Communication terminal control method, electronic equipment and storage medium

Abstract

The invention relates to the technical field of communication terminal control, and particularly provides a communication terminal control method, which comprises the following steps: in response to a remote control mode, initializing a grid map of a current area; acquiring human body track data in the current area in a first preset time period; determining track grid map information based on the grid map and the human body track data; determining the activeness of the current user based on the track grid map information; and based on the activity degree of the current user, the temperature of the air conditioner is controlled, and therefore the limitation of fixed temperature setting of a traditional air conditioner is broken through, intelligent matching of temperature adjustment and the real-time state of the human body is achieved, and the temperature control precision and the use comfort are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication terminal control, and in particular to a communication terminal control method, an electronic device and a storage medium. BACKGROUND

[0002] The temperature control of the current mainstream air conditioner is still mainly in the traditional mode, which depends on the user to manually set a fixed temperature value or to switch the temperature through a simple timing function, and it is difficult to adaptively adjust according to the dynamic changes of the environment and the actual needs of the human body. For example, when the outdoor temperature suddenly rises or drops, the indoor solar intensity changes, the number of people increases or decreases, or the activity state changes (such as from static to motion, from wakefulness to sleep), the air conditioner cannot perceive these variables in real time and still operates according to the initial set temperature, resulting in frequent fluctuations in indoor temperature, such as overcooling or overheating. In winter, the local temperature may suddenly drop due to the temporary opening of doors and windows, but the heating cannot be adjusted in time. In summer, the room temperature may exceed the comfortable range due to the increase in solar radiation in the afternoon, but the adjustment is delayed. This non-intelligent control logic not only affects the comfort of the human body, but also causes energy waste: to maintain the set temperature, the air conditioner is often in a high-frequency start-stop or full-load operation state, especially in scenes with large diurnal temperature differences or complex environments, and the proportion of invalid energy consumption increases significantly. At the same time, the user needs to manually adjust the temperature setting repeatedly to adapt to the changes in demand, which is tedious and difficult to accurately match the dynamic perception of the human body to the temperature (such as the gradual increase in the temperature suitable for the human body during sleep over time), further reducing the user experience. Although some air conditioners have introduced basic temperature sensors for simple feedback adjustment, due to limitations such as sensor accuracy, single sensing dimension (only monitoring the local temperature at the return air inlet, which cannot reflect the room-wide temperature difference), and simple algorithm logic, it is still difficult to achieve truly intelligent temperature control. SUMMARY

[0003] An object of the present application is to provide a communication terminal control method to at least solve the problem of how to accurately control the temperature of an air conditioner.

[0004] To achieve the above object, some embodiments of the present application provide the following aspects: In a first aspect, some embodiments of the present application further provide a communication terminal control method, which comprises: initializing a grid map of a current area in response to a remote control mode; obtaining human trajectory data in the current area within a first preset time period; determining trajectory grid map information based on the grid map and the human trajectory data; determining the activity level of a current user based on the trajectory grid map information; controlling the temperature of an air conditioner based on the activity level of the current user.

[0005] In a second aspect, some embodiments of the present application further provide a communication terminal control system, the system comprising: a first obtaining module configured to initialize a grid map of a current area in response to a remote control mode; a second obtaining module configured to obtain human trajectory data in the current area within a first preset time period; a first data processing module configured to determine trajectory grid map information based on the grid map and the human trajectory data; a second data processing module configured to determine an activity level of a current user based on the trajectory grid map information; a third data processing module configured to control a temperature of an air conditioner based on the activity level of the current user.

[0006] In a third aspect, some embodiments of the present application further provide an electronic device, comprising: one or more processors; and a memory storing computer program instructions, the computer program instructions, when executed, causing the processor to perform the steps of the method as described above.

[0007] In a fourth aspect, some embodiments of the present application further provide a computer readable medium having stored thereon computer program instructions executable by a processor to implement the method as described above.

[0008] Compared with the related art, in the scheme provided by the embodiment of the application, a communication terminal control method, when the air conditioner is in a remote control mode, the system first initializes a grid map of the current area, divides the physical space into grid units with millimeter-level precision, constructs a digital space coordinate system, and provides a space reference for subsequent accurate positioning of the human body trajectory. Subsequently, the fusion perception technology of the infrared array sensor and the millimeter wave radar is used to continuously collect human body trajectory data within a first preset time period (such as 30 minutes), including dynamic information such as the entering time, the staying time and the moving path of the user in each grid. Based on the initialized grid map and the collected human body trajectory data, the system further generates trajectory grid map information - the map marks the activity frequency, the cumulative staying time and the moving speed of each grid, realizes the visualization and quantitative representation of the user behavior trajectory. On this basis, the activity level of the current user is calculated in combination with the trajectory distribution characteristics (such as the grid activity density and the moving speed gradient), which accurately reflects the human body metabolic heat production level (such as the high activity level corresponding to the exercise state and the low activity level corresponding to the resting state). Finally, the system dynamically adjusts the air conditioner temperature according to the activity level: when the activity level is high, the set temperature is automatically lowered by 1-2℃ to offset the additional heat production, and when the activity level is low, the temperature is raised by 0.5-1℃ to adapt to the human body heat dissipation demand, while ensuring that the temperature adjustment is always within the user's preset comfortable interval. Through this closed-loop control logic, the application breaks through the limitation of the fixed temperature setting of the traditional air conditioner, realizes the intelligent matching of the temperature adjustment and the real-time state of the human body, and significantly improves the temperature control accuracy and the use comfort. BRIEF DESCRIPTION OF DRAWINGS

[0009] One or more embodiments are illustrated by way of example in the figures that are part of this disclosure and which are illustrative, but not restrictive, of the present embodiments, wherein elements having the same reference number designates like elements throughout the various figures. The figures of the drawings are not necessarily to scale, with emphasis being placed upon illustrating the principles of the embodiments.

[0010] Figure 1 A flowchart of a communication terminal control method provided by the embodiment of the application; Figure 2 A structure diagram of a communication terminal control system according to the embodiment of the application; Figure 3 An exemplary structure diagram of a processor and a memory according to the application; Figure 4 An exemplary structure diagram of an electronic device according to the application. DETAILED DESCRIPTION

[0011] To make the purposes, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0012] Reference is made to the accompanying drawings Figure 1 , Figure 1 A flowchart of a communication terminal control method provided by the embodiments of the present application is shown. As shown in FIG. 1, the communication terminal control method in the embodiments of the present application mainly includes the following steps. Figure 1 initializing a grid map of a current area in response to a remote control mode; acquiring human trajectory data in the current area within a first preset time period; determining trajectory grid map information based on the grid map and the human trajectory data; determining an activity level of a current user based on the trajectory grid map information; controlling a temperature of an air conditioner based on the activity level of the current user.

[0013] In the embodiments, when the air conditioner is in the remote control mode, the system first initializes the grid map of the current area, divides the physical space into millimeter-level grid units, constructs a digital space coordinate system, and provides a spatial reference for subsequent accurate positioning of the human trajectory. Subsequently, the fusion perception technology of the infrared array sensor and the millimeter wave radar is used to continuously collect the human trajectory data within a first preset time period (such as 30 minutes), including the entering time, the staying time, and the moving path of the user in each grid, and other dynamic information. Based on the initialized grid map and the collected human trajectory data, the system further generates the trajectory grid map information, which marks the activity frequency, the cumulative staying time, and the moving rate of each grid, realizes the visualization and quantitative representation of the user behavior trajectory, and calculates the activity level of the current user in combination with the trajectory distribution characteristics (such as the grid activity density and the moving rate gradient), accurately reflects the human metabolic heat production level (such as the high activity level corresponding to the exercise state and the low activity level corresponding to the resting state). Finally, the system dynamically adjusts the air conditioner temperature according to the activity level: automatically lowers the set temperature by 1-2℃ to offset the additional heat production when the activity level is high, and raises the temperature by 0.5-1℃ to adapt to the human heat dissipation demand when the activity level is low, while ensuring that the temperature adjustment is always within the user's preset comfortable interval. Through this closed-loop control logic, the present application breaks through the limitation of the fixed temperature setting of the traditional air conditioner, realizes the intelligent matching of the temperature adjustment and the real-time state of the human body, and significantly improves the temperature control accuracy and the use comfort. ​

[0014] In one embodiment, based on the trajectory grid map information, the activity level of the current user is determined, comprising: Based on the trajectory grid map information, the spatially weighted activity frequency entropy, the dynamic stay duration distribution, the moving rate gradient, and the behavior fluctuation coefficient are determined. Based on the spatially weighted activity frequency entropy, the dynamic stay duration distribution, the moving rate gradient, and the behavior fluctuation coefficient, the activity level of the current user is determined. The spatially weighted activity frequency entropy is used to represent the activity frequency distribution characteristics of the user in different grids, the dynamic stay duration distribution is used to represent the dynamic change of the stay time of the user in the grid, the moving rate gradient is used to represent the speed change characteristics of the user moving between grids, and the behavior fluctuation coefficient is used to represent the overall volatility of the activity frequency and the stay duration of the user.

[0015] In this embodiment, the activity level of the current user is determined based on the trajectory grid map information, and the specific process is as follows: first, the core feature parameters are extracted from the trajectory grid map information, and the spatially weighted activity frequency entropy, the dynamic stay duration distribution, the moving rate gradient, and the behavior fluctuation coefficient are obtained through quantitative calculation. Among them, the spatially weighted activity frequency entropy combines the grid weight coefficient and the last activity time difference, and quantifies the activity distribution uniformity of the user in different grids through the entropy value algorithm; the dynamic stay duration distribution is based on the deviation of the grid stay duration and the average stay duration, and reflects the dynamic change law of the user staying in each grid; the moving rate gradient uses the center distance between adjacent grids and the moving rate between grids to calculate the rate change rate to represent the dynamic characteristics of the user movement; the behavior fluctuation coefficient is obtained by multiplying the standard deviation of the grid activity frequency and the stay duration, and reflects the overall volatility of the user behavior. Subsequently, the above four parameters are nonlinearly mapped through a weighted fusion model, and the spatial distribution characteristics, the time allocation law, the moving dynamic attribute, and the behavior fluctuation characteristics are integrated into a unified quantitative index, and finally the activity level of the current user is determined to accurately represent the behavior state of the user.

[0016] In one embodiment, the trajectory grid map information includes the center distance between adjacent grids, the total number of grids, the grid weight coefficient, the grid activity frequency, the grid stay duration, the last activity time difference, the moving rate between grids, the frequency proportion, the average stay duration, and the rate gradient.

[0017] In this embodiment, the trajectory grid map information covers the basic spatial parameters such as the center distance between adjacent grids, the total number of grids, and the grid weight coefficient, and also includes dynamic behavior data such as the grid activity frequency, the stay duration, the last activity time difference, and the moving rate between grids, and further includes derived indicators such as the frequency proportion, the average stay duration, and the rate gradient, which comprehensively quantifies the spatial behavior characteristics of the user.

[0018] In one embodiment, the spatially weighted activity frequency entropy and the dynamic dwell time distribution are determined by the following formula:

[0019]

[0020]

[0021]

[0022] wherein, is the spatially weighted activity frequency entropy, is the total number of active activity grids in the trajectory grid map, is the activity frequency proportion of the i-th grid, is the cumulative activity frequency of the user entering the i-th grid, is the weight coefficient of the i-th grid, is the time decay factor, is the time difference between the last activity of the i-th grid and the current time, is the average dwell time of all activity grids, is the cumulative dwell time of the user in the i-th grid, is the dynamic dwell time distribution, is the time utility coefficient, is the total duration of the first preset time period.

[0023] In the present embodiment, is the total number of active activity grids in the trajectory grid map (positive integer), is the activity frequency proportion of the i-th grid (positive integer, unit: times), is the cumulative activity frequency of the user entering the i-th grid, is the weight coefficient of the i-th grid (1.2 for the core activity area, 0.8 for the edge area, no unit), is the time decay factor (value 0.01-0.1, controls the weight of recent activities, no unit), is the time difference between the last activity of the i-th grid and the current time (unit: minutes), is the average dwell time of all activity grids, is the cumulative dwell time of the user in the i-th grid, is the dynamic dwell time distribution, is the time utility coefficient, is the total duration of the first preset time period (i.e. the statistical period, unit: minutes), i is the grid number (from 1 to n, representing the i-th activity grid).

[0024] In one embodiment, the moving rate gradient and the behavior fluctuation coefficient are determined by the following formula:

[0025]

[0026]

[0027]

[0028] wherein, is the moving rate gradient, m is the total number of moving segments of the user between grids, is the rate gradient of the jth moving segment, is the rate of the jth moving segment, is the average rate of all moving segments, is the behavior fluctuation coefficient, is the standard deviation of the activity frequency, is the standard deviation of the stay duration, is the benchmark fluctuation threshold.

[0029] In the present embodiment, is the moving rate gradient, m is the total number of moving segments of the user between grids, is the rate gradient of the jth moving segment, is the rate of the jth moving segment, is the average rate of all moving segments, is the behavior fluctuation coefficient, is the standard deviation of the activity frequency, is the standard deviation of the stay duration (reflecting the dispersion degree of the stay time distribution, unit: minute), is the benchmark fluctuation threshold fixed value 0.5, used for normalizing the fluctuation coefficient, unitless), j is the moving segment number (from 1 to m, representing the jth adjacent grid moving segment).

[0030] In one embodiment, the activity level of the current user is determined by the following formula:

[0031] wherein, is the activity level of the current user, is the first feature weight coefficient, is the second feature weight coefficient, is the third feature weight coefficient, is the fourth feature weight coefficient.

[0032] In the present embodiment, is the first feature weight coefficient, is a third feature weight coefficient, is a fourth feature weight coefficient, is a fourth feature weight coefficient, optimized by a gradient descent algorithm, satisfying a sum of 2, respectively corresponding to a spatially weighted activity frequency entropy (reflecting the activity frequency distribution characteristics of the user in different grids), a dynamic stay duration distribution (reflecting the dynamic change of the user's stay time in the grid), a moving rate gradient (reflecting the speed change characteristics of the user moving between grids), a behavior fluctuation coefficient (reflecting the overall volatility of the user's activity frequency and stay duration), and the current user's activity level (output value, range 0~1, the higher the value, the higher the activity level).

[0033] In one embodiment, based on the current user's activity level, the temperature of the air conditioner is controlled, further comprising: determining the user's activity state based on the current user's activity level; controlling the temperature of the air conditioner based on the user's activity state; wherein the user's activity state includes low activity state, medium activity and high activity.

[0034] In this embodiment, when controlling the temperature of the air conditioner based on the current user's activity level, it also contains the progressive logic of state classification and precise adjustment: first, the activity level is quantized to the user's activity state by mapping the pre-set threshold, which is specifically divided into low activity state, medium activity state and high activity state - among them, the activity level ≤0.3 is determined as low activity state (corresponding to low metabolism state such as sitting and sleeping), the activity level 0.3~0.6 interval is medium activity state (corresponding to normal metabolism state such as daily walking and light work), and the activity level ≥0.6 is high activity state (corresponding to high metabolism state such as exercise and high-intensity activity). After determining the activity state of the user, the system will match the differentiated temperature control strategy: for low activity state, the air conditioner temperature needs to be adjusted to the upper limit of the comfort interval (such as from 26℃ to 27℃ in summer, from 20℃ to 21℃ in winter) due to less body heat production and increased temperature sensitivity, while reducing the wind speed to reduce air disturbance; in the medium activity state, the baseline comfortable temperature (25~26℃ in summer and 19~20℃ in winter) is adopted, and the wind speed is kept stable to adapt to the body's normal metabolic heat production; in the high activity state, due to the sudden increase of body heat production, the temperature needs to be dynamically adjusted to the lower limit of the comfort interval (summer down to 24~25℃, winter maintain 19℃ but improve heating efficiency), and 0.5~1℃ compensation adjustment is added according to the deviation of the environment temperature. In addition, the system will monitor the fluctuation amplitude of the activity level in real time, and if the activity level switches across states within 10 minutes (such as from high activity to medium activity), the smooth transition mechanism will be started to gradually adjust to the target temperature at a rate of 0.5℃ / min, avoiding sudden temperature changes that cause discomfort, and finally achieving precise adaptation of the activity state and temperature control strategy.

[0035] From a functional perspective, modern smart air conditioners can function as communication terminals in certain scenarios, but this needs to be viewed rationally in conjunction with their core positioning: Smart air conditioners can interact with mobile apps and smart home systems via network modules (such as Wi-Fi and Bluetooth) to receive control commands and provide feedback on operating status, possessing communication capabilities for "information transmission and reception." In this interaction, it does indeed act as a "node in the communication link," functionally resembling a "terminal device." However, it's crucial to clarify that this communication capability is an auxiliary means serving its core function (environmental regulation), rather than having "establishing and maintaining a communication link" as its core design goal (the core of traditional communication terminals like mobile phones and walkie-talkies is communication). Therefore, smart air conditioners are more like "environmental control terminals with communication functions," rather than "communication terminals" in the strict sense—their "communication attributes" are added through intelligent features, not their essential positioning. In short, from a broad perspective of "possessing information interaction capabilities," smart air conditioners can be considered a special, non-core communication-related terminal.

[0036] See appendix Figure 2 , Figure 2 This is a schematic diagram of the structure of a communication terminal control system according to an embodiment of this application. Figure 2 As shown, the communication terminal control system in this embodiment of the invention mainly includes: The first acquisition module 200 is configured to initialize a grid map of the current area in response to remote control mode; The second acquisition module 202 is configured to acquire human trajectory data within the current area during a first preset time period; The first data processing module 204 is configured to determine trajectory grid map information based on the grid map and the human trajectory data. The second data processing module 206 is configured to determine the current user's activity level based on the trajectory grid map information; The third data processing module 208 is configured to control the temperature of the air conditioner based on the activity level of the current user.

[0037] In one embodiment of the present invention, the second data processing module 206 is configured to perform the following operations: Determining the current user's activity level based on the trajectory grid map information includes: Based on the trajectory grid map information, the spatial weighted activity frequency entropy, dynamic dwell time distribution, movement rate gradient, and behavior fluctuation coefficient are determined. The activity level of the current user is determined based on the spatially weighted activity frequency entropy, dynamic dwell time distribution, movement rate gradient, and behavior fluctuation coefficient. The spatially weighted activity frequency entropy is used to represent activity frequency distribution characteristics of the user in different grids, the dynamic stay duration distribution is used to represent dynamic changes of stay duration of the user in the grid, the moving speed gradient is used to represent speed change characteristics of the user in the inter-grid movement, and the behavior fluctuation coefficient is used to represent overall fluctuation of the activity frequency and the stay duration of the user.

[0038] In an embodiment of the present application, the trajectory grid map information includes a center distance of adjacent grids, a total number of grids, a grid weight coefficient, a grid activity frequency, a grid stay duration, a last activity time difference, an inter-grid moving speed, a frequency proportion, an average stay duration and a speed gradient.

[0039] In an embodiment of the present application, the spatially weighted activity frequency entropy and the dynamic stay duration distribution are determined by the following formula:

[0040]

[0041]

[0042]

[0043] In the formula, is the spatially weighted activity frequency entropy, is a total number of effective activity grids in the trajectory grid map, is an activity frequency proportion of the i-th grid, is a cumulative activity frequency of the user entering the i-th grid, is a weight coefficient of the i-th grid, is a time decay factor, is a time difference between the last activity of the i-th grid and the current time, is an average stay duration of all activity grids, is a cumulative stay duration of the user in the i-th grid, is the dynamic stay duration distribution, is a time utility coefficient, is a total duration of a first preset time period.

[0044] In an embodiment of the present application, the moving speed gradient and the behavior fluctuation coefficient are determined by the following formula:

[0045]

[0046]

[0047]

[0048] wherein, is the moving rate gradient, m is the total number of moving segments of the user between grids, is the moving rate gradient of the jth segment, is the moving rate of the jth segment, is the average moving rate of all moving segments, is the behavior fluctuation coefficient, is the standard deviation of the activity frequency, is the standard deviation of the stay duration, is the reference fluctuation threshold.

[0049] In an embodiment of the present application, the activity level of the current user is determined by the following formula:

[0050] wherein, is the activity level of the current user, is the first feature weight coefficient, is the second feature weight coefficient, is the third feature weight coefficient, is the fourth feature weight coefficient.

[0051] In an embodiment of the present application, the third data processing module 208 is configured to perform the following operations: determining the activity state of the user based on the activity level of the current user; controlling the temperature of the air conditioner based on the activity state of the user; wherein, the activity state of the user includes a low activity level state, a medium activity level and a high activity level.

[0052] The step division of the above various methods is only for the purpose of clear description. In implementation, one step can be combined or some steps can be split and decomposed into multiple steps, as long as the same logical relationship is included, which is within the protection scope of the present patent. Adding insignificant modifications or introducing insignificant designs in the algorithm or flow, but not changing the core design of the algorithm and flow, are within the protection scope of the present patent.

[0053] It is not difficult to find that the present embodiment is a method embodiment corresponding to the system embodiment, and the present embodiment can be implemented in cooperation with the system embodiment. The related technical details mentioned in the system embodiment are still valid in the present embodiment. In order to reduce repetition, they will not be described here. Correspondingly, the related technical details mentioned in the present embodiment can also be applied in the system embodiment.

[0054] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problem proposed in this application; however, this does not mean that other units are absent from this embodiment.

[0055] Furthermore, some embodiments of this application also provide an electronic device. The electronic device can be various forms of digital computer, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, etc. The electronic device can also be various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices.

[0056] The electronic device includes: one or more processors; and a memory storing computer program instructions that, when executed, cause the processor to perform the steps of the methods provided in any one or more of the above embodiments. Figure 3 An exemplary structural diagram of the electronic device is disclosed. For example... Figure 3 As shown, the electronic device includes one or more processors 1101, a memory 1102, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components are interconnected via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some other embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple electronic devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). The components, their connections and relationships, and their functions shown herein are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0057] The electronic device may further include an input device 1103 and an output device 1104. The processor 1101, memory 1102, input device 1103, and output device 1104 may be connected via a bus or other means. Figure 4 Taking the example of a connection between China and Israel via a bus.

[0058] The input device 1103 can receive input of a number or character information, and generate a key signal corresponding to a user command input with respect to a function or setting of the electronic device, for example, a touch screen, a key pad, a mouse, a track ball, a touch pad, a jog wheel, one or more mouse buttons, a track ball, a joystick, etc. The output device 1104 can include a display device, a sub-lit (for example, an LED), a haptic feedback device (for example, a vibration motor), etc. The display device can include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, and a plasma display. In some embodiments, the display device can be a touch screen.

[0059] To provide the interaction with the user, the electronic device can be a computer. The computer has a display device (for example, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user, and a keyboard and a pointing device (for example, a mouse or a track ball) through which the user can provide input to the computer. Other kinds of devices can also be used for providing the interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (for example, visual feedback, auditory feedback, or tactile feedback), and the input from the user can be received in any form (including voice input, speech input, or tactile input).

[0060] In the embodiments of the present application, the computer program / instruction is stored on the computer readable medium, and the computer program / instruction is executed by the processor to implement the steps of the method provided by any one or more of the embodiments. The computer readable medium can be included in the electronic device described in the above embodiments; or can exist separately without being assembled into the device. The computer readable medium carries one or more computer readable instructions.

[0061] The memory 1102 can be used as a non-transitory computer readable storage medium for storing non-transitory software programs, non-transitory computer executable programs, and modules. The processor 1101 executes various functions and data processing of the server by running the non-transitory software programs, instructions, and modules stored in the memory 1102, so as to implement the program instructions / modules corresponding to the method provided by any one or more of the embodiments in the present application.

[0062] The memory 1102 can include a program region and a data region, where the program region can store an operating system, an application required by at least one function, and the like, and the data region can store data created according to use of the electronic device, and the like. In addition, the memory 1102 can include a high-speed random access memory, and can further include a non-transitory memory such as at least one of a magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1102 can optionally include a memory disposed remotely with respect to the processor 1101, and these remote memories can be connected to the electronic device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0063] It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable medium may, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or apparatus.

[0064] The computer-readable medium includes permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0065] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0066] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. For example, the embodiments can be implemented by an application specific integrated circuit (ASIC), a general purpose computer or any other similar hardware device. In some embodiments, the software programs of the embodiments can be executed by a processor to implement the above steps or functions. Similarly, the software programs (including related data structures) of the embodiments can be stored in a computer readable recording medium, such as a RAM memory, a magnetic or optical drive or a floppy disk and the like. In addition, some steps or functions of the embodiments can be implemented by hardware, such as a circuit cooperating with a processor to perform the steps or functions.

[0067] The computer program product provided by the embodiments of the present application includes one or more computer programs / instructions, which, when executed by a processor, generate all or part of the processes or functions described in the embodiments of the present application. The computer can be a general purpose computer, a special purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center and the like integrated with one or more available media. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)) and the like.

[0068] The computer program product of the present application can be a computer program embedded in a computer readable medium such as hard disk, CD, DVD, flash memory, etc. The computer readable medium can be directly readable by a computer or the computer can read the computer readable medium through a drive unit. The computer program product can also be a downloadable computer program transmitted via a network, e.g., the Internet, a local area network, etc. The downloadable computer program can be transmitted via a wired network or a wireless network, e.g., a satellite network, a cellular network, etc. The computer program product can also be a computer program product that is directly loadable into the internal memory of the computer.

[0069] The scope of the present application is defined by the appended claims rather than the description preceding it, therefore, all changes and modifications that come within the meaning and range of equivalents of the claims are to be embraced by the application. No feature of the application is considered critical unless the claims specifically and expressly identify it as essential. Furthermore, it is intended that whenever claims recite “comprising,” “including,” “containing,” or “having” particular elements or integers, it should be interpreted as including those elements or integers equivalents thereof as well. Likewise, the terms “first,” “second,” etc., are used merely as labels, and are not intended to impose numerical requirements on their objects. No language in the specification should be construed as indicating any non-claimed element as essential.

[0070] The above description is only specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be defined by the protection scope of the claims, and the above-described embodiments should be regarded as exemplary and non-limiting.

Claims

1. A communication terminal control method characterized by comprising: The method comprises: in response to a remote control mode, initializing a grid map of a current area; acquiring human trajectory data in the current area within a first preset time period; based on the grid map and the human trajectory data, determining trajectory grid map information; based on the trajectory grid map information, determining the activity level of the current user; based on the activity level of the current user, controlling the temperature of the air conditioner.

2. The method of claim 1, wherein, The determination of the activity level of the current user based on the trajectory grid map information comprises: based on the trajectory grid map information, determining a spatially weighted activity frequency entropy, a dynamic stay duration distribution, a moving speed gradient, and a behavior fluctuation coefficient; based on the spatially weighted activity frequency entropy, the dynamic stay duration distribution, the moving speed gradient, and the behavior fluctuation coefficient, determining the activity level of the current user; wherein the spatially weighted activity frequency entropy is used to represent the activity frequency distribution characteristics of the user in different grids, the dynamic stay duration distribution is used to represent the dynamic changes of the stay time of the user in the grid, the moving speed gradient is used to represent the speed change characteristics of the user moving between grids, and the behavior fluctuation coefficient is used to represent the overall volatility of the activity frequency and the stay duration of the user.

3. The method of claim 2, wherein, The trajectory grid map information comprises a center distance between adjacent grids, a total number of grids, a grid weight coefficient, a grid activity frequency, a grid stay duration, a last activity time difference, a moving speed between grids, a frequency proportion, an average stay duration, and a speed gradient.

4. The method of claim 3, wherein, The spatially weighted activity frequency entropy and the dynamic stay duration distribution are determined by the following formula: ； ； ； ； In the formula, is the spatially weighted active frequency entropy, is the total number of active grids in the trajectory grid map, is the active frequency proportion of the i-th grid, is the cumulative active frequency of the user entering the i-th grid, is the weight coefficient of the i-th grid, is the time decay factor, is the time difference between the last activity of the i-th grid and the current time, is the average stay duration of all active grids, is the cumulative stay duration of the user in the i-th grid, is the dynamic stay duration distribution, is the time utility coefficient, is the total duration of the first preset time period.

5. The method of claim 4, wherein, The moving speed gradient and the behavior fluctuation coefficient are determined by the following formula: ； ； ； ； wherein, is the moving rate gradient, m is the total number of moving segments of the user between grids, is the moving rate gradient of the jth segment, is the moving rate of the jth segment, is the average moving rate of all moving segments, is the behavior fluctuation coefficient, is the standard deviation of the activity frequency, is the standard deviation of the stay duration, is the benchmark fluctuation threshold.

6. The method of claim 5, wherein, The activity level of the current user is determined by the following formula: ； In the formula, is the activity of the current user, is the first feature weight coefficient, is the second feature weight coefficient, is the third feature weight coefficient, is the fourth feature weight coefficient.

7. The method of claim 6, wherein, The control of the temperature of the air conditioner based on the activity level of the current user further comprises: based on the activity level of the current user, determining the activity state of the user; based on the activity state of the user, controlling the temperature of the air conditioner; wherein the activity state of the user comprises a low activity level state, a medium activity level, and a high activity level.

8. A communication terminal control system characterized by comprising: The system applied to the method of any one of claims 1-7 comprises: a first acquisition module configured to initialize a grid map of a current area in response to a remote control mode; a second acquisition module configured to acquire human trajectory data in the current area within a first preset time period; a first data processing module configured to determine trajectory grid map information based on the grid map and the human trajectory data; a second data processing module configured to determine the activity level of the current user based on the trajectory grid map information; a third data processing module configured to control the temperature of the air conditioner based on the activity level of the current user.

9. An electronic device, comprising: The device comprises: one or more processors; and a memory storing computer program instructions that, when executed, cause the processor to perform the method of any one of claims 1-7.

10. A computer readable medium characterized by A computer program instruction is stored thereon, which can be executed by a processor to implement the method of any one of claims 1-7.

Images