Smart home air conditioner adaptive control method, storage medium and electronic device

Abstract

This invention relates to the field of smart home technology, and provides a smart home air conditioner adaptive control method, storage medium, and electronic device. The smart home air conditioner adaptive control method includes: receiving location and individual characteristic data of users with ultra-wideband tags, determined by a cloud server based on data reported by ultra-wideband base stations; the number of ultra-wideband base stations is at least four, used to receive signals emitted by devices with ultra-wideband tags; and adaptively determining the operating state of the air conditioner based on the location and individual characteristic data. This application solves the problem in the prior art that smart home air conditioners cannot accurately adapt to user needs and the environment, and realizes air conditioner adaptive control based on user location and individual characteristics.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and in particular to a smart home air conditioner adaptive control method, storage medium and electronic device. Background Technology

[0002] With the rapid development of IoT technology, smart homes have become an important part of modern families. Smart home systems integrate various smart devices, such as smart lighting, smart security, and smart appliances, to provide users with a more convenient, comfortable, and energy-efficient living environment. Among these, smart air conditioning, as a crucial component of the smart home system, directly impacts the user's living experience. Traditional air conditioning control methods largely rely on manual operation by the user and cannot achieve automatic adjustment based on the user's location and activity level, which significantly limits the overall intelligence level of the smart home system.

[0003] Currently, the control methods for smart home air conditioners have made some progress. One common approach is to use ultrasonic radar positioning technology to sense the location of a person and adjust the air conditioner's operating parameters accordingly. This technology uses an ultrasonic transmitter to emit ultrasonic signals, a receiver to receive the reflected signals, and calculates the distance between the person and the air conditioner based on the signal's propagation time, thereby controlling the air conditioner's oscillation direction, fan speed, and temperature. While ultrasonic positioning technology has achieved intelligent control of air conditioners to some extent, it suffers from drawbacks such as weak anti-interference capabilities, small measurement coverage, and weak penetration, limiting its effectiveness in complex home environments. Summary of the Invention

[0004] This invention provides an adaptive control method, storage medium, and electronic device for smart home air conditioners, which solves the problem that existing smart home air conditioners cannot accurately adapt to user needs and environment, and realizes adaptive control of air conditioners based on user location and individual characteristics.

[0005] This application provides an adaptive control method for smart home air conditioners, including: A smart home air conditioner adaptive control method, comprising: The system receives location and individual characteristic data of users with UWB tags, determined by a cloud server based on data reported by UWB base stations; the number of UWB base stations is at least four, used to receive signals emitted by devices with UWB tags. The operating status of the air conditioner is adaptively determined based on the location and individual characteristic data.

[0006] According to the adaptive control method for smart home air conditioners provided in this application, the method further includes: receiving indoor unoccupied status data sent by a cloud server; the unoccupied status data is generated when an ultra-wideband base station does not receive a signal from a device with an ultra-wideband tag within a preset time period; and automatically turning off the air conditioner based on the unoccupied status data.

[0007] According to the adaptive control method for smart home air conditioners provided in this application, after the ultra-wideband base station receives a signal emitted by a device with an ultra-wideband tag, the method further includes: obtaining a first timestamp of the request signal emitted by the device and a second timestamp of the received request signal; responding to the device and recording a third timestamp of the response signal emitted; obtaining a fourth timestamp of the response signal received by the device; and generating reporting data based on the first timestamp, the second timestamp, the third timestamp, and the fourth timestamp and sending it to a cloud server.

[0008] According to the adaptive control method for smart home air conditioners provided in this application, the determination of the location of the user with an ultra-wideband tag based on the data reported by the ultra-wideband base station specifically includes: determining the time difference of signal arrival between each pair of base stations based on the data reported by the ultra-wideband base station; and determining the location of the user with the ultra-wideband tag based on the location of each base station and the time difference using a positioning algorithm.

[0009] According to the adaptive control method for smart home air conditioners provided in this application, the method for determining the location of a user with an ultra-wideband tag based on a positioning algorithm and the location of each base station and the time difference specifically includes: constructing multiple hyperbolas based on at least three base stations; the hyperbolas are determined based on the location of the base stations and the time difference; and obtaining the intersection of the multiple hyperbolas as the actual location of the tag.

[0010] According to the adaptive control method for smart home air conditioners provided in this application, after determining the operating status of the air conditioner, the method further includes: if the air conditioner changes its operating status within a preset time period after operation, then it is determined that the user has manually changed the operating status, and the user behavior is recorded in the air conditioner usage record; based on the user's location information and the air conditioner usage record, the user's daily habit data is learned; and the air conditioner operating status is automatically adjusted based on the daily habit data.

[0011] This application also provides a smart home air conditioner adaptive control device, including: The data receiving module is used to receive the location and individual characteristic data of users with ultra-wideband tags, which are determined by the cloud server based on the data reported by the ultra-wideband base stations; the number of ultra-wideband base stations is at least 4, which are used to receive signals emitted by devices with ultra-wideband tags. An adaptive operating status module is used to adaptively determine the operating status of the air conditioner based on the location and individual characteristic data.

[0012] This application also provides an adaptive control system for smart home air conditioning, including: Mobile ultra-wideband tag devices are used to transmit user data on behalf of users; An ultra-wideband base station is used to receive user data from the mobile ultra-wideband tag device and report the user data to the cloud server in real time. A cloud server is used to receive user data from the ultra-wideband base station, determine the location of the mobile ultra-wideband tag device based on the user data, and send the location of the mobile ultra-wideband tag device and the user data to the air conditioner. An air conditioner is used to adaptively control its operating status based on the location of the mobile ultra-wideband tag device and user data.

[0013] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the computer program to implement any of the above-described smart home air conditioner adaptive control methods.

[0014] This application also provides a computer-readable storage medium comprising a stored program, wherein the program, when executed, implements any of the above-described smart home air conditioner adaptive control methods.

[0015] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the smart home air conditioner adaptive control method as described above.

[0016] The smart home air conditioner adaptive control method, storage medium, and electronic device provided in this application, by receiving data reported by a cloud server from an ultra-wideband (UWB) base station, enable the system to accurately acquire the location and individual characteristic data of users with UWB tags, and then adaptively adjust the operating status of the air conditioner. This not only improves the level of home intelligence, allowing the air conditioner to intelligently adjust according to the user's real-time location and personalized needs, but also enhances living comfort and energy efficiency. The precise positioning achieved through UWB technology enables more detailed scene control. Attached Figure Description

[0017] 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.

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the hardware environment for an adaptive control method for a smart home air conditioner according to an embodiment of this application; Figure 2 This is a flowchart illustrating the adaptive control method for smart home air conditioners provided in this application; Figure 3 This is a schematic diagram of the UWB ranging principle provided in this application; Figure 4 This is a schematic diagram of the home environment layout provided in this application; Figure 5 This is a schematic diagram of the structure of the smart home air conditioner adaptive control device provided in this application; Figure 6 This is a diagram of the architecture of the smart home air conditioning adaptive control system provided in this application; Figure 7 This is a schematic diagram of the electronic device provided in this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0021] 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.

[0022] Ultra-wideband (UWB) technology is a wireless carrier communication technology that uses frequency bandwidths above 1 GHz. It employs nanosecond-level non-sinusoidal narrow pulses to transmit data, thus occupying a very wide frequency spectrum. It features low system complexity, low transmitted signal power spectral density, insensitivity to channel fading, low interception capability, high positioning accuracy, and extremely strong penetration capability. Utilizing these characteristics of high-precision positioning and extremely strong penetration capability, it can be used for precise indoor positioning services.

[0023] There are several known smart home positioning technologies, one of the most commonly used being ultrasonic radar positioning.

[0024] Ultrasonic positioning: It consists of an ultrasonic transmitter, an ultrasonic receiver, and a controller.

[0025] Positioning method: When the ultrasonic transmitter emits an ultrasonic pulse, the emission time is recorded. When the ultrasonic receiver receives the pulse, the reception time is also recorded. By measuring the difference between these two times, the propagation time of the ultrasonic signal from the transmitter to the receiver can be calculated. Since the speed of sound in air is known (approximately 340 meters per second), the distance between the transmitter and receiver can be calculated based on the propagation time and speed.

[0026] By using ultrasound to locate a person indoors, the location information is reported to the cloud. The cloud then uses algorithms to calculate and deduce the direction of the air conditioner's oscillation, so that the airflow moves with the person's position. At the same time, it automatically adjusts the air conditioner's fan speed, temperature, and other parameters to create a more comfortable environment for the user through intelligent adaptation to ambient temperature.

[0027] Using millimeter-wave radar technology for positioning has the following drawbacks: 1. Weak anti-interference capability: Ultrasonic technology is easily affected by speed, vibration, temperature and humidity, and its detection capability will be affected when the target object is a plane at a special angle or an object that can absorb ultrasonic waves.

[0028] 2. Small measurement coverage: Ultrasonic technology has a short detection distance, generally applicable to a range of 0.2 meters to 5 meters.

[0029] 3. Weak penetration ability: When ultrasonic technology encounters obstacles, the signal penetration ability is limited.

[0030] Advantages of UWB: 1. Higher accuracy: UWB can provide positioning with centimeter-level or even higher accuracy.

[0031] 2. Enhanced anti-interference capability: UWB exhibits high immunity to various types of interference (including multipath interference), and its emitted pulse waves have stronger anti-interference capabilities than continuous electromagnetic waves. Operating in the 3GHz-10GHz frequency band, UWB experiences fewer external interference signals compared to ultrasonic technology, enabling it to maintain stable positioning performance in complex environments.

[0032] 3. Wider coverage: UWB signals have a relatively large coverage area, which can meet the positioning needs of a larger spatial range.

[0033] 4. Better penetration capability: UWB technology has better penetration capability to a certain extent, and can penetrate some non-metallic obstacles. For indoor scenarios with obstacles, UWB positioning is more reliable.

[0034] In summary, the advantages of UWB technology can compensate for the shortcomings of ultrasonic technology in terms of positioning convenience, providing higher precision UWB positioning technology, thereby enabling air conditioners to provide users with more precise proactive services in smart home scenarios.

[0035] This application proposes a method for adaptive control of an air conditioner based on UWB technology, enabling the air conditioner to automatically turn on and off, adjust the airflow direction and intensity, and adjust the temperature.

[0036] According to one aspect of the embodiments of this application, an adaptive control method for a smart home air conditioner is provided. This adaptive control method for a smart home air conditioner is widely applicable to whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, smart home device ecosystems, and intelligence house ecosystems. Optionally, in this embodiment, the above-mentioned adaptive control method for a smart home air conditioner 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.

[0037] 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.

[0038] Figure 2 This is a flowchart illustrating one of the upgrade methods for intelligent voice-enabled devices provided in this application, including the following steps: S210: Receives location and individual characteristic data of users with UWB tags, determined by the cloud server based on data reported by UWB base stations.

[0039] There are at least four UWB base stations used to receive signals from devices with UWB tags.

[0040] According to the adaptive control method for smart home air conditioners provided in this application, after receiving a signal from a device with a UWB tag, the UWB base station obtains the first timestamp of the request signal sent by the device and the second timestamp of the received request signal; responds to the device and records the third timestamp of the response signal sent; obtains the fourth timestamp of the response signal received by the device; and generates reporting data based on the first timestamp, the second timestamp, the third timestamp, and the fourth timestamp and sends it to the cloud server.

[0041] Specifically, the ranging principle of UWB is as follows: Two-way time-of-flight (TW-TOF) method: Each device generates an independent timestamp from the moment it is started.

[0042] like Figure 3As shown, Device1, acting as the initiator, transmits a request-type pulse signal at its timestamp T0. Device2, acting as the responder, receives the request signal from the initiator at time T1, and then transmits a response-type signal at time T2, which is received by Device1 at its own timestamp T3. The flight time of the pulse signal between the two devices can be calculated from this, thus determining the flight distance r. The calculation formula is as follows.

[0043] r=C[(T3-T0)-(T2-T1)] / 2 Where C is the speed of light, T0 is the first timestamp of the transmitter sending the request data, T1 is the second timestamp of the responder receiving the request data, T2 is the third timestamp of the responder sending the response data, and T3 is the fourth timestamp of the transmitter receiving the response data.

[0044] High-precision distance measurement is achieved by accurately measuring the flight time of the pulse signal between two devices. Utilizing the constant and extremely fast speed of light, combined with precise timestamp recording, ensures the accuracy and reliability of the ranging results. The two-way time-of-flight method effectively eliminates the influence of clock deviations between devices on the ranging results. By using a time difference in the calculation formula, i.e., [(T3-T0)-(T2-T1)], the inaccuracies of the device's own clock can be offset, thereby further improving the ranging accuracy.

[0045] According to the adaptive control method for smart home air conditioners provided in this application, the location of a user with a UWB tag is determined based on data reported by a UWB base station. Specifically, this includes: determining the time difference of signal arrival between each pair of base stations based on data reported by the UWB base station; and determining the location of the user with a UWB tag based on the location and time difference of each base station using a positioning algorithm.

[0046] According to the adaptive control method for smart home air conditioners provided in this application, based on a positioning algorithm, the location of a user with a UWB tag is determined according to the location and time difference of each base station. Specifically, the method includes: constructing multiple hyperbolas based on at least three base stations; determining the hyperbolas based on the location and time difference of the base stations; and obtaining the intersection of the multiple hyperbolas as the actual location of the tag.

[0047] Specifically, such as Figure 4 As shown, four UWB base stations are installed in four different locations in the home. When a user with a UWB tag enters the home, the tag communicates with the base station. The base station then reports the received data to the cloud in real time. The cloud computing service module calculates the location of the tag in real time using the TDOA principle.

[0048] Time Difference of Arrival (TDOA) is a positioning method that uses arrival time, also known as hyperbolic positioning. When a tag sends out a UWB signal, all base stations within the tag's wireless coverage area will receive the signal. If two base stations with known coordinates receive the signal, and the distance between the tag and the two base stations is different, then the time at which the two base stations receive the signal will be different.

[0049] The difference in flight distance between different base stations is calculated using the following formula: d12 = r1 - r2 = (t1 - t2) × c; d23 = r2 - r3 = (t2 - t3) × c; d34 = r3 - r4 = (t3 - t4) × c; d14 = r1 - r4 = (t1 - t4) × c; Where t1-t4 represent the time when base stations 1-4 receive signals from UWB tag devices, d12 represents the flight distance difference between base station 1 and base station 2, d23 represents the flight distance difference between base station 2 and base station 3, d34 represents the flight distance difference between base station 3 and base station 4, d14 represents the flight distance difference between base station 1 and base station 4, c represents the speed of light, and r1-r4 represents the flight distance of the pulse signal to base station 1-4.

[0050] After obtaining the above flight distance difference, the coordinates (xi, yi, zi) of the tag device can be calculated using the following formula, thereby obtaining the position of the tag device: d12= - ; d23= - ; d34= - ; d14= - ; Among them, the coordinates of base station 1 are (x1, y1, z1), the coordinates of base station 2 are (x2, y2, z2), the coordinates of base station 3 are (x3, y3, z3), and the coordinates of base station 4 are (x4, y4, z4).

[0051] Utilizing UWB technology and the TDOA algorithm, centimeter-level high-precision positioning can be achieved in indoor environments. Real-time location calculation via a cloud computing service module enables rapid response and updates to the tag device's location information. This real-time capability allows the system to handle various situations promptly, improving overall operational efficiency. Positioning accuracy and coverage can be adjusted by increasing or decreasing the number of base stations to meet different scenarios and needs. Simultaneously, the cloud computing service module can be easily integrated with other systems to achieve more functions and applications. By utilizing signals received from multiple base stations and performing time difference calculations, errors and interference that may exist in single-base station positioning are effectively eliminated. Data fusion and processing from multiple base stations improves positioning accuracy and stability.

[0052] S220: Adaptively determine the operating status of the air conditioner based on location and individual characteristic data.

[0053] Specifically, relying on the high-precision positioning characteristics of UWB technology, UWB tag devices communicate with base stations in real time, and the base stations report the data to the cloud. The cloud-based positioning calculation module can calculate the location of people wearing UWB tags in real time, and then adjust the position of the air conditioner louvers, the temperature, and the fan speed according to the weather conditions.

[0054] It can also perform personalized adjustments based on the characteristics of different tags. For example, in the hot summer, if a male homeowner wearing a UWB tag enters the house, the UWB base station reports the tag information to the cloud. The cloud locates the homeowner's position, immediately turns on the air conditioner, sets the cooling mode to maximum fan speed, and positions the air conditioner shroud towards the homeowner, allowing him to immediately feel cool air. As the homeowner moves, the air conditioner shroud remains facing him, and when he moves closer to the air conditioner, the air conditioner automatically reduces the fan speed to avoid discomfort caused by excessively strong airflow. The entire system can also learn the different habits of different family members. For example, if a female homeowner enters the home wearing her UWB tag, in addition to real-time location tracking, the system can also determine, based on the tag's characteristics, that she is the homeowner and prefers a temperature of 18°C ​​and a medium fan speed. The entire system will then automatically adjust the air conditioner's temperature, fan speed, and shroud position based on this information.

[0055] Leveraging the high-precision positioning capabilities of UWB technology, the system can accurately track the location of individuals tagged with UWB tags in real time. This allows the air conditioning system to respond quickly, adjusting the louver position based on the individual's location and movement to ensure that cool or warm air is directed directly to them, providing optimal comfort. The system can also be personalized based on the characteristics of different UWB tags. When different members enter the room, the air conditioning system automatically adjusts parameters such as temperature and fan speed according to their preferences and habits, providing a personalized and comfortable environment.

[0056] According to the adaptive control method for smart home air conditioners provided in this application, after determining the operating status of the air conditioner, if the air conditioner changes its operating status within a preset time period after operation, it is determined that the user has manually changed the operating status, and the user's behavior is recorded in the air conditioner usage record; based on the user's location information and the air conditioner usage record, the user's daily habit data is learned; and the air conditioner operating status is automatically adjusted based on the daily habit data.

[0057] Specifically, the system monitors the air conditioner's operating status through an intelligent air conditioning system. Once the system determines that the air conditioner is running, it continuously monitors changes in its status. If the air conditioner changes its operating status within a preset time period, such as 30 minutes, switching from cooling mode to fan mode, the system determines that this change is the result of manual user operation. At this time, the system records this user action, including the time of the change and the operating status before and after the change, in the air conditioner usage log.

[0058] Subsequently, the system combines user location information, such as the user's movement trajectory within the room obtained through an indoor positioning system, and air conditioner usage records, to learn the user's daily habits through big data analytics. For example, the system might discover that the user usually sets the air conditioner to silent mode after 10 PM, or that the user habitually turns up the air conditioner temperature after entering the bedroom.

[0059] Once the system has accumulated enough user habit data through learning, it can automatically adjust the air conditioner's operating status based on this data. For example, during the time when users usually prepare to rest, the system can automatically switch the air conditioner to a quiet and moderately warm mode, thus providing a more considerate user experience.

[0060] Because air conditioning systems possess self-learning capabilities, they can continuously optimize their understanding of occupants' habits by collecting and analyzing data, thereby more accurately meeting individual needs. This intelligent learning ability allows the system to become more intelligent and efficient over time.

[0061] By automatically adjusting the air conditioning settings, the comfort of residents is significantly improved. Whether in the hot summer or the cold winter, the air conditioning system ensures that residents can enjoy a comfortable temperature and airflow as soon as they enter the room, without the need for manual adjustment of the air conditioning settings.

[0062] According to the adaptive control method for smart home air conditioners provided in this application, the system receives indoor unoccupied status data sent by a cloud server; the unoccupied status data is generated when the UWB base station does not receive a signal from a device with a UWB tag within a preset time period; and the air conditioner is automatically turned off based on the unoccupied status data.

[0063] Specifically, leveraging the positioning capabilities of UWB technology, the system can detect when a home is unoccupied for an extended period, automatically shutting off the air conditioner to save energy. Specifically, the air conditioner receives indoor vacancy data from a cloud server. This vacancy data is automatically generated when the UWB (Ultra-Wideband) base station does not receive signals from any devices carrying UWB tags within a preset time period, such as 30 minutes or an hour. In other words, if no human activity is detected during this period, the system determines that the room is unoccupied. Once this vacancy data is received, the air conditioner automatically shuts off based on this data. This is done to save energy and avoid energy waste caused by the air conditioner running when no one is home.

[0064] The key point of this application is to utilize the high positioning accuracy, strong anti-interference capabilities, wide coverage, and strong penetration of UWB technology to achieve adaptive air conditioning in smart air conditioners, providing users with a comfortable experience. 1) The design employs 4 base stations, providing seamless coverage of the entire house and enabling whole-house positioning.

[0065] 2) By utilizing the feature information of UWB tags, the temperature, fan speed and other attributes of the air conditioner can be controlled according to the preferences of different users. 3) Utilizing the high precision and real-time characteristics of UWB, the location information of a person can be located in real time. The cloud service can automatically control the position of the air conditioner louvers to achieve an excellent experience of the airflow following the person. 4) At the same time, based on the real-time location of the distance between the person and the air conditioner, the air volume is automatically adjusted to avoid the wind blowing too hard when the person is too close and not being able to feel the wind when the person is too far away, thus providing a comfortable experience for the user. 5) At the same time, by taking advantage of its wide coverage and strong penetration, it can detect when no one is home for a long time and automatically turn off the air conditioner to achieve energy saving.

[0066] The advantages of this application are mainly reflected in the following aspects: 1. Compared to ultrasonic positioning technology, UWB technology has strong anti-interference capabilities, is not affected by factors such as temperature, and has the advantage of high consistency; 2. The cloud service can adjust the air conditioner's attributes in a personalized and adaptive manner based on the feature and location information reported by the UWB tag; 3. It has energy-saving effects.

[0067] The following describes the smart home air conditioner adaptive control device provided in this application. The smart home air conditioner adaptive control device described below can be referred to in correspondence with the smart home air conditioner adaptive control method described above.

[0068] Figure 5 This is a schematic diagram of the structure of the smart home air conditioner adaptive control device provided in an embodiment of this application. The structure includes: The data receiving module 510 is used to receive the location and individual characteristic data of users with ultra-wideband tags, which are determined by the cloud server based on the data reported by the ultra-wideband base stations; there are at least 4 ultra-wideband base stations, which are used to receive signals emitted by devices with ultra-wideband tags. The adaptive operating status module 520 is used to adaptively determine the operating status of the air conditioner based on location and individual characteristic data.

[0069] This application also provides an adaptive control system for smart home air conditioning, including: Mobile ultra-wideband tag devices are used to transmit user data on behalf of users; Ultra-wideband base stations are used to receive user data from mobile ultra-wideband tag devices and report the user data to the cloud server in real time. The cloud server is used to receive user data from the UWB base station, determine the location of the mobile UWB tag device based on the user data, and send the location of the mobile UWB tag device and user data to the air conditioner. Air conditioning is used to adaptively control the operation of the air conditioner based on the location of the mobile ultra-wideband tag device and user data.

[0070] like Figure 6 As shown, a mobile device with a UWB tag enters a home and transmits a signal. A UWB base station collects data and personal characteristics, reporting this information to a cloud server in real time. The cloud server receives the location data, calculates the tag's exact location, and sends this information to the air conditioner. Based on the real-time location information and individual characteristics, the air conditioner adaptively controls its operation, mode, temperature, and fan speed, while the louvers adjust their position as the person moves. When the cloud server detects no one in the room for an extended period, it automatically shuts off the air conditioner, achieving energy savings.

[0071] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7As shown, the electronic device may include a processor 710, a communications interface 720, a memory 730, and a communication bus 740. The processor 710, communications interface 720, and memory 730 communicate with each other via the communication bus 740. The processor 710 can call logic instructions stored in the memory 730 to execute a smart home air conditioner adaptive control method. This method includes: receiving location and individual characteristic data of users with ultra-wideband tags, determined by a cloud server based on data reported by ultra-wideband base stations; having at least four ultra-wideband base stations for receiving signals emitted by devices with ultra-wideband tags; and adaptively determining the operating status of the air conditioner based on the location and individual characteristic data.

[0072] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the smart home air conditioner adaptive control method provided by the above methods. The method includes: receiving location and individual characteristic data of users with ultra-wideband tags determined by a cloud server based on data reported by ultra-wideband base stations; having at least four ultra-wideband base stations for receiving signals emitted by devices with ultra-wideband tags; and adaptively determining the operating status of the air conditioner based on the location and individual characteristic data.

[0074] In another aspect, this application also provides a computer-readable storage medium, which includes a stored program, wherein the program executes the smart home air conditioner adaptive control method provided by the above methods when it runs. The method includes: receiving location and individual characteristic data of users with ultra-wideband tags determined by a cloud server based on data reported by ultra-wideband base stations; having at least four ultra-wideband base stations for receiving signals emitted by devices with ultra-wideband tags; and adaptively determining the operating status of the air conditioner based on the location and individual characteristic data.

[0075] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0076] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, 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 can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart home air conditioner adaptive control method, characterized in that, include: Receive location and individual characteristic data of users with ultra-wideband tags, determined by the cloud server based on data reported by ultra-wideband base stations; The number of ultra-wideband base stations is at least four, used to receive signals emitted by devices with ultra-wideband tags; The operating status of the air conditioner is adaptively determined based on the location and individual characteristic data.

2. The adaptive control method for smart home air conditioners according to claim 1, characterized in that, The method further includes: The system receives indoor unmanned status data sent by a cloud server; the unmanned status data is generated when the ultra-wideband base station does not receive a signal from a device with an ultra-wideband tag within a preset time period. The air conditioner will automatically shut off based on the unmanned status data.

3. The adaptive control method for smart home air conditioning according to claim 1 or 2, characterized in that, After receiving a signal from a device with an ultra-wideband tag, the method further includes: Obtain the first timestamp of the request signal sent by the device and the second timestamp of the request signal received; Respond to the device and record a third timestamp of the response signal; Obtain the fourth timestamp of the response signal received by the device; Data is generated based on the first, second, third, and fourth timestamps and sent to the cloud server.

4. The adaptive control method for smart home air conditioners according to claim 3, characterized in that, The location of the user with the ultra-wideband tag, determined based on the data reported by the ultra-wideband base station, specifically includes: The time difference of signal arrival between each pair of base stations is determined based on the data reported by the ultra-wideband base stations; Based on the positioning algorithm, the location of the user with the ultra-wideband tag is determined according to the location of each base station and the time difference.

5. The adaptive control method for smart home air conditioners according to claim 4, characterized in that, The method of determining the location of users with ultra-wideband tags based on the positioning algorithm, according to the location of each base station and the time difference, specifically includes: Multiple hyperbolas are constructed based on at least three base stations; the hyperbolas are determined based on the location of the base stations and the time difference. The intersection of multiple hyperbolas is used as the actual location of the label.

6. The adaptive control method for smart home air conditioning according to any one of claims 1 to 5, characterized in that, After determining the air conditioner's operating status, the method further includes: If the air conditioner changes its operating status within a preset time period after it starts running, it will be determined that the user manually changed the operating status, and the user's behavior will be recorded in the air conditioner usage log. Learn users' daily habits based on their location information and air conditioning usage records; The air conditioner's operating status is automatically adjusted based on the data of daily habits.

7. A smart home air conditioner adaptive control device, characterized in that, include: The data receiving module is used to receive the location and individual characteristics data of users with ultra-wideband tags, which are determined by the cloud server based on the data reported by the ultra-wideband base station. The number of ultra-wideband base stations is at least four, used to receive signals emitted by devices with ultra-wideband tags; An adaptive operating status module is used to adaptively determine the operating status of the air conditioner based on the location and individual characteristic data.

8. A smart home air conditioner adaptive control system, characterized in that, include: Mobile ultra-wideband tag devices are used to transmit user data on behalf of users; An ultra-wideband base station is used to receive user data from the mobile ultra-wideband tag device and report the user data to the cloud server in real time. A cloud server is used to receive user data from the ultra-wideband base station, determine the location of the mobile ultra-wideband tag device based on the user data, and send the location of the mobile ultra-wideband tag device and the user data to the air conditioner. An air conditioner is used to adaptively control its operating status based on the location of the mobile ultra-wideband tag device and user data.

9. 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 of any one of claims 1 to 6.

10. 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 of any one of claims 1 to 6 through the computer program.

Images