1, 2, 3, 4, 5, 6, 10, 12 and other numerical values.
  • the electronic device obtains M pieces of historical data from N pieces of historical data according to preset conditions. That is, the electronic device can obtain M pieces of historical data with the highest score from the N pieces of historical data, and the electronic device can also obtain M pieces of historical data with a score higher than the threshold from the N pieces of historical data. In the low order, the first M pieces of historical data are obtained from the N pieces of historical data.
  • the seat parameter corresponding to the user is the seat parameter corresponding to the highest-rated historical data; when M is an integer greater than 1, the seat parameter corresponding to the user can be the average value of M historical seat parameters , It can also be the median of M historical seat parameters, which is not limited in this application.
  • the M pieces of historical seat parameters include historical seat parameters A, historical seat parameters B, and historical seat parameters C.
  • Historical seat parameters A include seat back angle A, seat height A, seat front and rear position A, and seat temperature A
  • historical seat parameters B include seat back angle B, seat height B, seat front and rear position B And seat temperature B
  • historical seat parameters C include seat back angle C, seat height C, seat front and rear position C and seat temperature C.
  • the seat parameters corresponding to the user include the seat back angle corresponding to the user, the seat height corresponding to the user, the front and rear position of the seat corresponding to the user, and the seat temperature corresponding to the user.
  • the seat back angle corresponding to the user can be the average value of the seat back angle A, the seat back angle B and the seat back angle C, or the seat back angle A, the seat back angle B and the seat The median of the backrest angle C;
  • the user's corresponding seat height can be the average value of the seat height A, the seat height B, and the seat height C, or the seat height A, the seat height B, and the seat height C
  • the user’s corresponding seat front and rear position can be the average value of the seat front and rear position A, the seat front and rear position B, and the seat front and rear position C, or the seat front and rear position A, the seat front and rear position B and the seat
  • the seat temperature corresponding to the user can be the average value of the seat temperature A, the seat temperature B and the seat temperature C, or the seat temperature A, the seat temperature B, and the seat temperature The median of C.
  • the user's corresponding seat parameters can be determined based on the score, so that the user's needs can be better controlled, and the user's needs can also be provided with seat parameters that meet their needs.
  • the method further includes: the electronic device according to the historical time information corresponding to each piece of historical data in the N pieces of historical data and The difference between the time information determines the N weights corresponding to the N pieces of historical data, where the smaller the difference, the greater the weight; the electronic device is based on the N weights and the N pieces of historical data corresponding to the N historical scores, Determine N scoring coefficients, any one of the N scoring coefficients A is determined according to the weight corresponding to the scoring coefficient A and the historical score corresponding to the scoring coefficient A; the electronic device updates the N scoring coefficients to N historical scores, N scoring coefficients correspond one-to-one with N historical scorings.
  • the electronic device can update the scoring coefficient A to the historical score corresponding to the scoring coefficient A.
  • the N pieces of historical data include historical data 1, historical data 2, and historical data 3.
  • the historical time information corresponding to historical data 1 is 10:30 on April 12, 2020
  • the historical time information corresponding to historical data 2 is 14:30 on April 13, 2020
  • the historical time information 1 corresponding to historical data 3 is 2020. 16:30 on April 14th.
  • the time information is 9:30 on April 15, 2020.
  • the seat adjusting device 400 includes a transceiver module 401 and a processing module 402. Among them, the transceiver module 401 is used to obtain user information and status information corresponding to the user; the processing module 402 is used to determine the seat parameters corresponding to the user according to the user information and status information; the processing module 402 is also used to determine the seat parameters corresponding to the user. Seat parameters adjust the seat.
  • the status information can refer to the status information involved in step 301 in FIG. 3, which will not be repeated here.
  • the seat parameters corresponding to the user may refer to the seat parameters corresponding to the user involved in step 303 in FIG. 3, which will not be repeated here.
  • the user’s corresponding user information and status information are used to configure the corresponding seat parameters for the user, which meets the needs of differentiated users, avoids adjusting the seat according to the fixed parameters set by the manufacturer in advance, and also It provides users with more flexible seat adjustment methods and better improves user experience.
  • the processing module 402 when obtaining user information corresponding to the user, is configured to identify the user's identity information through a camera, or identify the identity information input by the user; and obtain the user information according to the identity information.
  • identity information For the identity information, reference may be made to the identity information involved in step 301 in FIG. 3, which will not be repeated here.
  • the transceiver module 401 when determining the seat parameters corresponding to the user according to the user information and status information, is used to send the user information and status information to the cloud server; receive the user corresponding information sent by the cloud server Seat parameters; or, the processing module 402 is configured to obtain N pieces of historical data according to user information and status information, where N is an integer greater than 0; and determine the seat parameters corresponding to the user according to the N pieces of historical data.
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • obtaining N pieces of historical data according to user information and status information includes: a transceiver module 401, configured to send user information and status information to a cloud server; and receive N pieces of historical data sent by the cloud server.
  • the cloud server can determine the historical data based on the user information and the status information to prepare for the subsequent determination of the seat parameters based on the historical data.
  • the processing module 402 when obtaining N pieces of historical data according to user information and status information, is specifically configured to obtain historical data belonging to different categories from the database according to the user information,
  • the historical data includes historical state information, and the category is determined based on the similarity of the historical state information; according to the state information, N pieces of historical data belonging to the same category are determined from the historical data.
  • the historical state information can refer to the historical state information involved in step 302 in FIG. 3, which will not be repeated here.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processing module 402 specifically uses According to a preset condition, M pieces of historical data are obtained from N pieces of historical data.
  • the preset condition includes one of the following: the highest score, the score is higher than the threshold, or the order of the score from high to low, the M is greater than 0 and An integer less than N; determine the seat parameter corresponding to the user according to the M historical seat parameters corresponding to the M historical data.
  • the user's corresponding seat parameters can be determined based on the score, so that the user's needs can be better controlled, and the user's needs can also be provided with seat parameters that meet their needs.
  • each piece of historical data in the N pieces of historical data further includes historical state information
  • the historical state information includes historical time information, which is obtained from the N pieces of historical data according to preset conditions
  • the processing module 402 is specifically configured to determine the N weights corresponding to the N pieces of historical data according to the difference between the historical time information and the time information corresponding to each piece of the N pieces of historical data, where , The smaller the difference, the greater the weight; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined, and any one of the N scoring coefficients A is corresponding to the scoring coefficient A The weight and the historical score corresponding to the scoring coefficient A are determined; the N scoring coefficients are updated to N historical scores, and the N scoring coefficients correspond to the N historical scores one-to-one.
  • An embodiment of the present application provides a seat adjustment system, which includes a processor, a memory, and a seat adjustment device, wherein the processor is used to obtain user information and status information corresponding to the user from the memory; according to the user information and The status information determines the seat parameters corresponding to the user; the seat adjustment device is used to adjust the seat according to the seat parameters corresponding to the user.
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • the system further includes an identity recognition device.
  • the identity recognition device When obtaining user information and status information corresponding to the user from the memory, the identity recognition device is used to identify the user's identity information through the camera, or to identify the user Input identity information; the processor is used to obtain user information based on the identity information.
  • identity information For the identity information, reference may be made to the identity information involved in step 301 in FIG. 3, which will not be repeated here.
  • the system further includes a communication device.
  • the processor is configured to send user information and status information to the cloud server through the communication device; receive the seat parameters corresponding to the user sent by the cloud server through the communication device; or,
  • the processor is configured to obtain N pieces of historical data from the memory according to user information and status information, where N is an integer greater than 0; and determine the seat parameters corresponding to the user according to the N pieces of historical data.
  • the communication device may be, for example, an in-vehicle tbox (telematicsbox).
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • the processor is used for sending user information and status information to the cloud server through the communication device; receiving N pieces of historical data sent by the cloud server.
  • the cloud server can determine the historical data based on the user information and the status information to prepare for the subsequent determination of the seat parameters based on the historical data.
  • the processor is used to obtain historical data belonging to different categories from the memory according to user information.
  • the historical data includes historical state information.
  • the category is determined based on the similarity of the historical state information; according to the state information, it is determined from the historical data that they belong to the same N pieces of historical data of the category.
  • the historical state information can refer to the historical state information involved in step 302 in FIG. 3, which will not be repeated here.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processor is used to obtain M pieces of historical data from N pieces of historical data according to preset conditions.
  • the preset conditions include one of the following: the highest score, the score is higher than the threshold, or the order of the score from high to low, where M is greater than An integer that is 0 and less than N; the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • the user's corresponding seat parameters can be determined based on the score, so that the user's needs can be better controlled, and the user's needs can also be provided with seat parameters that meet their needs.
  • each piece of historical data in the N pieces of historical data further includes historical state information, and the historical state information includes historical time information. According to a preset condition, M pieces of historical data are obtained from the N pieces of historical data.
  • the processor is also used to determine the N weights corresponding to the N pieces of historical data according to the difference between the historical time information and the time information corresponding to each piece of the N pieces of historical data, where the smaller the difference, the weight The larger is; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined. Any one of the N scoring coefficients A is based on the weight corresponding to the scoring coefficient A and the scoring coefficient A. The historical score is determined; the N score coefficients are updated to N historical scores, and the N score coefficients correspond to the N historical scores one-to-one.
  • An embodiment of the present application also provides a seat adjustment system.
  • the system includes a vehicle.
  • the vehicle includes a processor, a memory, a communication device, and a seat adjustment device.
  • the processor is used to obtain user information and status information corresponding to the user from the memory; determine the seat parameters corresponding to the user according to the user information and status information;
  • the seat adjustment device is used to adjust the seat according to the user's corresponding seat parameters.
  • the status information can refer to the status information involved in step 301 in FIG. 3, which will not be repeated here.
  • the seat parameters corresponding to the user can refer to the seat parameters corresponding to the user involved in step 303 in FIG. 3, which will not be repeated here.
  • the communication device may be, for example, an in-vehicle tbox (telematicsbox).
  • the user’s corresponding user information and status information are used to configure the corresponding seat parameters for the user, which meets the needs of differentiated users, avoids adjusting the seat according to the fixed parameters set by the manufacturer in advance, and also It provides users with more flexible seat adjustment methods and better improves user experience.
  • the vehicle further includes an identity recognition device.
  • an identity recognition device When obtaining user information and status information corresponding to the user from the memory,
  • the identity recognition device is used to recognize the user's identity information through the camera, or to recognize the identity information entered by the user;
  • the processor is used to obtain user information according to the identity information.
  • identity information For the identity information, reference may be made to the identity information involved in step 301 in FIG. 3, which will not be repeated here.
  • the system further includes a cloud server, and the car also includes a communication device.
  • the processor is used to send user information and status information to the cloud server through the communication device; the cloud server is used to determine the seat parameters corresponding to the user according to the user information and status information; send the seat parameters corresponding to the user to the communication device; or ,
  • the processor is configured to obtain N pieces of historical data from the memory according to user information and status information, where N is an integer greater than 0; and determine the seat parameters corresponding to the user according to the N pieces of historical data.
  • the cloud server can determine the seat parameters based on the user information and status information, and it can also determine the historical data based on the user information and status information, thereby determining the seat parameters based on the historical data.
  • the cloud server is used to receive user information and status information sent by the communication device;
  • the processor is configured to receive N pieces of historical data sent by the cloud server through the communication device.
  • the cloud server can determine the historical data based on the user information and the status information to prepare for the subsequent determination of the seat parameters based on the historical data.
  • the processor is used to obtain historical data belonging to different categories from the memory according to user information.
  • the historical data includes historical state information.
  • the category is determined based on the similarity of the historical state information; according to the state information, it is determined from the historical data that they belong to the same N pieces of historical data of the category.
  • the historical state information can refer to the historical state information involved in step 302 in FIG. 3, which will not be repeated here.
  • each piece of historical data in the N pieces of historical data includes historical scores and historical seat parameters.
  • the processor is used to obtain M pieces of historical data from N pieces of historical data according to preset conditions.
  • the preset conditions include one of the following: the highest score, the score is higher than the threshold, or the order of the score from high to low, where M is greater than An integer that is 0 and less than N; the seat parameter corresponding to the user is determined according to the M historical seat parameters corresponding to the M historical data.
  • the user's corresponding seat parameters can be determined based on the score, so that the user's needs can be better controlled, and the user's needs can also be provided with seat parameters that meet their needs.
  • each piece of historical data in the N pieces of historical data further includes historical state information, and the historical state information includes historical time information. According to a preset condition, M pieces of historical data are obtained from the N pieces of historical data.
  • the processor is also used to determine the N weights corresponding to the N pieces of historical data according to the difference between the historical time information and the time information corresponding to each piece of the N pieces of historical data, where the smaller the difference, the weight The larger is; according to the N weights and the N historical scores corresponding to the N historical data, N scoring coefficients are determined. Any one of the N scoring coefficients A is based on the weight corresponding to the scoring coefficient A and the scoring coefficient A. The historical score is determined; the N score coefficients are updated to N historical scores, and the N score coefficients correspond to the N historical scores one-to-one.
  • FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the application.
  • the electronic device 500 includes a memory 501, a processor 502, and a transceiver 503. They are connected by a bus 504 between them.
  • the memory 501 is used to store related instructions and data, and can transmit the stored data to the processor 502.
  • the memory 501 may include a volatile memory (volatile memory), such as random-access memory (RAM); the memory may also include a non-volatile memory (non-volatile memory), such as flash memory ( flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory may also include a combination of the above types of memory.
  • volatile memory such as random-access memory (RAM)
  • non-volatile memory such as flash memory ( flash memory, hard disk drive (HDD) or solid-state drive (SSD)
  • SSD solid-state drive
  • the memory may also include a combination of the above types of memory.
  • the processor 502 may be a central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof.
  • the above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.
  • the memory 501 may be a physically independent unit, or may be integrated with the processor 502.
  • processor 502 may execute related instructions stored in the memory 501 to execute the method involved in the embodiment in FIG. 3.
  • the embodiment of the present application also provides an in-vehicle device, and the in-vehicle device includes the electronic device involved in the embodiment in FIG. 4.
  • the embodiment of the present application also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed, any one of the methods involved in the embodiment of FIG. 3 is implemented.
  • the embodiment of the present application also provides a computer program product, including computer instructions, when the computer instructions run on the electronic device involved in the embodiment of FIG. 4, the electronic device is caused to execute any method involved in the embodiment of FIG. 3 .
  • the units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the above integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
  • the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium. It includes a number of instructions to enable a computer device (which may be a personal computer, a cloud server, or a network device, etc.) to execute all or part of the steps of the above methods of the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes. .
  • U disk mobile hard disk
  • read-only memory ROM, Read-Only Memory
  • RAM random access memory
  • magnetic disks or optical disks and other media that can store program codes.

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Abstract

一种座椅调节方法、装置及***，该方法包括：获取用户对应的用户信息和状态信息；根据用户信息和状态信息，确定用户对应的座椅参数；按照用户对应的座椅参数调节座椅。该座椅调节方法能满足差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。

Description

一种座椅调节方法、装置及*** 技术领域
本申请涉及汽车技术领域，尤其涉及一种座椅调节方法、装置及***。
背景技术
随着汽车的快速普及，汽车产业的竞争也越来越激烈。为了增加汽车的销量，提高用户在使用车辆的各项体验成为关键。
目前，为了提高用户在使用座椅时的舒适性体验，往往会将座椅的参数调节到预先设置好的参数，以此来避免用户手动调节座椅，实现解放用户的双手。一般来说，预先设置好的参数都是厂商提前设定的固定参数。因此，这种座椅调节方式比较死板，不够灵活，也无法满足差异化的用户需求。
发明内容
本申请实施例提供了一种座椅调节方法、装置及***，能满足差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。
第一方面，提供了一种座椅调节方法，包括：获取用户对应的用户信息和状态信息；根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；按照所述用户对应的座椅参数调节座椅。
可以看出，上述技术方案中，通过利用用户对应的用户信息和状态信息为用户配置对应的座椅参数，满足了差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。
可选的，在一种可能的实施方式中，所述获取用户对应的用户信息，包括：通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；根据所述身份信息，获取所述用户信息。
可以看出，上述技术方案中，实现了用户信息的获取。
可选的，在一种可能的实施方式中，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
可以看出，上述技术方案中，结合状态信息，实现了更加精准的把控用户需求，从而能够更好的为用户提供满足其需求的座椅参数。
可选的，在一种可能的实施方式中，所述根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数，包括：向云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述用户对应的座椅参数；或，根据所述用户信息和所述状态信息，获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
可选的，在一种可能的实施方式中，所述根据所述用户信息和所述状态信息，获取N条历史数据，包括：向所述云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述N条历史数据。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定历史数据，为后续基于历史数据确定座椅参数做准备。
可选的，在一种可能的实施方式中，所述根据所述用户信息和所述状态信息，获取N条历史数据，包括：根据所述用户信息，从数据库中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
可以看出，上述技术方案中，实现了基于用户信息获取属于不同类别的历史数据。同时，由于类别是根据历史数据包括的历史状态信息的相似度确定的，从而实现基于用户的状态信息从该用户对应的历史数据中确定出属于同一类别的N条历史数据，即实现了基于用户的状态信息确定了用户在相似历史状态所对应的历史数据。
可选的，在一种可能的实施方式中，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，所述根据所述N条历史数据，确定所述用户对应的座椅参数，包括：根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
可以看出，上述技术方案中，实现了基于评分确定用户对应的座椅参数，从而可以更好的把控用户需求，也可以为用户提供满足其需求的座椅参数。
可选的，在一种可能的实施方式中，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，所述方法还包括：
根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
可以看出，上述技术方案中，通过利用历史时间信息与时间信息之间的差值为每条历史评分分配不同的权重，并基于权重和历史评分确定不同的评分系数，实现了基于评分系数来选取历史数据。同时，也避免了在较长时间跨度内用户偏好的座椅参数发生变化时推荐的座椅参数无法满足用户需求的情况。
第二方面，提供一种座椅调节装置，包括：收发模块，用于获取用户对应的用户信息和状态信息；处理模块，用于根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；所述处理模块，还用于按照所述用户对应的座椅参数调节座椅。
在一种可能的实施方式中，在获取用户对应的用户信息时，所述处理模块，用于通过 摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；根据所述身份信息，获取所述用户信息。
在一种可能的实施方式中，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数时，所述收发模块，用于向云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述用户对应的座椅参数；或，所述处理模块，用于根据所述用户信息和所述状态信息，获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
在一种可能的实施方式中，所述根据所述用户信息和所述状态信息，获取N条历史数据，包括：所述收发模块，用于向所述云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述N条历史数据。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，获取N条历史数据时，所述处理模块，具体用于根据所述用户信息，从数据库中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据所述N条历史数据，确定所述用户对应的座椅参数时，所述处理模块，具体用于根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，所述处理模块，具体用于根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
第三方面，提供一种座椅调节***，所述***包括处理器、存储器和座椅调节装置，其中，所述处理器，用于从所述存储器中获取用户对应的用户信息和状态信息；根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；所述座椅调节装置，用于按照所述用户对应的座椅参数调节座椅。
在一种可能的实施方式中，所述***还包括身份识别装置，在从所述存储器中获取用户对应的用户信息和状态信息时，所述身份识别装置，用于通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；所述处理器，用于根据所述身份信息， 获取所述用户信息。
在一种可能的实施方式中，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
在一种可能的实施方式中，所述***还包括通信装置，在根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数时，
所述处理器，用于通过所述通信装置向云服务器发送所述用户信息和所述状态信息；通过所述通信装置接收所述云服务器发送的所述用户对应的座椅参数；或，
所述处理器，用于根据所述用户信息和所述状态信息，从所述存储器中获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，获取N条历史数据时，
所述处理器，用于通过所述通信装置向所述云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述N条历史数据。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，获取N条历史数据时，
所述处理器，用于根据所述用户信息，从所述存储器中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据所述N条历史数据，确定所述用户对应的座椅参数时，
所述处理器，用于根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，
所述处理器，还用于根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
第四方面，提供一种座椅调节***，所述***包括车，所述车包括处理器、存储器、通信装置和座椅调节装置，其中，
所述处理器，用于从所述存储器中获取用户对应的用户信息和状态信息；根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；
所述座椅调节装置，用于按照所述用户对应的座椅参数调节座椅。
在一种可能的实施方式中，所述车还包括身份识别装置，在从所述存储器中获取用户对应的用户信息和状态信息时，
所述身份识别装置，用于通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；
所述处理器，用于根据所述身份信息，获取所述用户信息。
在一种可能的实施方式中，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
在一种可能的实施方式中，所述***还包括云服务器，所述车还包括通信装置，在根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数时，
所述处理器，用于通过所述通信装置向云服务器发送所述用户信息和所述状态信息；所述云服务器，用于根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；向所述通信装置发送所述用户对应的座椅参数；或，
所述处理器，用于根据所述用户信息和所述状态信息，从所述存储器中获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，获取N条历史数据时，
所述云服务器，用于接收所述通信装置发送的所述用户信息和所述状态信息；
所述处理器，用于通过所述通信装置接收所述云服务器发送的所述N条历史数据。
在一种可能的实施方式中，在根据所述用户信息和所述状态信息，获取N条历史数据时，
所述处理器，用于根据所述用户信息，从所述存储器中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据所述N条历史数据，确定所述用户对应的座椅参数时，
所述处理器，用于根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
在一种可能的实施方式中，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，
所述处理器，还用于根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史 评分，所述N条评分系数与所述N条历史评分一一对应。
第五方面，提供一种电子装置，包括处理器和存储器，所述处理器与所述存储器相连，所述存储器用于存储计算机程序，所述处理器用于执行所述存储器中存储的计算机程序，以使得所述设备执行如第一方面或第一方面任一项所述的方法。
第六方面，提供一种车载设备，包括如第五方面所述的电子装置。
第七方面，提供一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机程序，当所述计算机程序被运行时，实现如第一方面或第一方面任一项所述的方法。
第八方面，提供一种计算机程序产品，包括计算机指令，当所述计算机指令在如第五方面所述的电子装置上运行时，使得所述电子装置执行如第一方面或第一方面任一项所述的方法。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
其中：
图1为本申请实施例提供的一种座椅调节***的架构示意图；
图2为本申请实施例提供的一种座椅示意图；
图3为本申请实施例提供的一种座椅调节方法的流程示意图；
图4为本申请实施例提供的一种座椅调节装置的结构示意图；
图5为本申请实施例提供的一种电子装置的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述。
首先，参见图1，图1为本申请实施例提供的一种座椅调节***的架构示意图。如图1所示，该座椅调节***10包括车载设备11、座椅调节装置12和座椅参数获取装置13。其中，车载设备11包括电子装置110、用户信息管理模块111、状态信息管理模块112、评价模块113和学习模块114。电子装置110可以与用户信息管理模块111、状态信息管理模块112、评价模块113和学习模块114通信，学习模块114可以与用户信息管理模块111、状态信息管理模块112、评价模块113通信。另外，该电子装置110例如可以是芯片。
其中，用户信息管理模块111用于对用户信息进行处理。比如，识别与验证用户的用户信息，并在验证成功后将用户信息传输至电子装置110或学习模块114。举例来说，可以利用指纹、掌纹、虹膜等生物信息完成识别与验证用户的用户信息，也可以利用车钥匙、 登录界面等方式完成识别与验证用户的用户信息，具体以哪种方式实现用户信息的识别与验证在本申请中不做限制。同理，在实现用户信息的识别与验证时所涉及的部件或模块等在本申请中也不做限制。比如，利用虹膜完成识别与验证用户的用户信息时，可能需要摄像头；利用指纹完成识别与验证用户的用户信息时，可能需要相应的传感器等。
其中，状态信息管理模块112用于对状态信息进行处理。比如，在用户进入第一状态或处于第一状态时获取状态信息并将状态信息传输至电子装置110或学习模块114。其中，第一状态例如可以为休息状态、驾驶状态等。另外，可以利用界面交互或语音等方式来检测用户进入第一状态或用户退出第一状态，比如用户进入第一状态的指令或用户退出第一状态的指令，在此本申请不做限制。需要说明的，该状态信息管理模块112可以与至少一种传感器通信，从而可以获取状态信息。比如，状态信息包括环境信息。当环境信息为车内温度信息时，那么状态信息管理模块112可以从温度传感器获取到车内温度信息。
其中，评价模块113包括第一评价子模块1131和第二评价子模块1132。第一评价子模块1131用于基于用户处于第一状态时所获取的评价参数进行评分得到第一评分。评价参数例如可以包括持续时间、姿态变换次数和生理参数，持续时间是用户在使用座椅的座椅参数为第一座椅参数时的时间长度，姿态变换次数是用户在持续时间内用户变换姿态的次数，生理参数是用户在使用座椅的座椅参数为第一座椅参数时的生理参数。可以理解的，生理参数例如可以包括心跳统计值、心率异变性、呼吸统计值、体温统计值、眨眼次数等。进一步的，在获取评价参数时所涉及的部件或模块等在本申请中也不做限制。比如，可以通过计时器获取持续时间，可以通过可穿戴设备的加速度传感器计算得到姿态变换次数，也可以通过视觉信号分析得到姿态变换次数，可以通过可穿戴设备的心率传感器获取心跳统计值或心率易变性，也通过视觉信号获取心跳统计值，通过声音传感器获取呼吸统计值，通过视觉信号分析得到呼吸统计值、眨眼次数等，通过可穿戴设备获取体温统计值等。第二评价子模块1132用于在用户退出第一状态时获取第二评分。举例来说，可以通过界面交互的方式获取第二评分，也可以通过语音询问的方式获取第二评分，也可以通过向手机发送消息的方式获取第二评分等。具体获取第二评分的方式在本申请中不做限制。在评价模块113得到第一评分和第二评分时，可以将第一评分和第二评分作为该用户对应的评分，也可以将第一评分和第二评分的均值作为该用户对应的评分，也可以将第一评分和第二评分中最高的评分作为该用户对应的评分，还可以将按照预设加权公式对第一评分和第二评分进行加权后，将加权后的评分作为该用户对应的评分，在此不做限制。最后，将该评分传输给电子装置110或学习模块114。需要说明的，若用户未反馈第二评分时，第二评价子模块1132可以将第二评分确定为无效评分。即在评价模块113得到第一评分时，可以将第一评分作为该用户对应的评分，并将该评分传输给电子装置110或学习模块114。
其中，学习模块114用于对用户信息、状态信息和评分进行处理。具体的，学习模块114可以利用用户信息、状态信息和评分进行模型训练。比如，可以利用用户信息、状态信息和评分实现聚类模型的训练。在模型训练结束时，还可以利用训练好的聚类模型，实现基于用户信息和状态信息获取历史座椅参数等。
其中，座椅调节装置12用于按照车载设备11或电子装置110传输的座椅参数调节座椅。座椅参数获取装置13用于在用户处于第一状态时检测到座椅参数变化时反馈变化后的 座椅参数。可以理解的，座椅参数获取装置可以为多种传感器。
参见图2，图2为本申请实施例提供的一种座椅示意图。如图2所示，可以看出，一般来说，在调节座椅时，主要与座椅靠背角度、座椅高度、座椅前后位置等有关。当然，还可以与座椅温度有关。具体可以调节座椅的哪些参数，本申请不做限制。
可以理解的，目前，为了提高用户在使用座椅时的舒适性体验，往往会将座椅的参数调节到预先设置好的参数，以此来避免用户手动调节座椅，实现解放用户的双手。一般来说，预先设置好的参数都是厂商提前设定的固定参数。比如，厂商可以提前设定好固定的座椅靠背角度，也可以提前设定好固定的座椅高度。因此，这种座椅调节方式比较死板，不够灵活，也无法满足差异化的用户需求。
基于此，本申请提供一种座椅调节方法，以解决上述技术问题，下面对本申请实施例进行详细介绍。
本申请实施例提供的一种座椅调节方法可以应用于车载设备，该车载设备可以为电子装置，也可以为包括该电子装置的设备。下面以电子装置为例，参见图3，图3为本申请实施例提供的一种座椅调节方法的流程示意图。如图3所示，该方法包括：
301、电子装置获取用户对应的用户信息和状态信息。
在步骤301之前，电子装置可以接收用户进入第一状态的指令。在电子装置接收用户进入第一状态的指令时，电子装置可以通过用户信息管理模块获取用户对应的用户信息。具体的，电子装置可以通过摄像头识别用户的身份信息，或，识别用户输入的所述身份信息；然后，电子装置可以根据身份信息，获取用户信息。
其中，通过摄像头识别用户的身份信息，该身份信息例如可以是包括该用户的图像、包括该用户的视频。比如，该用户的人脸图像、该用户的虹膜图像等。识别用户输入的身份信息，该身份信息例如可以是登录账号和登录密码等。
可以看出，上述技术方案中，实现了用户信息的获取。
进一步的，电子装置还可以通过状态信息管理模块获取用户对应的状态信息。
其中，该状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，环境信息包括车内的环境信息和/或车外的环境信息。
举例来说，车内环境信息可以包括车内人数、每个人坐的位置、车内分贝信息、车内温度信息等，车外的环境信息例如可以包括车外温度信息、车外亮度信息等。时间信息例如可以为当前时刻的时间戳信息、季节标签信息、时间标签信息等。比如，季节标签信息可以包括“春”、“夏”、“秋”、“冬”四种标签，时间标签信息可以包括“上午”、“下午”、“晚上”、“凌晨”四种标签，时间标签信息还可以包括“工作日”、“周末”两种标签。地理位置信息例如可以包括室内停车场、室外停车场、家、公司、服务区、户外公园、山区等。
可以看出，上述技术方案中，结合状态信息，实现了更加精准的把控用户需求，从而能够更好的为用户提供满足其需求的座椅参数。
另外，若电子装置是第一次接收用户进入第一状态的指令，电子装置也可以通过用户信息管理模块获取用户对应的用户信息，也可以通过状态信息管理模块获取用户对应的状 态信息。由于电子装置是第一次接收用户进入状态的指令，即表明无用户对应的历史数据。因此，电子装置无法根据用户信息和状态信息，获取历史数据。此时，电子装置可以获取预设座椅参数，并按照预设座椅参数调节座椅，即电子装置通过座椅调节装置按照预设座椅参数调节座椅。可以理解的，预设座椅参数例如可以包括座椅靠背角度、座椅高度、座椅前后位置、座椅温度等。比如，座椅靠背角度为R 0度，座椅高度为距离原点H 0厘米，座椅前后位置为距离原点L 0厘米，座椅温度为T 0摄氏度。
302、电子装置根据用户信息和状态信息，确定用户对应的座椅参数。
可选的，在一种可能的实施方式中，在根据用户信息和状态信息，确定用户对应的座椅参数时，电子装置可以向云服务器发送用户信息和状态信息，当云服务器接收用户信息和状态信息时，云服务器基于用户信息和状态信息，确定用户对应的座椅参数，从而可以向电子装置发送用户对应的座椅参数。
其中，用户对应的座椅参数例如可以包括座椅靠背角度、座椅高度、座椅前后位置、座椅温度等。
另外，电子装置也可以根据用户信息和状态信息，获取N条历史数据，从而根据N条历史数据，确定用户对应的座椅参数。
其中，N为大于0的整数，N例如可以为1、2、3、4、5、6、10、12等数值。
可以理解的，N条历史数据中的每条历史数据也包括历史状态信息、历史评分、历史座椅参数。其中，历史状态信息包括以下至少一种：历史环境信息、历史时间信息或历史地理位置信息，历史环境信息包括车内的历史环境信息和/或车外的历史环境信息。进一步的，历史状态信息可以参考参考图3中步骤301所涉及的状态信息，在此不加赘述。另外，N条历史数据中的每条历史数据为一个历史样本点关联的数据。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
进一步的，在根据用户信息和状态信息，获取N条历史数据时，电子装置可以向云服务器发送用户信息和状态信息。当云服务器接收用户信息和状态信息时，云服务器可以根据用户信息和状态信息，获取N条历史数据，从而可以将N条历史数据发送给电子装置。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定历史数据，为后续基于历史数据确定座椅参数做准备。
另外，在根据用户信息和状态信息，获取N条历史数据时，电子装置可以根据用户信息，从数据库中获取属于不同类别的历史数据，该历史数据包括历史状态信息，该类别是根据该历史状态信息的相似度确定的。进一步的，电子装置还可以根据该状态信息，从该历史数据中确定属于同一类别的N条历史数据。
可以理解，在电子装置根据用户信息，从数据库中获取属于不同类别的历史数据之前，电子装置每次接收到用户进入第一状态的指令时，电子装置均可以通过用户信息管理模块获取用户对应的用户信息，也可以通过状态信息管理模块获取用户对应的状态信息。
进一步的，在电子装置每次接收到用户退出第一状态的指令之前，若座椅参数获取装置未检测到座椅参数发生变化，即座椅参数获取装置未向电子装置反馈变化后的座椅参数。那么，在电子装置每次接收到用户退出第一状态的指令时，电子装置可以通过评价模块获 取评分K1。具体的，在用户已反馈第二评分K1时，该评分K1可以是第一评分K1和第二评分K1的总和，也可以是第一评分K1和第二评分K1的均值，也可以是第一评分K1和第二评分K1中评分最高的评分，也可以是按照预设加权公式对第一评分K1和第二评分K1进行加权后的评分，在此不做限制。在用户未反馈第二评分K1时，该评分K1为第一评分K1。其中，该第一评分K1是根据评价参数L1确定的，该评价参数L1包括持续时间L1、姿态变换次数L1和生理参数L1。持续时间L1是用户在使用座椅的座椅参数为座椅参数P1时的时间长度，姿态变换次数L1是用户在持续时间L1内用户变换姿态的次数，生理参数L1是用户在使用座椅的座椅参数为座椅参数P1时的生理参数。其中，生理参数L1例如可以为用户在使用座椅的座椅参数为座椅参数P1时的心跳统计值、心率异变性、呼吸统计值、体温统计值、眨眼次数等。可以理解的，比如，在电子装置第一次接收到用户退出第一状态的指令时，座椅参数P1可以为预设座椅参数。那么，持续时间L1是用户在使用座椅的座椅参数为预设座椅参数时的时间长度，姿态变换次数L1是用户在持续时间L1内用户变换姿态的次数，生理参数L1是用户在使用座椅的座椅参数为预设座椅参数时的生理参数。
进一步的，在电子装置每次接收到用户退出第一状态的指令之前，若座椅参数获取装置检测到座椅参数发生变化，即座椅参数获取装置向电子装置反馈变化后的座椅参数。那么，在电子装置每次接收到用户退出第一状态的指令之前，每当座椅参数获取装置检测到座椅参数发生变化时，电子装置都会通过评价模块获取座椅参数变化前的第一评分以及座椅参数变化后的第一评分，且，电子装置都会通过座椅参数获取装置获取到变化后的座椅参数。即，电子装置获取至少一个座椅参数和至少一个第一评分，至少一个座椅参数和至少一个第一评分一一对应。至少一个第一评分中的任意一个第一评分K2是根据评价参数L2确定的。该评价参数L2包括持续时间L2、姿态变换次数L2和生理参数L2。持续时间L2是用户在使用座椅的座椅参数为第一评分K2对应的座椅参数时的时间长度，姿态变换次数L2是用户在持续时间L2内用户变换姿态的次数，生理参数L2是用户在使用座椅的座椅参数为第一评分K2对应的座椅参数时的生理参数。其中，生理参数L2例如可以为用户在使用座椅的座椅参数为第一评分K2对应的座椅参数时的心跳统计值、心率异变性、呼吸统计值、体温统计值、眨眼次数等。进一步的，电子装置可以根据至少一个第一评分，从至少一个座椅参数中确定评分最高的第一评分K3所对应的座椅参数。另外，在电子装置每次接收到用户退出第一状态的指令时，若用户已反馈第二评分K2，电子装置可以通过评价模块获取第二评分K2。同时，电子装置可以根据第一评分K3和第二评分K2，确定用户对应的评分K2。可以理解的，评分K2可以是第一评分K3和第二评分K2的总和，也可以是第一评分K3和第二评分K2的均值，也可以是第一评分K3和第二评分K2中评分最高的评分，也可以是按照预设加权公式对第一评分K3和第二评分K2进行加权后的评分，在此不做限制。若用户未反馈第二评分K2，那么，用户对应的评分K2是第一评分K3。
综上，电子装置还可以将每次获取的用户信息、状态信息、评分、座椅参数作为一个样本点关联的信息。比如，电子装置可以将用户信息、状态信息、评分K1、座椅参数P1作为一个样本点关联的信息。电子装置也可以将用户信息、状态信息、评分K2、第一评分K3所对应的座椅参数作为一个样本点关联的信息。进一步的，电子装置还可以通过学习模 块利用聚类模型对样本点关联的信息进行聚类，以利用状态信息之间的相似度确定样本点所属的类别。可以理解的，在本申请中，当电子装置通过学习模块利用聚类模型对样本点关联的信息进行聚类时，可以利用状态信息包括的至少一种信息之间的相似度确定样本点所属的类别。比如，当状态信息包括环境信息时，可以利用环境信息之间的相似度确定样本点所属的类别，当状态信息包括环境信息和时间信息时，可以利用环境信息之间的相似度以及时间信息之间的相似度确定样本点所属的类别等。
需要说明的，在电子装置根据用户信息，从数据库中获取属于不同类别的历史数据之前，电子装置已经完成了聚类。因此，电子装置可以在本地实现根据用户信息和状态信息，获取N条历史数据。
可以看出，上述技术方案中，实现了基于用户信息获取属于不同类别的历史数据。同时，由于类别是根据历史数据包括的历史状态信息的相似度确定的，从而实现基于用户的状态信息从该用户对应的历史数据中确定出属于同一类别的N条历史数据，即实现了基于用户的状态信息确定了用户在相似历史状态所对应的历史数据。
303、电子装置按照用户对应的座椅参数调节座椅。
其中，电子装置可以通过座椅调节装置按照用户对应的座椅参数调节座椅。
可以看出，上述技术方案中，通过利用用户对应的用户信息和状态信息为用户配置对应的座椅参数，满足了差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。
可选的，在一种可能的实施方式中，电子装置根据N条历史数据，确定用户对应的座椅参数，包括：电子装置根据预设条件，从N条历史数据中获取M条历史数据，预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，M为大于0且小于N的整数；电子装置根据M条历史数据对应的M条历史座椅参数，确定用户对应的座椅参数。
其中，M例如可以为1、2、3、4、5、6、10、12等数值。
其中，电子装置根据预设条件，从N条历史数据中获取M条历史数据。即，电子装置可以从N条历史数据中获取评分最高的M条历史数据，电子装置也可以从N条历史数据中获取评分高于阈值的M条历史数据，电子装置还可以按照评分从高到低的顺序从N条历史数据中获取前M条历史数据。
另外，在M为1时，用户对应的座椅参数为评分最高历史数据对应的座椅参数；在M为大于1的整数时，用户对应的座椅参数可以是M条历史座椅参数的均值，也可以是M条历史座椅参数的中位数，在本申请中不做限制。
举例来说，M条历史座椅参数包括历史座椅参数A、历史座椅参数B和历史座椅参数C。历史座椅参数A包括座椅靠背角度A、座椅高度A、座椅前后位置A和座椅温度A；历史座椅参数B包括座椅靠背角度B、座椅高度B、座椅前后位置B和座椅温度B；历史座椅参数C包括座椅靠背角度C、座椅高度C、座椅前后位置C和座椅温度C。用户对应的座椅参数包括用户对应的座椅靠背角度、用户对应的座椅高度、用户对应的座椅前后位置和用户对应的座椅温度。可以理解的，用户对应的座椅靠背角度可以为座椅靠背角度A、座椅靠背角度B和座椅靠背角度C的均值，也可以为座椅靠背角度A、座椅靠背角度B和 座椅靠背角度C的中位数；用户对应的座椅高度可以为座椅高度A、座椅高度B、座椅高度C的均值，也可以为座椅高度A、座椅高度B、座椅高度C的中位数；用户对应的座椅前后位置可以为座椅前后位置A、座椅前后位置B和座椅前后位置C的均值，也可以为座椅前后位置A、座椅前后位置B和座椅前后位置C的中位数；用户对应的座椅温度可以为座椅温度A、座椅温度B和座椅温度C的均值，也可以为座椅温度A、座椅温度B和座椅温度C的中位数。
可以看出，上述技术方案中，实现了基于评分确定用户对应的座椅参数，从而可以更好的把控用户需求，也可以为用户提供满足其需求的座椅参数。
进一步的，在电子装置根据预设条件，从N条历史数据中获取M条历史数据之前，该方法还包括：包括：电子装置根据N条历史数据中的每条历史数据对应的历史时间信息与时间信息之间的差值，确定N条历史数据对应的N个权重，其中，该差值越小，该权重越大；电子装置根据N个权重以及N条历史数据对应的N条历史评分，确定N条评分系数，N条评分系数中的任意一个评分系数A是根据评分系数A对应的权重以及评分系数A对应的历史评分确定的；电子装置将N条评分系数更新为N条历史评分，N条评分系数与N条历史评分一一对应。
可以理解的，比如，电子装置可以将该评分系数A更新为评分系数A对应的历史评分。
进一步的，举例来说，N条历史数据包括历史数据1、历史数据2和历史数据3。历史数据1对应的历史时间信息为2020年4月12日10:30，历史数据2对应的历史时间信息为2020年4月13日14:30，历史数据3对应的历史时间信息1为2020年4月14日16:30。该时间信息为2020年4月15日9:30。那么，可以看出，历史数据1对应的历史时间信息与该时间信息之间的差值最大，历史数据3对应的历史时间信息与该时间信息之间的差值最小。因此，历史数据1对应的权重最小，历史数据3对应的权重最大。
可以看出，上述技术方案中，通过利用历史时间信息与时间信息之间的差值为每条历史评分分配不同的权重，并基于权重和历史评分确定不同的评分系数，实现了基于评分系数来选取历史数据。同时，也避免了在较长时间跨度内用户偏好的座椅参数发生变化时推荐的座椅参数无法满足用户需求的情况。
参见图4，图4为本申请实施例提供的一种座椅调节装置的结构示意图。该座椅调节装置400包括收发模块401和处理模块402。其中，收发模块401，用于获取用户对应的用户信息和状态信息；处理模块402，用于根据用户信息和状态信息，确定用户对应的座椅参数；处理模块402，还用于按照用户对应的座椅参数调节座椅。
其中，状态信息可以参考图3中步骤301所涉及的状态信息，在此不加赘述。用户对应的座椅参数可以参考图3中步骤303所涉及的用户对应的座椅参数，在此不加赘述。
可以看出，上述技术方案中，通过利用用户对应的用户信息和状态信息为用户配置对应的座椅参数，满足了差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。
在一种可能的实施方式中，在获取用户对应的用户信息时，处理模块402，用于通过 摄像头识别用户的身份信息，或，识别用户输入的身份信息；根据身份信息，获取用户信息。
其中，关于身份信息可以参考图3中步骤301所涉及的身份信息，在此不加赘述。
可以看出，上述技术方案中，实现了用户信息的获取。
在一种可能的实施方式中，在根据用户信息和状态信息，确定用户对应的座椅参数时，收发模块401，用于向云服务器发送用户信息和状态信息；接收云服务器发送的用户对应的座椅参数；或，处理模块402，用于根据用户信息和状态信息，获取N条历史数据，N为大于0的整数；根据N条历史数据，确定用户对应的座椅参数。
其中，关于用户对应的座椅参数可以参考图3中步骤302所涉及的座椅参数，在此不加赘述。其中，关于历史数据可以参考图3中步骤302所涉及的历史数据，在此不加赘述。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
在一种可能的实施方式中，根据用户信息和状态信息，获取N条历史数据，包括：收发模块401，用于向云服务器发送用户信息和状态信息；接收云服务器发送的N条历史数据。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定历史数据，为后续基于历史数据确定座椅参数做准备。
可选的，在一种可能的实施方式中，在根据用户信息和状态信息，获取N条历史数据时，处理模块402，具体用于根据用户信息，从数据库中获取属于不同类别的历史数据，历史数据包括历史状态信息，类别是根据历史状态信息的相似度确定的；根据状态信息，从历史数据中确定属于同一类别的N条历史数据。
其中，历史状态信息可以参考图3中步骤302所涉及的历史状态信息，在此不加赘述。
可以看出，上述技术方案中，实现了基于用户信息获取属于不同类别的历史数据。同时，由于类别是根据历史数据包括的历史状态信息的相似度确定的，从而实现基于用户的状态信息从该用户对应的历史数据中确定出属于同一类别的N条历史数据，即实现了基于用户的状态信息确定了用户在相似历史状态所对应的历史数据。
在一种可能的实施方式中，N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据N条历史数据，确定用户对应的座椅参数时，处理模块402，具体用于根据预设条件，从N条历史数据中获取M条历史数据，该预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，该M为大于0且小于N的整数；根据M条历史数据对应的M条历史座椅参数，确定用户对应的座椅参数。
其中，关于根据预设条件，从N条历史数据中获取M条历史数据的内容可以参考图3中的步骤303，在此不加赘述。
可以看出，上述技术方案中，实现了基于评分确定用户对应的座椅参数，从而可以更好的把控用户需求，也可以为用户提供满足其需求的座椅参数。
可选的，在一种可能的实施方式中，N条历史数据中的每条历史数据还包括历史状态信息，历史状态信息包括历史时间信息，在根据预设条件，从N条历史数据中获取M条历史数据之前，处理模块402，具体用于根据N条历史数据中的每条历史数据对应的历史时 间信息与时间信息之间的差值，确定N条历史数据对应的N个权重，其中，差值越小，权重越大；根据N个权重以及N条历史数据对应的N条历史评分，确定N条评分系数，N条评分系数中的任意一个评分系数A是根据评分系数A对应的权重以及评分系数A对应的历史评分确定的；将N条评分系数更新为N条历史评分，N条评分系数与N条历史评分一一对应。
可以看出，上述技术方案中，通过利用历史时间信息与时间信息之间的差值为每条历史评分分配不同的权重，并基于权重和历史评分确定不同的评分系数，实现了基于评分系数来选取历史数据。同时，也避免了在较长时间跨度内用户偏好的座椅参数发生变化时推荐的座椅参数无法满足用户需求的情况。
本申请实施例提供的一种座椅调节***，该***包括处理器、存储器和座椅调节装置，其中，处理器，用于从存储器中获取用户对应的用户信息和状态信息；根据用户信息和状态信息，确定用户对应的座椅参数；座椅调节装置，用于按照用户对应的座椅参数调节座椅。
其中，关于用户对应的座椅参数可以参考图3中步骤302所涉及的座椅参数，在此不加赘述。其中，关于历史数据可以参考图3中步骤302所涉及的历史数据，在此不加赘述。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
在一种可能的实施方式中，该***还包括身份识别装置，在从存储器中获取用户对应的用户信息和状态信息时，身份识别装置，用于通过摄像头识别用户的身份信息，或，识别用户输入的身份信息；处理器，用于根据身份信息，获取用户信息。
其中，关于身份信息可以参考图3中步骤301所涉及的身份信息，在此不加赘述。
可以看出，上述技术方案中，实现了用户信息的获取。
在一种可能的实施方式中，该***还包括通信装置，在根据用户信息和状态信息，确定用户对应的座椅参数时，
处理器，用于通过通信装置向云服务器发送用户信息和状态信息；通过通信装置接收云服务器发送的用户对应的座椅参数；或，
处理器，用于根据用户信息和状态信息，从存储器中获取N条历史数据，N为大于0的整数；根据N条历史数据，确定用户对应的座椅参数。
其中，通信装置例如可以为车载tbox(telematicsbox)。
其中，关于用户对应的座椅参数可以参考图3中步骤302所涉及的座椅参数，在此不加赘述。其中，关于历史数据可以参考图3中步骤302所涉及的历史数据，在此不加赘述。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
在一种可能的实施方式中，在根据用户信息和状态信息，获取N条历史数据时，
处理器，用于通过通信装置向云服务器发送用户信息和状态信息；接收云服务器发送的N条历史数据。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定历史数据， 为后续基于历史数据确定座椅参数做准备。
在一种可能的实施方式中，在根据用户信息和状态信息，获取N条历史数据时，
处理器，用于根据用户信息，从存储器中获取属于不同类别的历史数据，历史数据包括历史状态信息，类别是根据历史状态信息的相似度确定的；根据状态信息，从历史数据中确定属于同一类别的N条历史数据。
其中，历史状态信息可以参考图3中步骤302所涉及的历史状态信息，在此不加赘述。
可以看出，上述技术方案中，实现了基于用户信息获取属于不同类别的历史数据。同时，由于类别是根据历史数据包括的历史状态信息的相似度确定的，从而实现基于用户的状态信息从该用户对应的历史数据中确定出属于同一类别的N条历史数据，即实现了基于用户的状态信息确定了用户在相似历史状态所对应的历史数据。
在一种可能的实施方式中，N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据N条历史数据，确定用户对应的座椅参数时，
处理器，用于根据预设条件，从N条历史数据中获取M条历史数据，预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，M为大于0且小于N的整数；根据M条历史数据对应的M条历史座椅参数，确定用户对应的座椅参数。
其中，关于根据预设条件，从N条历史数据中获取M条历史数据的内容可以参考图3中的步骤303，在此不加赘述。
可以看出，上述技术方案中，实现了基于评分确定用户对应的座椅参数，从而可以更好的把控用户需求，也可以为用户提供满足其需求的座椅参数。
在一种可能的实施方式中，N条历史数据中的每条历史数据还包括历史状态信息，历史状态信息包括历史时间信息，在根据预设条件，从N条历史数据中获取M条历史数据之前，
处理器，还用于根据N条历史数据中的每条历史数据对应的历史时间信息与时间信息之间的差值，确定N条历史数据对应的N个权重，其中，差值越小，权重越大；根据N个权重以及N条历史数据对应的N条历史评分，确定N条评分系数，N条评分系数中的任意一个评分系数A是根据评分系数A对应的权重以及评分系数A对应的历史评分确定的；将N条评分系数更新为N条历史评分，N条评分系数与N条历史评分一一对应。
可以看出，上述技术方案中，通过利用历史时间信息与时间信息之间的差值为每条历史评分分配不同的权重，并基于权重和历史评分确定不同的评分系数，实现了基于评分系数来选取历史数据。同时，也避免了在较长时间跨度内用户偏好的座椅参数发生变化时推荐的座椅参数无法满足用户需求的情况。
本申请实施例还提供的一种座椅调节***，该***包括车，车包括处理器、存储器、通信装置和座椅调节装置，其中，
处理器，用于从存储器中获取用户对应的用户信息和状态信息；根据用户信息和状态信息，确定用户对应的座椅参数；
座椅调节装置，用于按照用户对应的座椅参数调节座椅。
其中，状态信息可以参考图3中步骤301所涉及的状态信息，在此不加赘述。用户对 应的座椅参数可以参考图3中步骤303所涉及的用户对应的座椅参数，在此不加赘述。
其中，通信装置例如可以为车载tbox(telematicsbox)。
可以看出，上述技术方案中，通过利用用户对应的用户信息和状态信息为用户配置对应的座椅参数，满足了差异化的用户需求，避免按照厂商提前设定的固定参数调节座椅，也为用户提供了更加灵活的座椅调节方式，更好的提升了用户体验。
在一种可能的实施方式中，车还包括身份识别装置，在从存储器中获取用户对应的用户信息和状态信息时，
身份识别装置，用于通过摄像头识别用户的身份信息，或，识别用户输入的身份信息；
处理器，用于根据身份信息，获取用户信息。
其中，关于身份信息可以参考图3中步骤301所涉及的身份信息，在此不加赘述。
可以看出，上述技术方案中，实现了用户信息的获取。
在一种可能的实施方式中，该***还包括云服务器，车还包括通信装置，在根据用户信息和状态信息，确定用户对应的座椅参数时，
处理器，用于通过通信装置向云服务器发送用户信息和状态信息；云服务器，用于根据用户信息和状态信息，确定用户对应的座椅参数；向通信装置发送用户对应的座椅参数；或，
处理器，用于根据用户信息和状态信息，从存储器中获取N条历史数据，N为大于0的整数；根据N条历史数据，确定用户对应的座椅参数。
其中，关于用户对应的座椅参数可以参考图3中步骤302所涉及的座椅参数，在此不加赘述。其中，关于历史数据可以参考图3中步骤302所涉及的历史数据，在此不加赘述。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定座椅参数，也实现了基于用户信息和状态信息，确定历史数据，从而基于历史数据确定座椅参数。
在一种可能的实施方式中，在根据用户信息和状态信息，获取N条历史数据时，
云服务器，用于接收通信装置发送的用户信息和状态信息；
处理器，用于通过通信装置接收云服务器发送的N条历史数据。
可以看出，上述技术方案中，实现了云服务器基于用户信息和状态信息确定历史数据，为后续基于历史数据确定座椅参数做准备。
在一种可能的实施方式中，在根据用户信息和状态信息，获取N条历史数据时，
处理器，用于根据用户信息，从存储器中获取属于不同类别的历史数据，历史数据包括历史状态信息，类别是根据历史状态信息的相似度确定的；根据状态信息，从历史数据中确定属于同一类别的N条历史数据。
其中，历史状态信息可以参考图3中步骤302所涉及的历史状态信息，在此不加赘述。
可以看出，上述技术方案中，实现了基于用户信息获取属于不同类别的历史数据。同时，由于类别是根据历史数据包括的历史状态信息的相似度确定的，从而实现基于用户的状态信息从该用户对应的历史数据中确定出属于同一类别的N条历史数据，即实现了基于用户的状态信息确定了用户在相似历史状态所对应的历史数据。
在一种可能的实施方式中，N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据N条历史数据，确定用户对应的座椅参数时，
处理器，用于根据预设条件，从N条历史数据中获取M条历史数据，预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，M为大于0且小于N的整数；根据M条历史数据对应的M条历史座椅参数，确定用户对应的座椅参数。
其中，关于根据预设条件，从N条历史数据中获取M条历史数据的内容可以参考图3中的步骤303，在此不加赘述。
可以看出，上述技术方案中，实现了基于评分确定用户对应的座椅参数，从而可以更好的把控用户需求，也可以为用户提供满足其需求的座椅参数。
在一种可能的实施方式中，N条历史数据中的每条历史数据还包括历史状态信息，历史状态信息包括历史时间信息，在根据预设条件，从N条历史数据中获取M条历史数据之前，
处理器，还用于根据N条历史数据中的每条历史数据对应的历史时间信息与时间信息之间的差值，确定N条历史数据对应的N个权重，其中，差值越小，权重越大；根据N个权重以及N条历史数据对应的N条历史评分，确定N条评分系数，N条评分系数中的任意一个评分系数A是根据评分系数A对应的权重以及评分系数A对应的历史评分确定的；将N条评分系数更新为N条历史评分，N条评分系数与N条历史评分一一对应。
可以看出，上述技术方案中，通过利用历史时间信息与时间信息之间的差值为每条历史评分分配不同的权重，并基于权重和历史评分确定不同的评分系数，实现了基于评分系数来选取历史数据。同时，也避免了在较长时间跨度内用户偏好的座椅参数发生变化时推荐的座椅参数无法满足用户需求的情况。
参见图5，图5为本申请实施例提供的一种电子装置的结构示意图。该电子装置500包括存储器501、处理器502和收发器503。它们之间通过总线504连接。存储器501用于存储相关指令和数据，并可以将存储的数据传输给处理器502。
其中，存储器501可以包括易失性存储器(volatile memory)，例如随机存取存储器(random-access memory，RAM)；存储器也可以包括非易失性存储器(non-volatile memory)，例如快闪存储器(flash memory)，硬盘(hard disk drive，HDD)或固态硬盘(solid-state drive，SSD)；存储器还可以包括上述种类的存储器的组合。
其中，处理器502可以是中央处理器(central processing unit，CPU)、微处理器、特定应用集成电路(application specific intergratedcircuit，ASIC)、可编程逻辑器件(programmable logic device，PLD)或其组合。上述PLD可以是复杂可编程逻辑器件(complex programmable logic device，CPLD)、现场可编程逻辑门阵列(field-programmable gate array，FPGA)、通用阵列逻辑(generic array logic,GAL)或其任意组合。
另外，存储器501可以是物理上独立的单元，也可以与处理器502集成在一起。
进一步的，处理器502可以执行存储器501存储的相关指令，以执行图3实施例所涉及的方法。
本申请实施例还提供一种车载设备，该车载设备包括图4实施例所涉及的电子装置。
本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，当该计算机程序被运行时，实现图3实施例所涉及的任一项方法。
本申请实施例还提供一种种计算机程序产品，包括计算机指令，当该计算机指令在图4实施例所涉及的电子装置上运行时，使得该电子装置执行图3实施例所涉及的任一项方法。
上述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本申请实施例方案的目的。另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
上述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，云服务器，或者网络设备等)执行本申请各个实施例上述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (28)

  1. 一种座椅调节方法，其特征在于，包括：
    获取用户对应的用户信息和状态信息；
    根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；
    按照所述用户对应的座椅参数调节座椅。
  2. 根据权利要求1所述的方法，其特征在于，所述获取用户对应的用户信息，包括：
    通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；
    根据所述身份信息，获取所述用户信息。
  3. 根据权利要求1所述的方法，其特征在于，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
  4. 根据权利要求1-3任意一项所述的方法，其特征在于，所述根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数，包括：
    向云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述用户对应的座椅参数；或，
    根据所述用户信息和所述状态信息，获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
  5. 根据权利要求4所述的方法，其特征在于，所述根据所述用户信息和所述状态信息，获取N条历史数据，包括：
    向所述云服务器发送所述用户信息和所述状态信息；
    接收所述云服务器发送的所述N条历史数据。
  6. 根据权利要求4所述的方法，其特征在于，所述根据所述用户信息和所述状态信息，获取N条历史数据，包括：
    根据所述用户信息，从数据库中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；
    根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
  7. 根据权利要求5或6所述的方法，其特征在于，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，所述根据所述N条历史数据，确定所述用户对应的座椅参数，包括：
    根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；
    根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
  8. 根据权利要求7所述的方法，其特征在于，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，所述方法还包括：
    根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；
    根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；
    将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
  9. 一种座椅调节***，其特征在于，所述***包括处理器、存储器和座椅调节装置，其中，
    所述处理器，用于从所述存储器中获取用户对应的用户信息和状态信息；根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；
    所述座椅调节装置，用于按照所述用户对应的座椅参数调节座椅。
  10. 根据权利要求9所述的***，其特征在于，所述***还包括身份识别装置，在从所述存储器中获取用户对应的用户信息和状态信息时，
    所述身份识别装置，用于通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；
    所述处理器，用于根据所述身份信息，获取所述用户信息。
  11. 根据权利要求9所述的***，其特征在于，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
  12. 根据权利要求9-11任意一项所述的***，其特征在于，所述***还包括通信装置，在根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数时，
    所述处理器，用于通过所述通信装置向云服务器发送所述用户信息和所述状态信息；通过所述通信装置接收所述云服务器发送的所述用户对应的座椅参数；或，
    所述处理器，用于根据所述用户信息和所述状态信息，从所述存储器中获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
  13. 根据权利要求12所述的***，其特征在于，在根据所述用户信息和所述状态信息，获取N条历史数据时，
    所述处理器，用于通过所述通信装置向所述云服务器发送所述用户信息和所述状态信息；接收所述云服务器发送的所述N条历史数据。
  14. 根据权利要求12所述的***，其特征在于，在根据所述用户信息和所述状态信息，获取N条历史数据时，
    所述处理器，用于根据所述用户信息，从所述存储器中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
  15. 根据权利要求13或14所述的***，其特征在于，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据所述N条历史数据，确定所述用户对应的座椅参数时，
    所述处理器，用于根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
  16. 根据权利要求15所述的***，其特征在于，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，
    所述处理器，还用于根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小，所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
  17. 一种座椅调节***，其特征在于，所述***包括车，所述车包括处理器、存储器、通信装置和座椅调节装置，其中，
    所述处理器，用于从所述存储器中获取用户对应的用户信息和状态信息；根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；
    所述座椅调节装置，用于按照所述用户对应的座椅参数调节座椅。
  18. 根据权利要求17所述的***，其特征在于，所述车还包括身份识别装置，在从所述存储器中获取用户对应的用户信息和状态信息时，
    所述身份识别装置，用于通过摄像头识别所述用户的身份信息，或，识别所述用户输入的所述身份信息；
    所述处理器，用于根据所述身份信息，获取所述用户信息。
  19. 根据权利要求17所述的***，其特征在于，所述状态信息包括以下至少一种：环境信息、时间信息或地理位置信息，所述环境信息包括车内的环境信息和/或车外的环境信息。
  20. 根据权利要求17-19任意一项所述的***，其特征在于，所述***还包括云服务器，所述车还包括通信装置，在根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数时，
    所述处理器，用于通过所述通信装置向云服务器发送所述用户信息和所述状态信息；所述云服务器，用于根据所述用户信息和所述状态信息，确定所述用户对应的座椅参数；向所述通信装置发送所述用户对应的座椅参数；或，
    所述处理器，用于根据所述用户信息和所述状态信息，从所述存储器中获取N条历史数据，所述N为大于0的整数；根据所述N条历史数据，确定所述用户对应的座椅参数。
  21. 根据权利要求20所述的***，其特征在于，在根据所述用户信息和所述状态信息，获取N条历史数据时，
    所述云服务器，用于接收所述通信装置发送的所述用户信息和所述状态信息；
    所述处理器，用于通过所述通信装置接收所述云服务器发送的所述N条历史数据。
  22. 根据权利要求20所述的***，其特征在于，在根据所述用户信息和所述状态信息，获取N条历史数据时，
    所述处理器，用于根据所述用户信息，从所述存储器中获取属于不同类别的历史数据，所述历史数据包括历史状态信息，所述类别是根据所述历史状态信息的相似度确定的；根据所述状态信息，从所述历史数据中确定属于同一类别的所述N条历史数据。
  23. 根据权利要求21或22所述的***，其特征在于，所述N条历史数据中的每条历史数据包括历史评分和历史座椅参数，在根据所述N条历史数据，确定所述用户对应的座椅参数时，
    所述处理器，用于根据预设条件，从所述N条历史数据中获取M条历史数据，所述预设条件包括以下一种：评分最高、评分高于阈值、或评分从高到低的顺序，所述M为大于0且小于所述N的整数；根据所述M条历史数据对应的M条历史座椅参数，确定所述用户对应的座椅参数。
  24. 根据权利要求23所述的***，其特征在于，所述N条历史数据中的每条历史数据还包括历史状态信息，所述历史状态信息包括历史时间信息，在所述根据预设条件，从所述N条历史数据中获取所述M条历史数据之前，
    所述处理器，还用于根据所述N条历史数据中的每条历史数据对应的历史时间信息与所述时间信息之间的差值，确定所述N条历史数据对应的N个权重，其中，所述差值越小， 所述权重越大；根据所述N个权重以及所述N条历史数据对应的N条历史评分，确定N条评分系数，所述N条评分系数中的任意一个评分系数A是根据所述评分系数A对应的权重以及所述评分系数A对应的历史评分确定的；将所述N条评分系数更新为所述N条历史评分，所述N条评分系数与所述N条历史评分一一对应。
  25. 一种电子装置，其特征在于，包括处理器和存储器，所述处理器与所述存储器相连，所述存储器用于存储计算机程序，所述处理器用于执行所述存储器中存储的计算机程序，以使得所述电子装置执行如权利要求1至8中任一项所述的方法。
  26. 一种车载设备，其特征在于，包括如权利要求25所述的电子装置。
  27. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机程序，当所述计算机程序被运行时，实现如权利要求1-8任一项所述的方法。
  28. 一种计算机程序产品，其特征在于，包括计算机指令，当所述计算机指令在如权利要求25所述的电子装置上运行时，使得所述电子装置执行如权利要求1-8任一项所述的方法。
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