Behavior data processing method, storage medium, and electronic device

Abstract

The application discloses a behavior data processing method, a storage medium and an electronic device, and relates to the technical field of smart homes. The behavior data processing method comprises the following steps: receiving behavior data generated when a first object uses a smart device, in the case that a data transmission interface between the smart device and a data platform is authenticated; processing the behavior data according to a data processing rule, so as to determine data of different analysis dimensions; receiving a query request sent by the smart device, so as to instruct the data platform to determine target data corresponding to the query request from the data of different analysis dimensions. By using the technical solution, the problem that the processing efficiency of behavior data of the smart device is low is solved.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and more specifically, to a method for processing behavioral data, a storage medium, and an electronic device. Background Technology

[0002] Currently, in the field of smart homes, the level of intelligence of smart home appliances is constantly improving. For example, new smart home appliance products have been developed, launched on the market, and promoted. One such product is a smart water heater with a display screen. However, the display screen on current smart water heaters is only used to display some conventional water heater parameters such as time and temperature. There is no solution in the relevant technology that can provide services to users based on the behavioral data generated when users operate the display screen on the smart water heater.

[0003] Therefore, in related technologies, there is a problem of low processing efficiency for behavioral data of smart devices.

[0004] There is still no effective solution to the problem of low processing efficiency of behavioral data from smart devices in related technologies. Summary of the Invention

[0005] This application provides a method and apparatus for processing behavioral data, a storage medium, and an electronic device to at least solve the problem of low processing efficiency of behavioral data in smart devices in related technologies.

[0006] According to one embodiment of this application, a method for processing behavioral data is provided, comprising: receiving behavioral data generated when a first object uses a smart device, transmitted by the smart device, after the data transmission interface between the smart device and the data platform has been authenticated; processing the behavioral data according to data processing rules to determine data of different analysis dimensions; and receiving a query request sent by the smart device to instruct the data platform to determine target data corresponding to the query request from the data of the different analysis dimensions.

[0007] In an exemplary embodiment, the behavioral data is processed in the data platform according to data processing rules to determine data of different analysis dimensions, including: if the behavioral data includes event codes of behavioral events, determining the event type of the behavioral events in the behavioral data according to the data processing rules; if the event code of the behavioral event corresponds to the device number of the smart device, clustering the behavioral data according to the event type of the behavioral event to obtain multiple behavioral event tables, wherein each of the multiple behavioral event tables corresponds to the same event type, including the event code of the behavioral event under the same event type and the device number of the smart device corresponding to the behavioral event; the event type of the behavioral event includes at least one of the following: custom event, start event, abnormal reporting event, message reminder event, device control event, device binding event, and device unbinding event.

[0008] In one exemplary embodiment, the behavioral data is processed in the data platform according to data processing rules to determine data for different analysis dimensions, including: if the behavioral data includes the time and location of the behavioral event, extracting the time and / or location of the behavioral event from the behavioral data according to the data processing rules; classifying the behavioral data according to the time of the behavioral event to obtain a behavioral event time attribute table, wherein the behavioral event time attribute table contains behavioral data under the time dimension; or, classifying the behavioral data according to the location of the behavioral event to obtain a behavioral event location attribute table, wherein the behavioral event time attribute table contains behavioral data under the location dimension; or, classifying the behavioral data according to the time and location of the behavioral event to obtain a behavioral event attribute table, wherein the behavioral event attribute table contains behavioral data under different analysis dimensions.

[0009] In an exemplary embodiment, determining the event type of a behavioral event in the behavioral data according to the data processing rules includes: if it is determined that the behavioral data includes device information corresponding to the behavioral event, determining the first startup time of the smart device based on the device information corresponding to the behavioral event; if it is determined that the time of the behavioral event is consistent with the first startup time of the smart device, determining the event type of the behavioral event of the smart device as a startup event.

[0010] In an exemplary embodiment, determining the event type of a behavioral event in the behavioral data according to the data processing rules includes: when it is determined that the behavioral data includes device information corresponding to the behavioral event and identity information of a first object corresponding to the behavioral event, determining the device number, device binding time, and device unbinding time of the smart device based on the device information corresponding to the behavioral event; determining the event type of the behavioral event as a device binding event based on the device number of the smart device, the device binding time, and the identity information of the first object corresponding to the behavioral event; and when it is determined that the difference between the device unbinding time and the device binding time is greater than a second preset value, determining the event type of the behavioral event as a device unbinding event based on the device number of the smart device and the device unbinding time.

[0011] In an exemplary embodiment, determining the event type of a behavioral event in the behavioral data according to the data processing rules includes: determining device touch data based on the device information corresponding to the behavioral event when the behavioral data includes device information corresponding to the behavioral event; determining the event type of the smart device's behavioral event as a device control event when the behavioral location of the behavioral event is located within a target area and the number of touches in the device touch data is greater than a third preset value, wherein the target area includes the smart device; and determining the event type of the smart device's behavioral event as a device control event when the time of the behavioral event is within the working time period of the smart device and the touch time in the device touch data exceeds a fourth preset value.

[0012] In an exemplary embodiment, determining the event type of a behavioral event in the behavioral data according to the data processing rules includes: when the behavioral data includes an event code of the behavioral event, the time of the behavioral event, the location of the behavioral event, and the device information corresponding to the behavioral event, determining the operating status and device number of the smart device based on the device information corresponding to the behavioral event; determining the behavioral event information of the behavioral event based on the event code of the behavioral event, the time of the behavioral event, and the location of the behavioral event; when the operating status of the smart device is abnormal, obtaining the device number of the smart device with the abnormal operating status; and determining the event type of the behavioral event as an abnormal reporting event based on the behavioral event information of the behavioral event and the device number of the smart device with the abnormal operating status.

[0013] According to another embodiment of this application, a behavioral data processing apparatus is also provided, comprising: a receiving module, configured to receive behavioral data generated when a first object uses a smart device, transmitted by the smart device, after authentication of the data transmission interface between the smart device and the data platform; a processing module, configured to process the behavioral data according to data processing rules to determine data of different analysis dimensions; and a determining module, configured to receive a query request sent by the smart device to instruct the data platform to determine target data corresponding to the query request from the data of the different analysis dimensions.

[0014] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes an event code of a behavior event, determine the event type of the behavior event in the behavior data according to the data processing rules; when determining that the event code of the behavior event corresponds to a device number of the smart device, cluster the behavior data according to the event type of the behavior event to obtain multiple behavior event tables, wherein each behavior event table corresponds to the same event type, including the event code of the behavior event under the same event type and the device number of the smart device corresponding to the behavior event; the event type of the behavior event includes at least one of the following: custom event, start event, exception reporting event, message reminder event, device control event, device binding event, and device unbinding event.

[0015] In an exemplary embodiment, the processing module is further configured to, when determining that the behavioral data includes the time of the behavioral event and the location of the behavioral event, extract the time and / or the location of the behavioral event from the behavioral data according to the data processing rules; classify the behavioral data according to the time of the behavioral event to obtain a behavioral event time attribute table, wherein the behavioral event time attribute table contains behavioral data under the time dimension; or, classify the behavioral data according to the location of the behavioral event to obtain a behavioral event location attribute table, wherein the behavioral event time attribute table contains behavioral data under the location dimension; or, classify the behavioral data according to the time and location of the behavioral event to obtain a behavioral event attribute table, wherein the behavioral event attribute table contains behavioral data under different analysis dimensions.

[0016] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes device information corresponding to the behavior event, determine the first startup time of the smart device based on the device information corresponding to the behavior event; and, when determining that the time of the behavior event is consistent with the first startup time of the smart device, determine that the event type of the behavior event of the smart device is a startup event.

[0017] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes device information corresponding to the behavior event and identity information of the first object corresponding to the behavior event, determine the device number, device binding time, and device unbinding time of the smart device based on the device information corresponding to the behavior event; determine the event type of the behavior event as a device binding event based on the device number of the smart device, the device binding time, and the identity information of the first object corresponding to the behavior event; and determine the event type of the behavior event as a device unbinding event based on the device number of the smart device and the device unbinding time when determining that the difference between the device unbinding time and the device binding time is greater than a second preset value.

[0018] In an exemplary embodiment, the processing module is further configured to: determine device touch data based on the device information corresponding to the behavior event when the behavior data includes device information corresponding to the behavior event; determine the event type of the behavior event of the smart device as a device control event when the behavior location of the behavior event is located within a target area and the number of touches in the device touch data is greater than a third preset value, wherein the target area includes the smart device; and determine the event type of the behavior event of the smart device as a device control event when the time of the behavior event is within the working time period of the smart device and the touch time in the device touch data exceeds a fourth preset value.

[0019] In an exemplary embodiment, the processing module is further configured to: determine the operating status and device number of the smart device based on the device information corresponding to the behavior event when the behavior data includes the event code of the behavior event, the time of the behavior event, the behavior location of the behavior event, and the device information corresponding to the behavior event; determine the behavior event information of the behavior event based on the event code of the behavior event, the time of the behavior event, and the behavior location of the behavior event; obtain the device number of the smart device with an abnormal operating status when the operating status of the smart device is abnormal; and determine the event type of the behavior event as an abnormal reporting event based on the behavior event information of the behavior event and the device number of the smart device with an abnormal operating status.

[0020] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, and the computer program is configured to execute the above-described method for processing behavioral data when it is run.

[0021] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for processing behavioral data through the computer program.

[0022] In this embodiment, when the data transmission interface between the smart device and the data platform is authenticated, the system receives behavioral data generated by a first object using the smart device; processes the behavioral data according to data processing rules to determine data in different analysis dimensions; receives a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data in the different analysis dimensions; by adopting the above technical solution, the problem of low processing efficiency of behavioral data of smart devices is solved, thereby improving the processing efficiency of behavioral data of smart devices. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the hardware environment for a method of processing behavioral data according to an embodiment of this application;

[0026] Figure 2 This is a flowchart of a method for processing behavioral data according to an embodiment of this application;

[0027] Figure 3 This is a flowchart illustrating a method for processing behavioral data according to an embodiment of this application;

[0028] Figure 4 This is a structural block diagram (a) of a behavioral data processing apparatus according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram (II) of a behavioral data processing apparatus according to an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] According to one aspect of the embodiments of this application, a method for processing behavioral data is provided. This method is widely applicable to whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, and intelligence house ecosystems. Optionally, in this embodiment, the above-mentioned behavioral data processing method can be applied to, for example... Figure 1 The hardware environment shown consists of terminal device 102 and server 104. For example... Figure 1 As shown, server 104 is connected to terminal device 102 via a network and can be used to provide services (such as application services) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data processing services for server 104.

[0033] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal device 102 may not be limited to PC, mobile phone, tablet computer, smart air conditioner, smart range hood, smart refrigerator, smart oven, smart stove, smart washing machine, smart water heater, smart washing equipment, smart dishwasher, smart projector, smart TV, smart clothes rack, smart curtains, smart audio-visual equipment, smart socket, smart speaker, smart speaker box, smart fresh air equipment, smart kitchen and bathroom equipment, smart bathroom equipment, smart robot vacuum cleaner, smart window cleaning robot, smart mopping robot, smart air purifier, smart steam oven, smart microwave oven, smart water heater, smart air purifier, smart water dispenser, smart door lock, etc.

[0034] This embodiment provides a method for processing behavioral data, applied to the aforementioned computer terminal. Figure 2 This is a flowchart of a method for processing behavioral data according to an embodiment of this application, which includes the following steps:

[0035] Step S202: If the data transmission interface between the smart device and the data platform is authenticated, receive the behavioral data generated when the first object uses the smart device.

[0036] It should be noted that the first object mentioned above can be a person or a robot, and this application does not limit it in this way.

[0037] It is understood that the aforementioned smart devices may include smart home appliances, such as smart water heaters.

[0038] Step S204: Process the behavioral data according to the data processing rules to determine the data for different analysis dimensions;

[0039] Step S206: Receive a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data of different analysis dimensions.

[0040] Through the above steps, with the data transmission interface between the smart device and the data platform authenticated, the system receives behavioral data generated when a first object uses the smart device; processes the behavioral data according to data processing rules to determine data in different analysis dimensions; and receives a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data in the different analysis dimensions. This solves the problem of low processing efficiency of behavioral data of smart devices in related technologies, thereby improving the processing efficiency of behavioral data of smart devices.

[0041] In one embodiment, when a smart device is used as the execution side, the following technical solution can be implemented: acquiring behavioral data generated when a first object uses the smart device; if the data transmission interface is authenticated, transmitting the behavioral data to a data platform through the data transmission interface to instruct the data platform to process the behavioral data according to data processing rules to determine data of different analysis dimensions, wherein the data transmission interface is the transmission interface between the smart device and the data platform; sending a query request to the data platform to instruct the data platform to determine the target data corresponding to the query request from the data of different analysis dimensions.

[0042] In one embodiment, the authentication process of the data transmission interface between the smart device and the data platform is as follows: obtain the actual transmission parameters input in the data transmission interface, determine whether the actual transmission parameters can be found in the pre-stored transmission parameter library, and if the actual transmission parameters can be found in the pre-stored transmission parameter library, confirm that the data transmission interface has passed authentication. At this time, the data transmission interface can be used to transmit behavioral data generated by the smart device.

[0043] The pre-stored transmission parameter library contains transmission parameters that can identify different data users and the user products associated with those users. For example, the pre-stored transmission parameter library includes application parameters appid and appkey. The appid corresponds to different data users and can be used to identify them. The appkey corresponds to the user products associated with a data user and can be used to identify those products.

[0044] In an exemplary embodiment, to better understand how the behavioral data is processed according to data processing rules in the data platform in step S204 above to determine data of different analysis dimensions, if it is determined that the behavioral data includes event codes of behavioral events, the event type of the behavioral events in the behavioral data can be determined according to the data processing rules; if it is determined that the event code of the behavioral event corresponds to the device number of the smart device, the behavioral data is clustered according to the event type of the behavioral event to obtain multiple behavioral event tables, wherein each of the multiple behavioral event tables corresponds to the same event type, including the event code of the behavioral event under the same event type and the device number of the smart device corresponding to the behavioral event; the event type of the behavioral event includes at least one of the following: custom event, start event, abnormal reporting event, message reminder event, device control event, device binding event, and device unbinding event.

[0045] In one exemplary embodiment, a technical solution is also provided for processing the behavioral data according to data processing rules in the data platform to determine data of different analytical dimensions. Specifically: when it is determined that the behavioral data includes the time and location of the behavioral event, the time and / or location of the behavioral event in the behavioral data are extracted according to the data processing rules; the behavioral data is classified according to the time of the behavioral event to obtain a behavioral event time attribute table, wherein the behavioral event time attribute table contains behavioral data under the time dimension; or, the behavioral data is classified according to the location of the behavioral event to obtain a behavioral event location attribute table, wherein the behavioral event time attribute table contains behavioral data under the location dimension; or, the behavioral data is classified according to the time and location of the behavioral event to obtain a behavioral event attribute table, wherein the behavioral event attribute table contains behavioral data under different analytical dimensions.

[0046] In one exemplary embodiment, various schemes are provided for determining the event type of behavioral events in the behavioral data according to the data processing rules, including:

[0047] Option 1: If the behavior data includes device information corresponding to the behavior event, determine the first startup time of the smart device based on the device information corresponding to the behavior event; if the time of the behavior event is consistent with the first startup time of the smart device, determine the event type of the behavior event of the smart device as a startup event.

[0048] Furthermore, in one embodiment, after determining the startup event, the number of consecutive startups of the smart device is determined based on the device information corresponding to the behavioral event. If the number of consecutive startups of the smart device is greater than a first preset value, the event type of the behavioral event of the smart device is determined to be a consecutive startup event. Here, the number of consecutive startups represents the number of times the startup program of the smart device is executed consecutively. In one embodiment, if the number of consecutive startups of the smart device is 2, and the first preset value is 0, the event type of the behavioral event of the smart device is determined to be a consecutive startup event.

[0049] Option 2: If the behavior data includes device information corresponding to the behavior event and identity information of the first object corresponding to the behavior event, determine the device number, device binding time, and device unbinding time of the smart device based on the device information corresponding to the behavior event; determine the event type of the behavior event as a device binding event based on the device number, the device binding time, and the identity information of the first object corresponding to the behavior event; if the difference between the device unbinding time and the device binding time is greater than a second preset value, determine the event type of the behavior event as a device unbinding event based on the device number and the device unbinding time of the smart device.

[0050] In one embodiment, if the difference between the device unbinding time and the device binding time is determined to be 2 hours, and the second preset value is 10 minutes, then the event type of the behavior event is determined to be a device unbinding event.

[0051] In one embodiment, if the difference between the device unbinding time and the device binding time is less than a second preset value, it is determined that the device has not been successfully unbound. In this case, it is impossible to determine the event type of the behavior event as a device unbinding event based on the device number of the smart device and the device unbinding time.

[0052] Option 3: If the behavior data includes device information corresponding to the behavior event, determine the device touch data based on the device information corresponding to the behavior event; if the behavior location of the behavior event is located within the target area, and the number of touches in the device touch data is greater than a third preset value, determine the event type of the smart device's behavior event as a device control event, wherein the target area includes the smart device; if the time of the behavior event is within the working time period of the smart device, and the touch time in the device touch data exceeds a fourth preset value, determine the event type of the smart device's behavior event as a device control event.

[0053] It should be noted that the target area mentioned above can be, for example, the area corresponding to the device location in the device information mentioned above. In one embodiment, the device in the device information mentioned above is a refrigerator, and the refrigerator is placed in the kitchen. The behavior location of the behavior event is determined to be the kitchen. If the number of touches is 4 and the third preset value is 1, then the event type of the behavior event of the smart device is determined to be a device control event. The device control event is, for example, adjusting the temperature of the refrigerator compartment.

[0054] In one embodiment, if the time of the behavioral event is determined to be 3:30 PM on April 16, 2022, the working time of the smart device is from 6:00 AM to 11:00 PM on April 16, 2022, the touch time in the device touch data is 10 seconds, and the fourth preset value is 5 seconds, then the event type of the behavioral event of the smart device is determined to be a device control event.

[0055] Option 4: When the behavior data includes the event code of the behavior event, the time of the behavior event, the location of the behavior event, and the device information corresponding to the behavior event, determine the operating status and device number of the smart device based on the device information corresponding to the behavior event; determine the behavior event information of the behavior event based on the event code of the behavior event, the time of the behavior event, and the location of the behavior event; if the operating status of the smart device is abnormal, obtain the device number of the smart device with the abnormal operating status; determine the event type of the behavior event as an abnormal reporting event based on the behavior event information of the behavior event and the device number of the smart device with the abnormal operating status.

[0056] The following description, in conjunction with optional embodiments, illustrates the implementation process of the above-mentioned behavioral data processing, but is not intended to limit the technical solutions of the embodiments of this application.

[0057] Figure 3 This is a flowchart illustrating a method for processing behavioral data according to an embodiment of this application, such as... Figure 3 As shown, in this embodiment, a water heater with a display screen is taken as an example of a smart device, and the screen data generated by the user using the water heater's display screen is taken as the behavioral data generated when the first object of this application uses the smart device. A behavioral data collection scheme and application scenario are provided. By embedding data points on the water heater's display screen, the collected and reported data points are transmitted to a data platform for storage via a common POST interface (equivalent to the aforementioned data transmission interface). The data platform can be used to analyze the embedded data, and the analysis results can be applied to the business analysis field (i.e.,...). Figure 3 (Business data analysis services in data application scenarios).

[0058] The water heater's display screen uses a Linux-based operating system (referred to as the Linux display system), which is divided into a kernel layer and an application layer. Data tracking is implemented at the application layer, while the data platform resides at the kernel layer. Although the Linux display system differs from iOS and Android applications, it still performs data tracking at the application layer, and the transmission interfaces are generally compatible. The water heater's display screen can show information such as weather, time, city, water temperature, and control parameters.

[0059] The data collected includes user ID data, splash screen data, standby time data, device ID data, and data from other custom events.

[0060] Among these features, the data from the embedded data points can be transmitted to the data platform via the WIFI module built into the water heater itself.

[0061] Among them, such as Figure 3 As shown, data application scenarios can include: 1. Using on-screen event tracking data to count the number of users and page views corresponding to independent on-screen event tracking events. 2. Starting from the needs of business stakeholders, counting the number of users and page views of independent on-screen event tracking events according to different dimensions, including but not limited to date, city, application version, and channel. 3. Making the collected on-screen event tracking data available to relevant business departments through a data platform for real-time and refined data analysis and operation based on constantly changing business needs.

[0062] To better understand the process of processing the aforementioned behavioral data, we will continue to use a water heater as an example of a smart device, and explain it from the following aspects:

[0063] I. Functions of Smart Water Heaters via Display Panel:

[0064] In this embodiment, the behavioral data is collected from the display screen on the smart water heater. The display screen shows the water temperature, the user's location (city), the current weather conditions in the user's city (e.g., cloudy), and the user's current time (e.g., 15:30). The water heater can be controlled via the control area of ​​the display screen.

[0065] II. Control Module of Smart Water Heater:

[0066] The control module of a smart water heater is a core component of smart home appliances, used to control the Wi-Fi module of the smart water heater. The Wi-Fi module enables data interaction between the smart water heater and the data platform in a smart device manner.

[0067] III. Data from embedded points of smart water heaters:

[0068] By embedding data points in real time on the display screen of a smart water heater, and using the collected data points for analysis, it is possible to count the number of users using and browsing the display screen, thereby improving the user experience and refining product design.

[0069] In one embodiment, the data can be broken down according to the needs of the business party and the final statistical analysis indicators or data analysis objectives, down to the fields of the raw data and the field values ​​that need to be reported. These field values ​​include the event value reported by the launch screen embedding, the event code value, the event occurrence time, the user ID, the device ID, and other custom business events (i.e.,...). Figure 3 Custom events, etc.

[0070] IV. Data transmission from embedded points in smart water heaters:

[0071] In this embodiment, the embedded data uploaded from the client is transmitted to the data platform via a general POST interface. Before transmitting the data, the general POST interface needs to be authenticated. After successful authentication, a data processing request can be submitted to the big data platform, including submitting forms, uploading files, and uploading embedded data.

[0072] V. Data Storage: Upload the data tracking data to the data platform for storage, for example, in the log table.

[0073] 6. Process the data collected into different analytical dimensions: For example, it may include: custom data, startup data, anomaly reporting data, message reminder data, device control data, device binding data, device unbinding data, as well as time attribute data and location attribute data.

[0074] Among them, startup data corresponds to startup events, including on-screen startup data, such as initial on-screen startup and custom startup events. Anomaly reporting data corresponds to anomaly reporting events, such as reports of errors or crashes. Message notification data corresponds to message notification events, such as messages about overheating or low water pressure. Device control data corresponds to device control events, representing the user's control process of the water heater, such as the user controlling the water heater to turn it on via touch or voice interaction. Device binding data and device unbinding data correspond to device binding events and device unbinding events, respectively. Device binding events indicate that the user has bound the water heater to a frequently used device, and device unbinding events indicate that the user has unbound the water heater to an infrequently used device. Custom data corresponds to custom events, which can be understood as events defined by the user.

[0075] Additionally, the time attribute data represents the duration of different events. For example, if the launch event is the launch of the weather page, then the duration of the user's browsing of the weather page can be understood as the duration of the weather page launch event. The location attribute data, on the other hand, represents the current location information of the water heater.

[0076] VII. Data application and analysis scenarios include KPI assessment BI dashboards, business data analysis dashboards or business data analysis reports, and open data services.

[0077] The KPI assessment BI dashboard is used to track the number of users and page views for independent screen-based event tracking. The business data analysis dashboard or reports can be designed based on business needs, tracking the number of users and page views for independent screen-based event tracking broken down by different dimensions, including but not limited to date, city, application version, and channel. The data open service means that the collected screen-based event tracking data will be made available to relevant business departments through the data platform, allowing business colleagues to conduct more refined operational analysis.

[0078] Through the above embodiments, a solution for implementing screen-based data embedding, data collection, and data application has been realized. This allows for a better understanding of the market size, user preferences, and user behavior of smart home appliances with screens, guiding subsequent product development, product upgrades, and market positioning. Ultimately, this enables more functions for the display screen on smart water heaters.

[0079] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0080] Figure 4 This is a structural block diagram (a) of a behavioral data processing apparatus according to an embodiment of this application. Figure 4 As shown, it includes:

[0081] The receiving module 42 is used to receive behavioral data generated by the first object when using the smart device, when the data transmission interface between the smart device and the data platform is authenticated.

[0082] It should be noted that the first object mentioned above can be a person or a robot, and this application does not limit it in this way.

[0083] It is understood that the aforementioned smart devices may include smart home appliances, such as smart water heaters.

[0084] Processing module 44 is used to process the behavioral data according to data processing rules to determine data in different analysis dimensions;

[0085] The determination module 46 is used to receive the query request sent by the smart device, so as to instruct the data platform to determine the target data corresponding to the query request from the data of different analysis dimensions.

[0086] Through the aforementioned device, when the data transmission interface between the smart device and the data platform is authenticated, the device receives behavioral data generated by a first object using the smart device; processes the behavioral data according to data processing rules to determine data in different analysis dimensions; and receives a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data in the different analysis dimensions. This solves the problem of low processing efficiency of behavioral data of smart devices in related technologies, thereby improving the processing efficiency of behavioral data of smart devices.

[0087] In one embodiment, when a smart device is used as the execution side, the following technical solution can be implemented: acquiring behavioral data generated when a first object uses the smart device; if the data transmission interface is authenticated, transmitting the behavioral data to a data platform through the data transmission interface to instruct the data platform to process the behavioral data according to data processing rules to determine data of different analysis dimensions, wherein the data transmission interface is the transmission interface between the smart device and the data platform; sending a query request to the data platform to instruct the data platform to determine the target data corresponding to the query request from the data of different analysis dimensions.

[0088] In one embodiment, the authentication process of the data transmission interface between the smart device and the data platform is as follows: obtain the actual transmission parameters input in the data transmission interface, determine whether the actual transmission parameters can be found in the pre-stored transmission parameter library, and if the actual transmission parameters can be found in the pre-stored transmission parameter library, confirm that the data transmission interface has passed authentication. At this time, the data transmission interface can be used to transmit behavioral data generated by the smart device.

[0089] The pre-stored transmission parameter library contains transmission parameters that can identify different data users and the user products associated with those users. For example, the pre-stored transmission parameter library includes application parameters appid and appkey. The appid corresponds to different data users and can be used to identify them. The appkey corresponds to the user products associated with a data user and can be used to identify those products.

[0090] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes an event code of a behavior event, determine the event type of the behavior event in the behavior data according to the data processing rules; when determining that the event code of the behavior event corresponds to a device number of the smart device, cluster the behavior data according to the event type of the behavior event to obtain multiple behavior event tables, wherein each behavior event table corresponds to the same event type, including the event code of the behavior event under the same event type and the device number of the smart device corresponding to the behavior event; the event type of the behavior event includes at least one of the following: custom event, start event, exception reporting event, message reminder event, device control event, device binding event, and device unbinding event.

[0091] In an exemplary embodiment, the processing module is further configured to, when determining that the behavioral data includes the time of the behavioral event and the location of the behavioral event, extract the time and / or the location of the behavioral event from the behavioral data according to the data processing rules; classify the behavioral data according to the time of the behavioral event to obtain a behavioral event time attribute table, wherein the behavioral event time attribute table contains behavioral data under the time dimension; or, classify the behavioral data according to the location of the behavioral event to obtain a behavioral event location attribute table, wherein the behavioral event time attribute table contains behavioral data under the location dimension; or, classify the behavioral data according to the time and location of the behavioral event to obtain a behavioral event attribute table, wherein the behavioral event attribute table contains behavioral data under different analysis dimensions.

[0092] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes device information corresponding to the behavior event, determine the first startup time of the smart device based on the device information corresponding to the behavior event; and, when determining that the time of the behavior event is consistent with the first startup time of the smart device, determine that the event type of the behavior event of the smart device is a startup event.

[0093] Furthermore, the aforementioned processing module is also used to, after determining a startup event, determine the number of consecutive startups of the smart device based on the device information corresponding to the behavioral event, and if the number of consecutive startups of the smart device is greater than a first preset value, determine the event type of the behavioral event of the smart device as a consecutive startup event. Here, the number of consecutive startups represents the number of times the smart device's startup program is executed consecutively. In one embodiment, if the number of consecutive startups of the smart device is 2, and the first preset value is 0, then the event type of the behavioral event of the smart device is determined to be a consecutive startup event.

[0094] In an exemplary embodiment, the processing module is further configured to, when determining that the behavior data includes device information corresponding to the behavior event and identity information of the first object corresponding to the behavior event, determine the device number, device binding time, and device unbinding time of the smart device based on the device information corresponding to the behavior event; determine the event type of the behavior event as a device binding event based on the device number of the smart device, the device binding time, and the identity information of the first object corresponding to the behavior event; and determine the event type of the behavior event as a device unbinding event based on the device number of the smart device and the device unbinding time when determining that the difference between the device unbinding time and the device binding time is greater than a second preset value.

[0095] In one embodiment, if the difference between the device unbinding time and the device binding time is determined to be 2 hours, and the second preset value is 10 minutes, then the event type of the behavior event is determined to be a device unbinding event.

[0096] In one embodiment, if the difference between the device unbinding time and the device binding time is less than a second preset value, it is determined that the device has not been successfully unbound. In this case, it is impossible to determine the event type of the behavior event as a device unbinding event based on the device number of the smart device and the device unbinding time.

[0097] In an exemplary embodiment, the processing module is further configured to: determine device touch data based on the device information corresponding to the behavior event when the behavior data includes device information corresponding to the behavior event; determine the event type of the behavior event of the smart device as a device control event when the behavior location of the behavior event is located within a target area and the number of touches in the device touch data is greater than a third preset value, wherein the target area includes the smart device; and determine the event type of the behavior event of the smart device as a device control event when the time of the behavior event is within the working time period of the smart device and the touch time in the device touch data exceeds a fourth preset value.

[0098] It should be noted that the target area mentioned above can be, for example, the area corresponding to the device location in the device information mentioned above. In one embodiment, the device in the device information mentioned above is a refrigerator, and the refrigerator is placed in the kitchen. The behavior location of the behavior event is determined to be the kitchen. If the number of touches is 4 and the third preset value is 1, then the event type of the behavior event of the smart device is determined to be a device control event. The device control event is, for example, adjusting the temperature of the refrigerator compartment.

[0099] In one embodiment, if the time of the behavioral event is determined to be 3:30 PM on April 16, 2022, the working time of the smart device is from 6:00 AM to 11:00 PM on April 16, 2022, the touch time in the device touch data is 10 seconds, and the fourth preset value is 5 seconds, then the event type of the behavioral event of the smart device is determined to be a device control event.

[0100] Figure 5 This is a structural block diagram (II) of a behavioral data processing apparatus according to an embodiment of this application. Figure 5 As shown, the above processing module includes a reporting unit 52, used to: determine the operating status and device number of the smart device based on the device information corresponding to the behavior event when the behavior data includes the event code of the behavior event, the time of the behavior event, the behavior location of the behavior event, and the behavior location of the behavior event; determine the behavior event information of the behavior event based on the event code of the behavior event, the time of the behavior event, and the behavior location of the behavior event; obtain the device number of the smart device with an abnormal operating status when the operating status of the smart device is abnormal; and determine the event type of the behavior event as an abnormal reporting event based on the behavior event information of the behavior event and the device number of the smart device with an abnormal operating status.

[0101] Embodiments of this application also provide a storage medium including a stored program, wherein the program executes any of the methods described above when it is run.

[0102] Optionally, in this embodiment, the storage medium may be configured to store program code for performing the following steps:

[0103] S1, under the condition that the data transmission interface between the smart device and the data platform is authenticated, receives the behavioral data generated by the first object when using the smart device;

[0104] S2, Process the behavioral data according to the data processing rules to determine the data for different analysis dimensions;

[0105] S3, receive a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data of the different analysis dimensions.

[0106] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0107] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0108] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0109] S1, under the condition that the data transmission interface between the smart device and the data platform is authenticated, receives the behavioral data generated by the first object when using the smart device;

[0110] S2, Process the behavioral data according to the data processing rules to determine the data for different analysis dimensions;

[0111] S3, receive a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data of the different analysis dimensions.

[0112] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0113] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0114] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0115] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for processing behavioral data, characterized in that, include: When the data transmission interface between the smart device and the data platform is authenticated, the system receives behavioral data generated by the first object when using the smart device. The behavioral data is processed according to data processing rules in the data platform to determine data in different analytical dimensions; Receive a query request sent by the smart device to instruct the data platform to determine the target data corresponding to the query request from the data of the different analysis dimensions; The process of processing the behavioral data according to data processing rules in the data platform to determine data in different analytical dimensions includes: If the behavior data includes an event code of a behavior event, the event type of the behavior event in the behavior data is determined according to the data processing rules. If the event code of the behavior event corresponds to the device number of the smart device, the behavior data is clustered according to the event type of the behavior event to obtain multiple behavior event tables. Each behavior event table corresponds to the same event type, including the event code of the behavior event under the same event type and the device number of the smart device corresponding to the behavior event. The step of determining the event type of the behavioral event in the behavioral data according to the data processing rules includes: When the behavior data includes the event code of the behavior event, the time of the behavior event, the location of the behavior event, and the device information corresponding to the behavior event, the operating status and device number of the smart device are determined based on the device information corresponding to the behavior event; the behavior event information of the behavior event is determined based on the event code of the behavior event, the time of the behavior event, and the location of the behavior event; if the operating status of the smart device is abnormal, the device number of the smart device with the abnormal operating status is obtained; the event type of the behavior event is determined to be an abnormal reporting event based on the behavior event information of the behavior event and the device number of the smart device with the abnormal operating status.

2. The method for processing behavioral data according to claim 1, characterized in that, The behavioral data is processed according to data processing rules in the data platform to determine data in different analytical dimensions, including: If it is determined that the behavioral data includes the time of the behavioral event and the location of the behavioral event, the time of the behavioral event and / or the location of the behavioral event in the behavioral data are extracted according to the data processing rules. The behavioral data is categorized according to the time of the behavioral events to obtain a behavioral event time attribute table, wherein the behavioral event time attribute table contains behavioral data in the time dimension; Alternatively, the behavioral data can be categorized according to the location of the behavioral events to obtain a behavioral event location attribute table, wherein the behavioral event time attribute table is behavioral data under the location dimension; Alternatively, the behavioral data can be categorized according to the time and location of the behavioral events to obtain a behavioral event attribute table, wherein the behavioral event attribute table contains behavioral data under different analysis dimensions.

3. The method for processing behavioral data according to claim 1, characterized in that, The event types of the behavioral events include at least one of the following: custom event, startup event, exception reporting event, message notification event, device control event, device binding event, and device unbinding event.

4. The method for processing behavioral data according to claim 3, characterized in that, The event type of the behavioral event in the behavioral data is determined according to the data processing rules, including: If the behavioral data includes device information corresponding to the behavioral event, the first startup time of the smart device is determined based on the device information corresponding to the behavioral event. If the time of the behavioral event is determined to be consistent with the first startup time of the smart device, the event type of the behavioral event of the smart device is determined to be a startup event.

5. The method for processing behavioral data according to claim 3, characterized in that, The event type of the behavioral event in the behavioral data is determined according to the data processing rules, including: If the behavior data includes device information corresponding to the behavior event and identity information of the first object corresponding to the behavior event, the device number, device binding time, and device unbinding time of the smart device are determined based on the device information corresponding to the behavior event. The event type of the behavior event is determined to be a device binding event based on the device number of the smart device, the device binding time, the identity information of the first object corresponding to the behavior event; If the difference between the device unbinding time and the device binding time is greater than a second preset value, the event type of the behavior event is determined to be a device unbinding event based on the device number of the smart device and the device unbinding time.

6. The method for processing behavioral data according to claim 3, characterized in that, The event type of the behavioral event in the behavioral data is determined according to the data processing rules, including: If it is determined that the behavior data includes device information corresponding to the behavior event, device touch data is determined based on the device information corresponding to the behavior event; If the location of the behavioral event is determined to be within the target area, and the number of touches in the device touch data is greater than a third preset value, the event type of the behavioral event of the smart device is determined to be a device control event, wherein the target area includes the smart device; If the time of the behavioral event is determined to be within the working time period of the smart device, and the touch time in the device touch data exceeds a fourth preset value, then the event type of the behavioral event of the smart device is determined to be a device control event.

7. A device for processing behavioral data, characterized in that, include: The receiving module is used to receive behavioral data generated by the first object when using the smart device, after the data transmission interface between the smart device and the data platform has been authenticated. The processing module is used to process the behavioral data in the data platform according to data processing rules to determine data in different analysis dimensions; The determination module is used to receive a query request sent by the smart device, so as to instruct the data platform to determine the target data corresponding to the query request from the data of different analysis dimensions; The processing module is further configured to: when it is determined that the behavior data includes an event code of a behavior event, determine the event type of the behavior event in the behavior data according to the data processing rules; when it is determined that the event code of the behavior event corresponds to the device number of the smart device, cluster the behavior data according to the event type of the behavior event to obtain multiple behavior event tables, wherein each behavior event table corresponds to the same event type, including the event code of the behavior event under the same event type and the device number of the smart device corresponding to the behavior event; The processing module is further configured to: determine the operating status and device number of the smart device based on the device information corresponding to the behavior event when the behavior data includes the event code of the behavior event, the time of the behavior event, the behavior location of the behavior event, and the behavior location of the behavior event; determine the behavior event information of the behavior event based on the event code of the behavior event, the time of the behavior event, and the behavior location of the behavior event; obtain the device number of the smart device with an abnormal operating status when the operating status of the smart device is abnormal; and determine the event type of the behavior event as an abnormal reporting event based on the behavior event information of the behavior event and the device number of the smart device with an abnormal operating status.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method described in any one of claims 1 to 6.

9. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method described in any one of claims 1 to 6 through the computer program.

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