Scene recognition method, device and equipment, storage medium and vehicle

Abstract

The invention discloses a scene recognition method and device, equipment, a storage medium and a vehicle. The method comprises: for a target intelligent terminal, obtaining a plurality of sub-vehicle usage scenes corresponding to a target vehicle usage scene, the sub-vehicle usage scenes comprising function tag sequences and corresponding Bluetooth positioning sequences, each function tag sequence comprising a plurality of function tags arranged according to a time sequence, the function label is a label corresponding to a function involved in the target vehicle use scene, and the Bluetooth positioning sequence represents a relative position relationship between the target intelligent terminal and the vehicle along with time change in the target vehicle use scene. Classifying the plurality of vehicle using sub-scenes according to whether the plurality of vehicle using sub-scenes are the same or not to obtain a plurality of scene sets of different categories; and in the plurality of scene sets, determining the scene set of which the number of the sub-vehicle-use scenes meets a preset condition as at least one target scene set. According to the embodiment of the invention, the use experience of the target user on the Bluetooth key of the intelligent terminal can be improved.

Description

Technical Field

[0001] This application belongs to the technical field of smart terminal Bluetooth keys, and particularly relates to a scene recognition method, device, equipment, storage medium and vehicle. Background Art

[0002] With the development of artificial intelligence, smart terminals have been able to unlock and lock vehicles as Bluetooth keys of the vehicles. In order to achieve accurate unlocking and locking based on the smart terminal Bluetooth key, it is necessary to judge the position of the smart terminal Bluetooth key to determine the unlocking and locking range of the vehicle according to the position information of the smart terminal Bluetooth key, which involves the data calibration problem of the smart terminal Bluetooth key. Since different models of smart terminals have different sensitivities to Bluetooth signals, currently, usually one model of smart terminal corresponds to one calibration data.

[0003] However, in actual situations, if different users using the same model of smart terminal have different usage habits for the vehicle, it will result in different unlocking and locking ranges of the vehicle. Therefore, for the same model of smart terminal, a single calibration data is difficult to meet the usage experience of all users for the smart terminal Bluetooth key, resulting in a low usage experience of the smart terminal Bluetooth key for users. Summary of the Invention

[0004] The embodiments of this application provide a scene recognition method, device, equipment, storage medium and vehicle, which can improve the usage experience of the target user for the smart terminal Bluetooth key.

[0005] In a first aspect, the embodiments of this application provide a scene recognition method, and the method includes:

[0006] For a target smart terminal, obtain a plurality of sub-usage scenarios corresponding to the target usage scenario, where the target usage scenario is any one of the getting-on vehicle scenario and the getting-off vehicle scenario, and each sub-usage scenario includes a function tag sequence and its corresponding Bluetooth positioning sequence. Each function tag sequence includes a plurality of function tags arranged in chronological order, and the function tag is a tag corresponding to the function involved in the target usage scenario. The Bluetooth positioning sequence represents the relative position relationship that changes with time between the target smart terminal and the vehicle in the target usage scenario;

[0007] Classify the plurality of sub-usage scenarios according to whether the plurality of sub-usage scenarios are the same to obtain a plurality of different categories of scene sets, and each scene set includes at least one of the sub-usage scenarios;

[0008] Among the multiple scene sets, determine the scene sets in which the number of the sub-vehicle use scenarios meets a preset condition as at least one target scene set. That the number of the sub-vehicle use scenarios meets the preset condition includes that the number is greater than a preset quantity threshold. The at least one target scene set is used to adjust the calibration data corresponding to the target intelligent terminal.

[0009] In a possible implementation manner, the obtaining of multiple sub-vehicle use scenarios corresponding to a target vehicle use scenario includes:

[0010] In the target vehicle use scenario, collect function tags respectively corresponding to multiple target functions triggered by the vehicle and arranged in chronological order to obtain the function tag sequence, and monitor the relative position relationship that changes with time between the target intelligent terminal and the vehicle to obtain the Bluetooth positioning sequence;

[0011] Align the occurrence times of the function tag sequence and the Bluetooth positioning sequence to obtain the sub-vehicle use scenario.

[0012] In a possible implementation manner, the collecting, in the target vehicle use scenario, of function tags respectively corresponding to multiple target functions triggered by the vehicle and arranged in chronological order to obtain the function tag sequence includes:

[0013] In the target vehicle use scenario, when the vehicle triggers the target function, obtain the function tag corresponding to the target function and set a time stamp for the function tag;

[0014] Sort the multiple function tags involved in the target vehicle use scenario according to the time stamp to obtain the function tag sequence.

[0015] In a possible implementation manner, the obtaining, in the target vehicle use scenario, of the function tag corresponding to the target function and setting a time stamp for the function tag when the vehicle triggers the target function includes:

[0016] In the getting-on vehicle scenario, when the vehicle is awakened and the vehicle triggers the target function, obtain the function tag corresponding to the target function and set a time stamp for the function tag until the vehicle speed increases from zero to greater than a first preset threshold.

[0017] In a possible implementation manner, the obtaining, in the target vehicle use scenario, of the function tag corresponding to the target function and setting a time stamp for the function tag when the vehicle triggers the target function further includes:

[0018] In the off-vehicle scenario, when the vehicle speed of the vehicle decreases from less than a second preset threshold to zero and the vehicle triggers the target function, obtain a function label corresponding to the target function and set a timestamp for the function label until the vehicle is powered off.

[0019] In a possible implementation manner, in the multiple scenario sets, determining the scenario set in which the number of sub-vehicle usage scenarios meets a preset condition as at least one target scenario set includes:

[0020] Count the number of sub-vehicle usage scenarios corresponding to each of the multiple scenario sets;

[0021] Sort the multiple scenario sets in descending order according to the number of the multiple sub-vehicle usage scenarios to obtain a scenario set sequence;

[0022] In the scenario set sequence, determine the preset number of scenario sets with a forward position as the at least one target scenario set.

[0023] In a second aspect, an embodiment of the present application provides a scenario recognition device, and the device includes:

[0024] An acquisition module, configured to obtain, for a target intelligent terminal, multiple sub-vehicle usage scenarios corresponding to a target vehicle usage scenario, where the target vehicle usage scenario is any one of an on-vehicle scenario and an off-vehicle scenario, the sub-vehicle usage scenarios include a function label sequence and its corresponding Bluetooth positioning sequence, each function label sequence includes multiple function labels arranged in chronological order, the function label is a label corresponding to a function involved in the target vehicle usage scenario, and the Bluetooth positioning sequence represents the relative position relationship between the target intelligent terminal and the vehicle that changes over time in the target vehicle usage scenario;

[0025] A classification module, configured to classify the multiple sub-vehicle usage scenarios according to whether the multiple sub-vehicle usage scenarios are the same to obtain multiple different categories of scenario sets, and each scenario set includes at least one of the sub-vehicle usage scenarios;

[0026] A determination module, configured to, in the multiple scenario sets, determine the scenario set in which the number of sub-vehicle usage scenarios meets a preset condition as at least one target scenario set, where the number of sub-vehicle usage scenarios meeting the preset condition includes that the number is greater than a preset number threshold, and the at least one target scenario set is used to adjust the calibration data corresponding to the target intelligent terminal.

[0027] In a third aspect, an embodiment of the present application provides an electronic device, and the electronic device includes: a processor and a memory storing computer program instructions;

[0028] When the processor executes the computer program instructions, the method in any possible implementation method of the first aspect described above is implemented.

[0029] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method in any possible implementation method of the first aspect described above is implemented.

[0030] In a fifth aspect, an embodiment of the present application provides a vehicle, which includes at least one of the following:

[0031] A scene recognition device as in any embodiment of the second aspect;

[0032] An electronic device as in any embodiment of the third aspect;

[0033] A computer-readable storage medium as in any embodiment of the fourth aspect.

[0034] In the scene recognition method, device, equipment, storage medium and vehicle of the embodiment of the present application, the sub-usage scenarios of the vehicle include the correspondence between the function tag sequence and the Bluetooth positioning sequence. That is, the sub-usage scenarios of the vehicle can indicate in which functional state the vehicle is, the target intelligent terminal (i.e., the target user) is in which area of the vehicle. Therefore, by obtaining multiple sub-usage scenarios corresponding to the target usage scenario for the target intelligent terminal, the usage method of the target user for the vehicle in the target usage scenario can be determined. By classifying multiple sub-usage scenarios according to whether they are the same, multiple different categories of scenario sets are obtained, and in multiple scenario sets, the scenario set in which the number of sub-usage scenarios meets the preset conditions is determined as the target scenario set, that is, in the multiple sub-usage scenarios corresponding to the target terminal, the usage scenario (usage method of the vehicle) used more by the target user is determined, and the usage habits of the target user for the vehicle can be recognized. In this way, by adjusting the calibration data corresponding to the target intelligent terminal based on at least one target scenario set, that is, by performing personalized adjustment on the calibration data according to the usage habits of the target user for the vehicle, the accuracy of the calibration data can be improved, and further the usage experience of the target user for the Bluetooth key of the intelligent terminal can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0036] Figure 1 It is a flowchart of a scene recognition method provided by an embodiment of the present application;

[0037] Figure 2 is a schematic diagram of a boarding scenario provided by an embodiment of the present application;

[0038] Figure 3 is a schematic diagram of another boarding scenario provided by an embodiment of the present application;

[0039] Figure 4 is a schematic diagram of an alighting scenario provided by an embodiment of the present application;

[0040] Figure 5 is a schematic diagram of another alighting scenario provided by an embodiment of the present application;

[0041] Figure 6 is a schematic diagram of the structure of a scenario recognition device provided by an embodiment of the present application;

[0042] Figure 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0043] In order to more clearly understand the above objects, features and advantages of the present application, the solutions of the present application will be further described below. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.

[0044] Many specific details are set forth in the following description in order to provide a thorough understanding of the present application, but the present application may be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of the present application, rather than all embodiments.

[0045] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0046] As described in the background art section, to solve the problems of the prior art, embodiments of the present application provide a scenario recognition method, apparatus, device, storage medium, and vehicle. The scenario recognition method can be used to adjust calibration data corresponding to a Bluetooth key of an intelligent terminal. The scenario recognition method can be executed by a server. Among them, the server can be a cloud server, a vehicle-side server, or a server corresponding to the intelligent terminal, which is not limited herein.

[0047] First, the scenario recognition method provided by the embodiments of the present application will be introduced below.

[0048] Figure 1 The flowchart of a scenario recognition method provided by an embodiment of the present application is shown. As Figure 1 shown, the scenario recognition method provided by the embodiments of the present application includes steps S110 to S130.

[0049] S110, for a target intelligent terminal, obtain multiple sub-usage scenarios corresponding to a target usage scenario, where the target usage scenario is any one of a getting-on vehicle scenario and a getting-off vehicle scenario. The sub-usage scenarios include a function tag sequence and its corresponding Bluetooth positioning sequence. Each function tag sequence includes multiple function tags arranged in chronological order. The function tag is a tag corresponding to a function involved in the target usage scenario. The Bluetooth positioning sequence represents the relative position relationship that changes with time between the target intelligent terminal and the vehicle in the target usage scenario.

[0050] Here, the target intelligent terminal can be an intelligent terminal with a Bluetooth key function. The target intelligent terminal can be, for example, a smart phone and a smart wearable device. Each target intelligent terminal can correspond to a user and a vehicle. That is, there can be a one-to-one correspondence relationship among the target intelligent terminal, the user, and the vehicle. The user corresponding to the target intelligent terminal can be the target user. The vehicle corresponding to the target intelligent terminal can be the target vehicle.

[0051] The target vehicle usage scenario can be any one of the boarding scenario and the alighting scenario. Among them, the boarding scenario can include the scenario between vehicle wake-up and vehicle driving. The boarding scenario can, for example, include processes such as vehicle wake-up, Bluetooth connection, vehicle unlocking, opening of the driver's door, occupancy of the driver's seat, vehicle power-on (ON), switching of the vehicle from D gear to P gear, and vehicle speed from 0 to greater than 10. The alighting scenario can include the scenario between vehicle stop and vehicle power-off (OFF). The alighting scenario can, for example, include processes such as vehicle speed from greater than 10 to 0, switching of the vehicle from P gear to D gear, the vehicle being in the Adaptive Cruise Control (ACC) state, no occupancy of the driver's seat in the vehicle, opening of the driver's door, vehicle locking, and vehicle power-off (OFF). In addition, each target vehicle usage scenario can correspond to multiple sub-vehicle usage scenarios. That is to say, the boarding scenario can correspond to multiple sub-boarding scenarios. The alighting scenario can correspond to multiple sub-alighting scenarios. For example, in the boarding scenario, if the vehicle is unlocked through Bluetooth key passive unlocking, it can be the first sub-boarding scenario. If the vehicle is unlocked through left front door touch unlocking, it can be the second sub-boarding scenario. If the vehicle is unlocked through right front door touch unlocking, it can be the third sub-boarding scenario. Another example is that in the alighting scenario, if the vehicle is locked through Bluetooth key passive locking, it can be the first sub-alighting scenario. If the vehicle is locked through left front door touch locking, it can be the second sub-alighting scenario. If the vehicle is locked through right front door touch locking, it can be the third sub-alighting scenario.

[0052] In addition, the function label can be a label corresponding to the function involved in the target vehicle usage scenario. The correspondence between the function label and the function can be preset by the user. For example, if the function corresponding to the vehicle is unlocking through left front door touch, the function label can be set as left front door touch unlocking. If the function corresponding to the vehicle is unlocking through the tailgate, the function label can be set as tailgate unlocking. Based on this, the function labels can, for example, include vehicle wake-up, Bluetooth connection, tailgate opening, tailgate closing, vehicle power-on, vehicle power-off, occupancy of the driver's seat, opening of the charging port cover, closing of the charging port cover, left front door touch unlocking, left rear door touch unlocking, right front door touch unlocking, right rear door touch unlocking, etc. In a vehicle usage scenario, multiple function labels arranged in chronological order may be involved. Multiple function labels arranged in chronological order can form a function label sequence. The function label sequence can, for example, include multiple function labels such as vehicle wake-up, Bluetooth connection, vehicle unlocking, opening of the driver's door, occupancy of the driver's seat, vehicle power-on, switching of the vehicle from D gear to P gear, and vehicle speed from 0 to greater than 10. That is to say, the function label sequence can include the correspondence between the function label and time (with the function label as the independent variable).

[0053] In addition, the Bluetooth positioning sequence can characterize the relative position relationship that changes over time between the target intelligent terminal and the vehicle in the target vehicle usage scenario. Among them, the vehicle can include multiple vehicle areas. The multiple vehicle areas can include, for example, an unlocking area, the interior of the vehicle, a connection area, a locking area, the rear area of the vehicle, the front area of the vehicle, etc. Among them, the unlocking area can be the unlocking area corresponding to the vehicle. That is, after the target intelligent terminal enters the unlocking area, the vehicle can be automatically unlocked. The locking area is the same as the unlocking area and will not be elaborated in detail here. In addition, the connection area can be an unrecognized area other than areas such as the unlocking area, the interior of the vehicle, the locking area, the rear area of the vehicle, and the front area of the vehicle. Based on this, the relative position relationship can characterize which vehicle area of the vehicle the target intelligent terminal is in. Based on this, for example, the Bluetooth positioning sequence can include when the target intelligent terminal (i.e., the target user) is in which area of the vehicle. That is, the Bluetooth positioning sequence can be the correspondence between the relative position relationship and time. Among them, the Bluetooth positioning sequence can be a continuous sequence or a discrete sequence, which is not limited here. Specifically, the continuous sequence can include the distance relationship (with time as the independent variable) between the target intelligent terminal and the vehicle throughout the target vehicle usage scenario. The discrete sequence can include the correspondence between the vehicle area and time (with the vehicle area as the independent variable).

[0054] In addition, each sub-vehicle usage scenario can include a function label sequence and the Bluetooth positioning sequence corresponding to the function label sequence. Among them, the time of the function label sequence and the Bluetooth positioning sequence can be aligned. Specifically, since the function label sequence can include the correspondence between the function label and time, and the Bluetooth positioning sequence can be the correspondence between the relative position relationship and time, therefore, the sub-vehicle usage scenario can include the correspondence among time, the function label sequence, and the relative position relationship.

[0055] Based on this, in some embodiments, the above S110 can specifically include:

[0056] In the target vehicle usage scenario, collect the function labels corresponding to multiple target functions triggered by the vehicle and arranged in chronological order to obtain a function label sequence, and monitor the relative position relationship that changes over time between the target intelligent terminal and the vehicle to obtain a Bluetooth positioning sequence;

[0057] Align the occurrence times of the function label sequence and the Bluetooth positioning sequence to obtain a sub-vehicle usage scenario.

[0058] Here, in the target driving scenario, on the one hand, after the target intelligent terminal and the vehicle are connected via Bluetooth, the relative position relationship between the target intelligent terminal and the vehicle over time can be monitored via Bluetooth to obtain a Bluetooth positioning sequence. Among them, the form of the Bluetooth positioning sequence can be a line chart showing the change of the relative position relationship over time, or a one-to-one relationship between time periods and vehicle areas, which is not limited here. Among them, the vehicle area can indicate which area of the vehicle the target intelligent terminal is in.

[0059] On the other hand, the target function can be any one of multiple preset functions. The multiple preset functions can be multiple functions that are preset to be possibly triggered by the vehicle in the target driving scenario. For example, the vehicle may be unlocked in the getting-in-the-vehicle scenario. The vehicle may be locked in the getting-out-of-the-vehicle scenario. In addition, the corresponding relationship between the preset function and the function label can also be preset in advance.

[0060] As an example, in the target driving scenario, every time the vehicle triggers a target function, the function label corresponding to the target function can be determined according to the corresponding relationship between the preset function and the function label, and the multiple function labels can be sorted according to the triggering time of the multiple target functions to obtain a function label sequence.

[0061] Specifically, in some embodiments, in the above-mentioned target driving scenario, collecting the function labels corresponding to multiple target functions triggered by the vehicle in chronological order to obtain a function label sequence may specifically include:

[0062] In the target driving scenario, when the vehicle triggers a target function, obtain the function label corresponding to the target function and set a timestamp for the function label;

[0063] Sort the multiple function labels involved in the target driving scenario according to the timestamps to obtain a function label sequence.

[0064] Here, every time the vehicle triggers a target function, a function signal corresponding to the target kinetic energy can be generated. The server can collect the function signal, determine the function label corresponding to the target function according to the corresponding relationship between the function signal and the function label, and set a timestamp for the function label. By sorting the multiple function labels involved in the target driving scenario according to the timestamps, a function label sequence can be obtained.

[0065] In the target driving scenario, after obtaining the function label sequence and the Bluetooth positioning sequence, by aligning the occurrence times of the function label sequence and the Bluetooth positioning sequence, a sub-driving scenario can be obtained.

[0066] Based on this, in order to determine the complete function tag sequence in the vehicle boarding scenario, in some embodiments, in the target vehicle use scenario, when the vehicle triggers the target function, obtaining the function tag corresponding to the target function and setting a timestamp for the function tag may specifically include:

[0067] In the vehicle boarding scenario, when the vehicle is awakened and the vehicle triggers the target function, a function tag corresponding to the target function is obtained and a timestamp is set for the function tag until the vehicle speed increases from zero to greater than a first preset threshold.

[0068] Here, the first preset threshold value may be a preset vehicle speed threshold value. The first preset threshold value may be 10, for example.

[0069] As an example, in a vehicle boarding scenario, after the vehicle is awakened, the logic can be triggered to start collecting function tags until the vehicle speed increases from 0 to greater than 10, and then the collection of function tags stops.

[0070] As a more specific example, in the vehicle boarding scenario, when the vehicle is locked and the power mode of the vehicle is off, if the vehicle is awakened, it is possible to monitor whether the vehicle triggers the target function. If the vehicle triggers the target function, the function tag corresponding to the target function can be obtained and a timestamp can be set for the function tag until the vehicle is powered on, the vehicle is switched from P gear to D gear, and the vehicle speed increases from 0 to greater than 10. It can be determined that the vehicle has started successfully, and then the collection of function tags can be stopped.

[0071] For example, in the vehicle boarding scenario, if the user unlocks the vehicle without any sense through the Bluetooth key of the smart terminal, the multiple function tags collected in chronological order can be displayed as follows: Figure 2 shown.

[0072] For another example, in the vehicle boarding scenario, if the user touches the door handle to unlock the vehicle through the Bluetooth key of the smart terminal, the multiple function tags collected in chronological order can be displayed as follows: Figure 3 shown.

[0073] In this way, by starting to collect function tags after the vehicle is awakened and stopping the collection when the vehicle speed increases from zero to greater than a first preset threshold, a complete function tag sequence in the boarding scene can be determined.

[0074] Based on this, in order to determine the complete function tag sequence in the vehicle leaving scenario, in some embodiments, in the target vehicle use scenario, when the vehicle triggers the target function, the function tag corresponding to the target function is obtained and a timestamp is set for the function tag, which may specifically include:

[0075] In the vehicle-leaving scenario, when the vehicle speed decreases from less than a second preset threshold to zero and the vehicle triggers a target function, obtain the function label corresponding to the target function and set a timestamp for the function label until the vehicle is powered off.

[0076] Here, the second preset threshold can be a preset vehicle speed threshold. The second preset threshold can be equal to, greater than, or less than the first preset threshold, which is not limited here. For example, the second preset threshold can be 10.

[0077] As an example, in the vehicle-leaving scenario, when the vehicle speed decreases from less than the second preset threshold to zero (e.g., from less than 10 to 0), the logic can be triggered to start collecting function labels until the vehicle is powered off and the collection of function labels stops.

[0078] As a more specific example, in the vehicle-leaving scenario, after the vehicle speed decreases from less than 10 to 0, if the D gear is switched to the P gear, it is possible to monitor whether the vehicle triggers a target function. If the vehicle triggers the target function, the function label corresponding to the target function can be obtained and a timestamp can be set for the function label until the vehicle is locked and powered off, indicating that the user has left the vehicle, and then the collection of function labels can be stopped.

[0079] For example, in the vehicle-leaving scenario, if the user performs keyless locking through the intelligent terminal Bluetooth key, the multiple function labels arranged in chronological order can be as Figure 4 shown.

[0080] For another example, in the vehicle-leaving scenario, if the user performs touch door handle locking through the intelligent terminal Bluetooth key, the multiple function labels arranged in chronological order can be as Figure 5 shown.

[0081] In this way, by starting to collect function labels when the vehicle speed decreases from less than the second preset threshold to zero and stopping the collection until the vehicle is powered off, a complete sequence of function labels in the vehicle-leaving scenario can be determined.

[0082] S120. Classify multiple sub-vehicle usage scenarios according to whether they are the same to obtain multiple different categories of scenario sets, and each scenario set includes at least one sub-vehicle usage scenario.

[0083] Here, the sameness of two sub-vehicle usage scenarios can mean that the function label sequences, Bluetooth positioning sequences, and the correspondence relationships between the function label sequences and Bluetooth positioning sequences included in the two sub-vehicle usage scenarios are all the same. If multiple sub-vehicle usage scenarios are the same, then the multiple sub-vehicle usage scenarios can be determined as one category. For example, for the getting-into-vehicle scenario, if there are a total of 100 sub-vehicle usage scenarios, among which 20 sub-vehicle usage scenarios are getting-into-vehicle scenarios corresponding to Bluetooth key passive unlocking, 30 sub-vehicle usage scenarios are getting-into-vehicle scenarios corresponding to left front door touch unlocking, and 50 sub-vehicle usage scenarios are getting-into-vehicle scenarios corresponding to tailgate touch unlocking, then the 100 sub-vehicle usage scenarios can be divided into three scenario sets. One scenario set can be Bluetooth key passive unlocking, corresponding to 20 sub-vehicle usage scenarios, one scenario set can be left front door touch unlocking, corresponding to 30 sub-vehicle usage scenarios, and one scenario set can be tailgate touch unlocking, corresponding to 50 sub-vehicle usage scenarios.

[0084] S130. Among multiple scenario sets, determine the scenario sets whose number of sub-vehicle usage scenarios meets a preset condition as at least one target scenario set. That the number of sub-vehicle usage scenarios meets the preset condition includes that the number is greater than a preset quantity threshold. The at least one target scenario set is used to adjust the calibration data corresponding to the target intelligent terminal.

[0085] Here, the target scenario set can be the scenario set that the target user uses more frequently. For example, among the three scenario sets (including Bluetooth key passive unlocking, left front door touch unlocking, and tailgate touch unlocking) in the above example, the target scenario set can include tailgate touch unlocking. Additionally, the target scenario set can be one or multiple, which is not limited here.

[0086] In addition, that the number of sub-vehicle usage scenarios meets the preset condition can be that the number of sub-vehicle usage scenarios is greater than a preset quantity threshold. That the number of sub-vehicle usage scenarios meets the preset condition can also be that the number ranks among the top several in multiple quantities. Specifically, in some embodiments, the above S130 can specifically include:

[0087] Count the number of sub-vehicle usage scenarios corresponding to multiple scenario sets respectively;

[0088] Sort the multiple scenario sets in descending order according to the number of the multiple sub-vehicle usage scenarios to obtain a scenario set sequence;

[0089] In the scenario set sequence, determine the preset quantity of scenario sets at the front positions as at least one target scenario set.

[0090] Here, the preset quantity can be one or multiple. In the above example, the scenario set sequence can be: tailgate touch unlocking, left front door touch unlocking, and Bluetooth key passive unlocking. If the preset quantity is 2, then the target scenario set can include tailgate touch unlocking and left front door touch unlocking.

[0091] In addition, after determining the number of sub-usage scenarios corresponding to each scenario set, the proportion of each scenario set in the multiple scenario sets can also be determined according to the number. The determined target scenario set may include the proportion of the target scenario set.

[0092] After determining the target scenario set, the initial calibration data corresponding to the target intelligent terminal can be adjusted based on the target scenario set to obtain the target calibration data. Among them, the initial calibration data may be the calibration data corresponding to the model of the target intelligent terminal. The target calibration data may be the calibration data corresponding to the target intelligent terminal.

[0093] In the scenario recognition method of the embodiments of the present application, the sub-usage scenario includes the correspondence between the function tag sequence and the Bluetooth positioning sequence. That is, the sub-usage scenario can indicate in which functional state the vehicle is, and which area of the vehicle the target intelligent terminal (i.e., the target user) is in. Therefore, by obtaining multiple sub-usage scenarios corresponding to the target usage scenario for the target intelligent terminal, the usage method of the target user for the vehicle in the target usage scenario can be determined. By classifying the multiple sub-usage scenarios according to whether they are the same, multiple different categories of scenario sets are obtained, and among the multiple scenario sets, the scenario set in which the number of sub-usage scenarios meets the preset conditions is determined as the target scenario set. That is, in the multiple sub-usage scenarios corresponding to the target terminal, the usage scenario (usage method of the vehicle) used more by the target user is determined, and the usage habit of the target user for the vehicle can be recognized. In this way, by adjusting the calibration data corresponding to the target intelligent terminal based on at least one target scenario set, that is, by performing personalized adjustment on the calibration data according to the usage habit of the target user for the vehicle, the accuracy of the calibration data can be improved, and further the usage experience of the target user for the Bluetooth key of the intelligent terminal can be improved.

[0094] Based on the scenario recognition method provided in the above embodiments, correspondingly, the present application also provides a specific implementation manner of the scenario recognition device. Please refer to the following embodiments.

[0095] As Figure 6 shown, the scenario recognition device 600 provided in the embodiments of the present application includes the following modules:

[0096] An obtaining module 610, configured to obtain, for a target intelligent terminal, multiple sub-usage scenarios corresponding to a target usage scenario, where the target usage scenario is any one of a boarding scenario and a leaving-vehicle scenario, the sub-usage scenario includes a function tag sequence and its corresponding Bluetooth positioning sequence, each function tag sequence includes multiple function tags arranged in chronological order, the function tag is a tag corresponding to a function involved in the target usage scenario, and the Bluetooth positioning sequence represents the relative position relationship between the target intelligent terminal and the vehicle that changes over time in the target usage scenario;

[0097] A classification module 620, configured to classify multiple sub-vehicle usage scenarios according to whether the multiple sub-vehicle usage scenarios are the same, so as to obtain multiple scenario sets of different categories, and each scenario set includes at least one sub-vehicle usage scenario;

[0098] A determination module 630, configured to determine, among the multiple scenario sets, the scenario sets in which the number of sub-vehicle usage scenarios meets a preset condition as at least one target scenario set, where the number of sub-vehicle usage scenarios meeting the preset condition includes being greater than a preset number threshold, and the at least one target scenario set is used to adjust the calibration data corresponding to the target intelligent terminal.

[0099] The above scenario recognition device 600 will be described in detail below, as follows:

[0100] In some embodiments, the acquisition module 610 may specifically include:

[0101] An acquisition sub-module, configured to collect function tags corresponding to multiple target functions triggered by the vehicle in chronological order in a target vehicle usage scenario, so as to obtain a function tag sequence, and monitor the relative position relationship between the target intelligent terminal and the vehicle that changes over time, so as to obtain a Bluetooth positioning sequence;

[0102] An alignment sub-module, configured to align the occurrence times of the function tag sequence and the Bluetooth positioning sequence to obtain a sub-vehicle usage scenario.

[0103] In some embodiments, the acquisition sub-module may specifically include:

[0104] An acquisition unit, configured to, in a target vehicle usage scenario, when the vehicle triggers a target function, acquire a function tag corresponding to the target function and set a timestamp for the function tag;

[0105] A sorting unit, configured to sort multiple function tags involved in the target vehicle usage scenario according to timestamps to obtain a function tag sequence.

[0106] In some embodiments, the acquisition unit may specifically include:

[0107] A first acquisition sub-unit, configured to, in an on-vehicle scenario, when the vehicle is awakened and the vehicle triggers a target function, acquire a function tag corresponding to the target function and set a timestamp for the function tag until the vehicle speed increases from zero to greater than a first preset threshold.

[0108] In some embodiments, the acquisition unit may specifically further include:

[0109] A second acquisition subunit, configured to, in a scenario of getting out of the vehicle, when the vehicle speed of the vehicle decreases from less than a second preset threshold to zero and the vehicle triggers a target function, acquire a function tag corresponding to the target function and set a timestamp for the function tag until the vehicle is powered off.

[0110] In some embodiments, the determining module 630 may specifically include:

[0111] A statistics sub-module, configured to count the number of sub-vehicle usage scenarios corresponding to multiple scenario sets respectively;

[0112] A sorting sub-module, configured to sort the multiple scenario sets in descending order according to the number of sub-vehicle usage scenarios to obtain a scenario set sequence;

[0113] A determining sub-module, configured to determine at least one target scenario set as the preset number of scenario sets with a forward position in the scenario set sequence.

[0114] In the scenario recognition device according to the embodiment of the present application, the sub-vehicle usage scenario includes the correspondence between the function tag sequence and the Bluetooth positioning sequence. That is, the sub-vehicle usage scenario can indicate in which functional state the vehicle is, which area of the vehicle the target smart terminal (i.e., the target user) is in. Therefore, by acquiring multiple sub-vehicle usage scenarios corresponding to the target usage scenario for the target smart terminal, the usage mode of the target user for the vehicle in the target usage scenario can be determined. By classifying the multiple sub-vehicle usage scenarios according to whether they are the same, multiple different categories of scenario sets are obtained, and in the multiple scenario sets, the scenario sets whose number of sub-vehicle usage scenarios meets the preset conditions are determined as target scenario sets, that is, in the multiple sub-vehicle usage scenarios corresponding to the target terminal, the usage scenarios (usage modes of the vehicle) used more by the target user are determined, and the usage habits of the target user for the vehicle can be recognized. In this way, by adjusting the calibration data corresponding to the target smart terminal based on at least one target scenario set, that is, by performing personalized adjustment on the calibration data according to the usage habits of the target user for the vehicle, the accuracy of the calibration data can be improved, and thus the usage experience of the target user for the Bluetooth key of the smart terminal can be improved.

[0115] Based on the scenario recognition method provided in the above embodiments, the embodiment of the present application also provides a specific implementation manner of an electronic device. Figure 7 FIG. shows a schematic diagram of an electronic device 700 provided in the embodiment of the present application.

[0116] The electronic device 700 may include a processor 710 and a memory 720 storing computer program instructions.

[0117] Specifically, the above-mentioned processor 710 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured as one or more integrated circuits for implementing the embodiments of the present application.

[0118] The memory 720 may include a mass storage for data or instructions. By way of example and not limitation, the memory 720 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disc, a magneto-optical disc, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In a suitable case, the memory 720 may include removable or non-removable (or fixed) media. In a suitable case, the memory 720 may be internal or external to the electronic device 700. In a particular embodiment, the memory 720 is a non-volatile solid-state memory.

[0119] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage media device, an optical storage media device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to the first aspect of the present application.

[0120] The processor 710 reads and executes the computer program instructions stored in the memory 720 to implement any one of the scenario recognition methods in the above embodiments.

[0121] In one example, the electronic device 700 may further include a communication interface 730 and a bus 740. As shown, Figure 7 the processor 710, the memory 720, and the communication interface 730 are connected via the bus 740 and complete communication with each other.

[0122] The communication interface 730 is mainly used to implement communication between the modules, devices, units, and / or devices in the embodiments of the present application.

[0123] The bus 740 includes hardware, software, or both, and couples components of an electronic device to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, the bus 740 may include one or more buses. Although embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0124] Exemplarily, the electronic device 700 may be a mobile phone, a tablet computer, a laptop computer, a handheld computer, an in-vehicle electronic device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA), etc.

[0125] The electronic device may execute the scene recognition method in the embodiments of the present application, so as to implement the combination of Figure 1 and Figure 6 the described scene recognition method and apparatus.

[0126] In addition, in combination with the scene recognition method in the above embodiments, an embodiment of the present application may provide a computer-readable storage medium to implement. Computer program instructions are stored on the computer-readable storage medium; when the computer program instructions are executed by a processor, any one of the scene recognition methods in the above embodiments is implemented.

[0127] In addition, an embodiment of the present application further provides a vehicle, which may include at least one of the following:

[0128] The scene recognition device in any one of the embodiments of the second aspect;

[0129] The electronic device in any one of the embodiments of the third aspect;

[0130] The computer-readable storage medium in any one of the embodiments of the fourth aspect. Details are not described herein again.

[0131] It should be clear that the present application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0132] The functional blocks shown in the above-described structural block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present application are programs or code segments for performing the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0133] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0134] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each block in the flowcharts and / or block diagrams, and the combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing devices enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It can also be understood that each block in the block diagrams and / or flowcharts, and the combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0135] As described above, this is only the specific implementation manner of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein. It should be understood that the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application.

Claims

1. A scene recognition method, characterized in that, Including: For a target intelligent terminal, obtain multiple sub-usage scenarios corresponding to the target vehicle usage scenario, where the target vehicle usage scenario is any one of the getting-on vehicle scenario and the getting-off vehicle scenario. Each sub-usage scenario includes a function tag sequence and its corresponding Bluetooth positioning sequence. Each function tag sequence includes multiple function tags arranged in chronological order, and the function tag is a tag corresponding to the function involved in the target vehicle usage scenario. The Bluetooth positioning sequence represents the relative position relationship that changes over time between the target intelligent terminal and the vehicle in the target vehicle usage scenario; Classify the multiple sub-usage scenarios according to whether they are the same to obtain multiple scenario sets of different categories. Each scenario set includes at least one of the sub-usage scenarios; Among the multiple scenario sets, determine the scenario sets in which the number of sub-usage scenarios meets a preset condition as at least one target scenario set. The number of sub-usage scenarios meeting the preset condition includes that the number is greater than a preset number threshold. The at least one target scenario set is used to adjust the calibration data corresponding to the target intelligent terminal.

2. The method according to claim 1, wherein The obtaining of multiple sub-usage scenarios corresponding to the target vehicle usage scenario includes: In the target vehicle usage scenario, collect the function tags corresponding to multiple target functions triggered by the vehicle and arranged in chronological order to obtain the function tag sequence, and monitor the relative position relationship that changes over time between the target intelligent terminal and the vehicle to obtain the Bluetooth positioning sequence; Align the occurrence times of the function tag sequence and the Bluetooth positioning sequence to obtain the sub-usage scenario.

3. The method according to claim 2, wherein The collecting, in the target vehicle usage scenario, of the function tags corresponding to multiple target functions triggered by the vehicle and arranged in chronological order to obtain the function tag sequence includes: In the target vehicle usage scenario, when the vehicle triggers the target function, obtain the function tag corresponding to the target function and set a time stamp for the function tag; Sort the multiple function tags involved in the target vehicle usage scenario according to the time stamp to obtain the function tag sequence.

4. The method according to claim 3, wherein The obtaining, in the target vehicle usage scenario, of the function tag corresponding to the target function and setting a time stamp for the function tag when the vehicle triggers the target function includes: In the getting-on vehicle scenario, when the vehicle is awakened and the vehicle triggers the target function, obtain the function tag corresponding to the target function and set a time stamp for the function tag until the vehicle speed increases from zero to greater than a first preset threshold.

5. The method according to claim 3, wherein The obtaining, in the target vehicle usage scenario, of the function tag corresponding to the target function and setting a time stamp for the function tag when the vehicle triggers the target function further includes: In the getting-off vehicle scenario, when the vehicle speed decreases from less than a second preset threshold to zero and the vehicle triggers the target function, obtain the function tag corresponding to the target function and set a time stamp for the function tag until the vehicle is powered off.

6. The method according to claim 1, wherein Among the multiple scenario sets, determining the scenario sets in which the number of the sub-vehicle usage scenarios meets a preset condition as at least one target scenario set includes: Counting the number of the sub-vehicle usage scenarios respectively corresponding to the multiple scenario sets; Sorting the multiple scenario sets in descending order according to the number of the multiple sub-vehicle usage scenarios to obtain a scenario set sequence; In the scenario set sequence, determining the preset number of scenario sets with a forward position as the at least one target scenario set.

7. A scene recognition device, characterized in that, The device includes: An acquisition module, configured to acquire, for a target intelligent terminal, multiple sub-vehicle usage scenarios corresponding to a target vehicle usage scenario, where the target vehicle usage scenario is any one of a boarding scenario and an alighting scenario, the sub-vehicle usage scenarios include a function tag sequence and its corresponding Bluetooth positioning sequence, each function tag sequence includes multiple function tags arranged in chronological order, the function tags are tags corresponding to functions involved in the target vehicle usage scenario, and the Bluetooth positioning sequence represents the relative position relationship between the target intelligent terminal and the vehicle changing over time in the target vehicle usage scenario; A classification module, configured to classify the multiple sub-vehicle usage scenarios according to whether the multiple sub-vehicle usage scenarios are the same to obtain multiple scenario sets of different categories, and each scenario set includes at least one of the sub-vehicle usage scenarios; A determination module, configured to, among the multiple scenario sets, determine the scenario sets in which the number of the sub-vehicle usage scenarios meets a preset condition as at least one target scenario set, where the number of the sub-vehicle usage scenarios meeting the preset condition includes that the number is greater than a preset number threshold, and the at least one target scenario set is used to adjust the calibration data corresponding to the target intelligent terminal.

8. An electronic device, characterized in that, The electronic device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the scenario recognition method according to any one of claims 1-6 is implemented.

9. A computer-readable storage medium, characterized in that, Computer program instructions are stored on a computer-readable storage medium, and when the computer program instructions are executed by a processor, the scenario recognition method according to any one of claims 1-6 is implemented.

10. A vehicle, characterized in that, Including at least one of the following: The scenario recognition device according to claim 7; The electronic device according to claim 8; The computer-readable storage medium according to claim 9.

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