An air conditioner control method and device, electronic equipment and storage medium

Abstract

The application discloses an air conditioner control method and device, electronic equipment and storage medium, the application can understand the distribution of personnel in the region in real time by acquiring and analyzing real-time flow data of each region in the indoor space. The analysis result of each region can be obtained by analyzing the real-time flow data, and the first parameter of each air outlet of the central air conditioner can be generated according to the flow condition of different regions, so as to realize accurate air conditioner control of each region. The first control instruction is generated based on the first parameter and sent to the corresponding air outlet, so that the air outlet operates according to the indicated first parameter, realizing automatic control. Reduce manual intervention, improve the automation degree and operation efficiency of the air conditioning system. Through accurate air conditioner control, intelligent adjustment is carried out according to the flow data of each region, and unnecessary energy consumption is reduced.

Description

Technical Field

[0001] This invention relates to the field of intelligent equipment control, specifically to an air conditioning control method, device, electronic equipment, and storage medium. Background Technology

[0002] Central air conditioning systems are widely used in commercial and residential buildings to provide a comfortable indoor environment. However, traditional central air conditioning systems typically distribute cooling / heating evenly, making it impossible to precisely control the temperature based on the distribution and activity of people in the indoor space. Therefore, while meeting overall indoor temperature requirements, they cannot meet the varying needs of people in different areas, resulting in uneven temperatures and low comfort levels in some areas.

[0003] For example, in areas with a high concentration of people, traditional central air conditioning systems may still provide uniform cooling or heating, resulting in excessively low or high temperatures and affecting comfort. Furthermore, in densely populated areas, central air conditioning systems may supply too much cooling / heating, leading to energy waste. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide an air conditioning control method, device, electronic device, and storage medium to solve the problem that existing central air conditioning systems cannot accurately regulate the distribution or activities of people in an indoor space.

[0005] In a first aspect, embodiments of the present invention provide an air conditioning control method, the method being applied to a server, the method comprising:

[0006] Real-time pedestrian flow data for each area in an indoor space is acquired, and the analysis results for each area are obtained by analyzing the real-time pedestrian flow data.

[0007] The analysis results are used to generate first parameters corresponding to each air outlet of the central air conditioner, wherein each air outlet of the central air conditioner corresponds to each area of ​​the indoor space.

[0008] Generate a first control command based on the first parameter;

[0009] Send the first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command.

[0010] Furthermore, the analysis of the real-time pedestrian flow data to obtain analysis results corresponding to each of the aforementioned areas includes:

[0011] The real-time pedestrian flow data is analyzed to obtain the pedestrian flow situation corresponding to the area;

[0012] The flow of people in each of the aforementioned areas is sorted to obtain the ranking of each area.

[0013] The analysis results are generated based on the pedestrian flow and the regional ranking.

[0014] Furthermore, the analysis of the real-time pedestrian flow data to obtain the pedestrian flow situation corresponding to the area includes:

[0015] Extract pedestrian behavior data, pedestrian location, and pedestrian movement direction from the real-time pedestrian flow data;

[0016] The population density within the area is determined using the location of the personnel.

[0017] The population flow trend within the area is determined by using the location of the personnel and their direction of movement.

[0018] The types of human activities within the area are determined using the aforementioned human behavior data;

[0019] The pedestrian flow data is generated based on the population density, population flow trend, and population activity type.

[0020] Furthermore, the step of generating the first parameters corresponding to each air outlet of the central air conditioning system using the analysis results includes:

[0021] The airflow direction is determined based on the regional ranking and the population flow trend.

[0022] The airflow size is determined based on the type of personnel activity and the personnel density.

[0023] The first parameter is generated based on the air outlet direction and air outlet size.

[0024] Furthermore, determining the airflow direction based on the regional ranking and the population flow trend includes:

[0025] The regions whose regional ranking is greater than the preset ranking are designated as target regions.

[0026] Obtain the orientation information of the target area in the indoor space, and generate an initial airflow direction based on the orientation information;

[0027] The initial airflow direction is adjusted using the population flow trend to obtain the final airflow direction.

[0028] Furthermore, determining the airflow size based on the type of personnel activity and the personnel density includes:

[0029] Based on the mapping relationship between preset activity types and air outlet size, the initial air outlet size corresponding to the activity type of the person is obtained;

[0030] The initial airflow size is adjusted based on the personnel density to obtain the airflow size.

[0031] Furthermore, after sending the first control command to the corresponding air outlet, the method further includes:

[0032] Obtain usage information for each region at the next time step;

[0033] The first parameter is updated using the usage information to obtain the second parameter;

[0034] A second control command is generated based on the second parameter;

[0035] Send the second control command to the corresponding air outlet, wherein the air outlet is used to operate according to the second parameter indicated by the second control command.

[0036] Secondly, embodiments of the present invention provide an air conditioning control device, the device comprising:

[0037] The acquisition module is used to acquire real-time pedestrian flow data in various areas of the indoor space and analyze the real-time pedestrian flow data to obtain the analysis results corresponding to each area.

[0038] The processing module is used to generate first parameters corresponding to each air outlet of the central air conditioner using the analysis results, wherein each air outlet of the central air conditioner corresponds to each area of ​​the indoor space.

[0039] The generation module is used to generate a first control instruction based on the first parameter;

[0040] The sending module is used to send the first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command.

[0041] Thirdly, embodiments of the present invention provide an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the method described in the first aspect or any of its corresponding embodiments.

[0042] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that cause a computer to perform the method described in the first aspect or any of its corresponding embodiments.

[0043] The method provided in this application acquires and analyzes real-time pedestrian flow data in various areas of an indoor space, enabling real-time understanding of the distribution of people in those areas. By analyzing the real-time pedestrian flow data, analysis results for each area are obtained. Based on the pedestrian flow in different areas, first parameters for each air outlet of the central air conditioning system are generated, thereby achieving precise air conditioning control for each area, improving indoor air comfort and energy efficiency. First control commands are generated based on the first parameters and sent to the corresponding air outlets, causing the outlets to operate according to the indicated first parameters, achieving automated control. This reduces manual intervention and improves the automation level and operating efficiency of the air conditioning system. Through precise air conditioning control and intelligent adjustment based on pedestrian flow data in each area, it is possible to avoid fully activating the air conditioning, reducing unnecessary energy consumption. Attached Figure Description

[0044] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0045] Figure 1 This is a schematic flowchart of an air conditioning control method according to some embodiments of the present invention;

[0046] Figure 2 This is a schematic flowchart of an air conditioning control method according to some embodiments of the present invention;

[0047] Figure 3 This is a schematic flowchart of an air conditioning control method according to some embodiments of the present invention;

[0048] Figure 4 This is a schematic diagram of an air conditioning control scenario according to some embodiments of the present invention;

[0049] Figure 5 This is a structural block diagram of an air conditioning control device according to an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] According to embodiments of the present invention, an air conditioning control method, apparatus, electronic device, and storage medium are provided. It should be noted that the steps shown in the flowcharts in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0053] This embodiment provides an air conditioning control method. Figure 1 This is a flowchart of an air conditioning control method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0054] Step S11: Obtain real-time pedestrian flow data for each area in the indoor space, and analyze the real-time pedestrian flow data to obtain the corresponding analysis results for each area.

[0055] The method provided in this application is applied to a server, which is communicatively connected to sensors deployed in various areas of the indoor space. These sensors are used to detect the location, distribution, and activity of people. The sensors can be infrared sensors, cameras, sound sensors, etc. The sensors transmit the collected information to the server, which analyzes the information to obtain real-time pedestrian flow data.

[0056] As an example, the collected information could be a series of multiple frames of regional images. The sensor transmits these regional images to a server, which can then perform image recognition to obtain real-time pedestrian flow data. Specifically, after receiving the image data, the server uses image recognition technology to process and analyze the images. Image recognition technology can include methods such as computer vision, machine learning, and deep learning.

[0057] Building upon image recognition, the server can extract features of people, such as facial and body characteristics, to determine their behavioral data. For example, it can identify a person's actions, such as walking, standing, or sitting. By analyzing features and location information, the server can determine a person's position. This can be achieved using techniques such as object detection and tracking. For instance, it can identify faces or bodies and track their positions within an image. By comparing the positional information of people across consecutive frames, the server can calculate their direction of movement. Finally, real-time pedestrian flow data is generated based on the image recognition results, and this data can be stored in a database for subsequent analysis and applications.

[0058] In this embodiment of the application, real-time pedestrian flow data is analyzed to obtain analysis results for each area, such as... Figure 2 As shown, it includes the following steps A1-A3:

[0059] Step A1: Analyze real-time pedestrian flow data to obtain the pedestrian flow situation corresponding to the area.

[0060] In this embodiment of the application, analyzing real-time pedestrian flow data to obtain the pedestrian flow situation corresponding to a region includes: extracting personnel behavior data, personnel location, and personnel movement direction from the real-time pedestrian flow data; determining the personnel density in the region using personnel location; determining the personnel flow trend in the region using personnel location and personnel movement direction; determining the personnel activity type in the region using personnel behavior data; and generating pedestrian flow information based on personnel density, personnel flow trend, and personnel activity type.

[0061] In this embodiment, the process of determining the population density within an area using person locations includes: First, converting the location information of people identified in the image into specific coordinate values. Then, mapping the coordinate values ​​in the image to the actual area. That is, converting the image coordinate values ​​into coordinate values ​​of the actual area, for example, using methods such as camera calibration. Next, dividing the actual area into several smaller areas. The actual area can be divided into grid-like smaller areas. For each smaller area, counting the number of people within that area. Whether a person is located within a smaller area can be determined by comparing the coordinate values ​​of the person's location with the boundary of the smaller area. Based on the number of people in each smaller area, calculating the population density, for example, by dividing the number of people by the area of ​​the smaller area.

[0062] In this embodiment, the process of determining the flow trend of people within an area using personnel location and movement direction includes: First, determining the position coordinates of each person at different time points. Based on continuous position coordinates, the movement direction of each person can be calculated. For example, the movement direction can be determined by calculating the difference between the current position and the previous position. The movement direction of the person is then associated with the area. The entire area is divided into several smaller areas, and each person's position is matched with a smaller area. For each smaller area, the number of people entering and leaving the area is counted, and the corresponding time points and personnel IDs are recorded. By comparing the position information between two consecutive time points, it can be determined whether a person is entering or leaving the area. Finally, the flow trend of people is analyzed based on the number of people entering and leaving and the order of the time points. That is, the flow direction of people is determined by counting the difference in the number of people entering and leaving each smaller area. For example, if the number of people entering a smaller area is greater than the number of people leaving within a certain time period, it indicates that the flow direction of people is towards that smaller area.

[0063] In this embodiment, the process of determining the type of human activity within a region using human behavior data includes: associating human behavior data with the region; dividing the entire region into several smaller regions and matching each person's location and behavior information with each smaller region; counting the number of people in each smaller region for the corresponding activity type; and, based on the classification results of the human behavior data, counting the number of people performing a specific activity in each smaller region. Based on the statistical results, determining the type of human activity within the region. For example, if a large amount of human behavior data in a smaller region indicates dancing, then the activity type in that region can be determined to be exercise.

[0064] Step A2: Sort the pedestrian flow in each area to obtain the ranking of each area.

[0065] In this embodiment, the pedestrian flow in each area of ​​the indoor space is statistically analyzed based on collected data. Pedestrian flow can be represented by the number of people passing through or staying in each area. The areas are then sorted according to pedestrian flow, ranked from highest to lowest. Areas with higher pedestrian flow are ranked higher, and areas with lower pedestrian flow are ranked lower. The parameters of the central air conditioning vents within each area can be determined based on the area ranking. For example, based on the principle that areas with higher pedestrian flow are ranked higher, the vents can be adjusted to those areas to meet the comfort requirements of densely populated areas.

[0066] Step A3: Generate analysis results based on pedestrian flow and regional ranking.

[0067] The method provided in this application can clearly understand the pedestrian traffic volume in each area by sorting, identifying peak and off-peak periods, and helping to optimize the operating efficiency of the central air conditioning system. Based on the analysis results, the air outlet parameters of the central air conditioning system can be adjusted to maximize the satisfaction of temperature and comfort needs in each area and improve energy efficiency. It can also reduce energy waste and cost increases, thereby improving energy efficiency and saving costs.

[0068] Step S12: Use the analysis results to generate the first parameters corresponding to each air outlet of the central air conditioning system, wherein each air outlet of the central air conditioning system corresponds to each area of ​​the indoor space.

[0069] In this embodiment, the correspondence between each air outlet of the central air conditioning system and each area of ​​the indoor space is first determined. This can be determined based on building floor plans, sensor layout, or other markings in the air conditioning system design. It is ensured that each air outlet corresponds to a specific area of ​​the indoor space. First parameters applicable to each area are generated based on the analysis results. This involves adjusting parameters such as airflow direction, airflow volume, or other relevant parameters. Corresponding first parameters are generated for each area based on its characteristics and needs.

[0070] Specifically, the analysis results are used to generate the first parameter corresponding to each air outlet of the central air conditioning system, such as... Figure 3 As shown, it includes the following steps B1-B3:

[0071] Step B1: Determine the airflow direction based on regional rankings and population flow trends.

[0072] In this embodiment of the application, determining the air outlet direction based on the regional ranking and the flow of people includes: taking the region with a regional ranking greater than a preset ranking as the target region; obtaining the orientation information of the target region in the indoor space and generating an initial air outlet direction based on the orientation information; and adjusting the initial air outlet direction using the flow of people to obtain the air outlet direction.

[0073] Specifically, by ranking the pedestrian flow in each area, areas with high pedestrian traffic are identified as target areas. These target areas are typically those where the central air conditioning vent parameters need to be adjusted first. The location and orientation of the target area within the indoor space can be determined using building floor plans, sensor placement, etc. Then, based on the target area's location and orientation relative to the central air conditioning system, an initial airflow direction is generated. Real-time pedestrian flow data analysis then yields trend information on pedestrian movement, such as direction and density. Based on this trend information, the initial airflow direction can be adjusted to better meet the needs of pedestrian flow. For example, if pedestrian flow tends in a certain direction, the airflow direction can be adjusted to face that direction to provide better comfort and air circulation.

[0074] The method provided in this application adjusts the air outlet direction based on regional ranking and population flow trends to better meet the needs of different areas and provide personalized temperature and comfort. By adjusting the air outlet direction, the air conditioner's cool / hot air can be delivered more precisely to the areas that need it, avoiding resource waste and improving energy efficiency. Precise adjustment of the air outlet direction can reduce unnecessary energy consumption and equipment operating time, thereby lowering operating costs. Furthermore, the air outlet direction can be adjusted promptly to adapt to constantly changing population flow, improving response speed and flexibility.

[0075] Step B2: Determine the airflow size based on the type of personnel activity and personnel density.

[0076] In this embodiment of the application, determining the air outlet size based on the type of personnel activity and the personnel density includes: obtaining the initial air outlet size corresponding to the type of personnel activity based on the preset mapping relationship between the activity type and the air outlet size; and adjusting the initial air outlet size using the personnel density to obtain the air outlet size.

[0077] Specifically, different types of personnel activities have different requirements for airflow volume. For example, conference rooms require a larger airflow volume to meet the characteristics of concentrated personnel and high ventilation needs, while office areas may only require a smaller airflow volume. Based on the preset mapping relationship between activity types and airflow volume, the initial airflow volume corresponding to each activity type is determined. Personnel density refers to the density of people in a certain area or place. Areas with high personnel density require a larger airflow volume to maintain comfort and air circulation. By monitoring personnel density in real time, the initial airflow volume can be dynamically adjusted. For example, when the personnel density is high, the airflow volume can be increased to provide sufficient fresh air and comfort; when the personnel density is low, the airflow volume can be reduced to save energy.

[0078] The method provided in this application determines the initial airflow size based on the type of personnel activity, providing personalized comfort according to the characteristics of different areas and meeting the needs of different activity types. Adjusting the airflow size based on personnel density ensures indoor air circulation and freshness, providing good indoor environmental quality. Simultaneously, it can also adjust the airflow size promptly according to changes in the number of people, adapting to changes in needs at different times or activity stages, improving flexibility and adaptability.

[0079] Step B3: Generate the first parameter based on the air outlet direction and air outlet size.

[0080] In this embodiment, the air outlet direction of each area is determined based on the above analysis results. The air outlet direction can be converted into a numerical parameter, such as an angle or azimuth. This numerical parameter serves as the basis for generating the first parameter. Simultaneously, the air outlet size of each area is determined. The air outlet size can be represented by specific numerical values, such as wind speed or air volume. Based on the air outlet size setting, it is converted into a numerical parameter as the basis for generating the first parameter. Then, the numerical parameters of the air outlet direction and air outlet size are combined to generate the first parameter. The method for generating the first parameter can be determined according to specific needs, such as using a weighted average or other relevant algorithms. The generated first parameter can be a weighted value or index that comprehensively considers the air outlet direction and air outlet size, used to adjust relevant parameters of the central air conditioning system.

[0081] Step S13: Generate a first control command based on the first parameter.

[0082] In this embodiment, the first parameter is converted into specific control instructions. These control instructions may include adjusting the central air conditioning's temperature setting, fan speed setting, and airflow direction setting. Based on the value of the first parameter and the setting logic, corresponding control instructions are generated and sent to the central air conditioning unit for execution.

[0083] Step S14: Send a first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command.

[0084] The method provided in this application embodiment can precisely regulate the temperature based on the distribution or activity of people in different areas, while fully meeting the overall indoor temperature requirements. By acquiring real-time pedestrian flow data for each area and generating corresponding control commands based on this data, cooling / heating can be prioritized for densely populated areas, or the supply can be adjusted in a timely manner according to changes in pedestrian density, thereby achieving balanced regional temperature and improved comfort.

[0085] Specifically, first, the specific air outlets requiring adjustment are identified. Air outlets can be labeled or coded according to the layout and design of the air conditioning system to accurately identify and locate the target outlets. The generated first control command is then transmitted to the corresponding air outlet via an appropriate communication method. This can be achieved through wired or wireless communication technologies, such as sensor networks or wireless control systems. Upon receiving the first control command, the air outlet will make corresponding adjustments. Based on the content of the control command, the air outlet may adjust parameters such as temperature, wind speed, and wind direction to adapt to the required airflow direction and volume. By sending the first control command to the corresponding air outlet, it is possible to precisely instruct that outlet to adjust accordingly based on the first parameters to meet the area's needs. This enables real-time response and adjustment to adapt to the time-varying needs of personnel activities.

[0086] During the execution of the first control command at the air outlet, the status and effect of the air outlet can be monitored through sensors and other means to ensure that the adjustment meets expectations. The feedback mechanism can transmit the adjusted air outlet parameter data back to the control system for further analysis and optimization.

[0087] The method provided in this application acquires and analyzes real-time pedestrian flow data in various areas of an indoor space, enabling real-time understanding of the distribution of people in those areas. By analyzing the real-time pedestrian flow data, analysis results for each area are obtained. Based on the pedestrian flow in different areas, first parameters for each air outlet of the central air conditioning system are generated, thereby achieving precise air conditioning control for each area, improving indoor air comfort and energy efficiency. First control commands are generated based on the first parameters and sent to the corresponding air outlets, causing the outlets to operate according to the indicated first parameters, achieving automated control. This reduces manual intervention and improves the automation level and operating efficiency of the air conditioning system. Through precise air conditioning control and intelligent adjustment based on pedestrian flow data in each area, it is possible to avoid fully activating the air conditioning, reducing unnecessary energy consumption and improving indoor air quality and comfort.

[0088] As an example, such as Figure 4 As shown, the group of people is located in Zone 1, ranked 1st, and their movement trend is from Zone 1 to Zone 2. Their activity type is sightseeing. The airflow direction from the vents in Zone 1 is the direction of the zone's exit, and the airflow strength is determined based on the type of sightseeing and the density of the group. The airflow direction from the vents in Zone 2 is the direction of the zone's entrance, and the airflow strength is determined based on the type of sightseeing and the density of the group.

[0089] In this embodiment of the application, after sending the first control command to the corresponding air outlet, the method further includes: obtaining usage information for each area at the next moment; updating the first parameter using the usage information to obtain the second parameter; generating a second control command based on the second parameter; and sending the second control command to the corresponding air outlet, wherein the air outlet is used to operate according to the second parameter indicated by the second control command.

[0090] Specifically, various sensors or monitoring devices are used to acquire usage information for each area at the next moment, such as the number of people, activity type, and temperature requirements. This information can be obtained through methods such as people flow statistics, temperature sensors, and access control systems. The acquired usage information is then used to update the original primary parameter. Based on the changing trends of the usage information and actual needs, algorithms or rules are used to adjust the value of the primary parameter, resulting in the updated secondary parameter. For example, the airflow or temperature setting of the air vents can be adjusted based on an increase or decrease in the number of people in the area.

[0091] Based on the updated second parameters, a second control command is generated. The second control command is then sent to the corresponding air outlet: the generated first control command is sent to the corresponding air outlet. Each air outlet corresponds to a specific area; by sending commands to the corresponding air outlet, the operating status and parameters of that air outlet can be controlled. The air outlet operates according to the second parameters indicated by the second control command, such as adjusting fan speed and temperature.

[0092] The method provided in this application can dynamically acquire usage information and update and adjust the parameters and control commands of the air conditioning system accordingly, thereby achieving precise, intelligent, and energy-saving air conditioning control, improving comfort and energy efficiency. At the same time, this solution also reduces manual intervention and enhances the user experience.

[0093] This embodiment also provides an air conditioning control device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0094] This embodiment provides an air conditioning control device, such as... Figure 5 As shown, it includes:

[0095] The acquisition module 21 is used to acquire real-time pedestrian flow data in various areas of the indoor space and analyze the real-time pedestrian flow data to obtain the corresponding analysis results for each area;

[0096] The processing module 22 is used to generate the first parameters corresponding to each air outlet of the central air conditioner using the analysis results, wherein each air outlet of the central air conditioner corresponds to each area of ​​the indoor space.

[0097] Generation module 23 is used to generate a first control command based on the first parameter;

[0098] The sending module 24 is used to send a first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command.

[0099] In this embodiment of the application, the acquisition module 21 includes:

[0100] The analysis unit is used to analyze real-time pedestrian flow data to obtain the pedestrian flow situation in the corresponding area;

[0101] The sorting unit is used to sort the flow of people in each area and obtain the ranking of each area.

[0102] The generation unit is used to generate analysis results based on pedestrian flow and regional ranking.

[0103] In this embodiment of the application, the analysis unit is used to extract personnel behavior data, personnel location, and personnel movement direction from real-time pedestrian flow data; determine the personnel density in the area using personnel location; determine the personnel flow trend in the area using personnel location and personnel movement direction; determine the personnel activity type in the area using personnel behavior data; and generate pedestrian flow information based on personnel density, personnel flow trend, and personnel activity type.

[0104] In this embodiment of the application, the processing module 22 includes:

[0105] The first processing unit is used to determine the air outlet direction based on regional ranking and population flow trends.

[0106] The second processing unit is used to determine the air outlet size based on the type of personnel activity and personnel density.

[0107] The building unit is used to generate the first parameter based on the air outlet direction and air outlet size.

[0108] In this embodiment of the application, the first processing unit is used to select the region with a regional ranking greater than the preset ranking as the target region; obtain the orientation information of the target region in the indoor space, and generate the initial air outlet direction based on the orientation information; and adjust the initial air outlet direction using the flow trend of people to obtain the air outlet direction.

[0109] In this embodiment of the application, the second processing unit is used to obtain the initial air outlet size corresponding to the activity type based on the mapping relationship between the preset activity type and the air outlet size; and to adjust the initial air outlet size using the personnel density to obtain the air outlet size.

[0110] In this embodiment of the application, the device further includes: an update unit, configured to acquire usage information corresponding to each region at the next moment; update the first parameter using the usage information to obtain a second parameter; generate a second control command based on the second parameter; and send the second control command to the corresponding air outlet, wherein the air outlet is used to operate according to the second parameter indicated by the second control command.

[0111] This application embodiment acquires and analyzes real-time pedestrian flow data in various areas of an indoor space, enabling real-time understanding of the distribution of people in those areas. By analyzing the real-time pedestrian flow data, analysis results for each area are obtained. Based on the pedestrian flow in different areas, first parameters for each air outlet of the central air conditioning system are generated, thereby achieving precise air conditioning control for each area, improving indoor air comfort and energy efficiency. First control commands are generated based on the first parameters and sent to the corresponding air outlets, causing the outlets to operate according to the indicated first parameters, achieving automated control. This reduces manual intervention and improves the automation level and operating efficiency of the air conditioning system. Through precise air conditioning control and intelligent adjustment based on pedestrian flow data in each area, it is possible to avoid fully activating the air conditioning and reduce unnecessary energy consumption.

[0112] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an optional embodiment of the present invention, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer 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).

[0113] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0114] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0115] This application embodiment acquires and analyzes real-time pedestrian flow data in various areas of an indoor space, enabling real-time understanding of the distribution of people in those areas. By analyzing the real-time pedestrian flow data, analysis results for each area are obtained. Based on the pedestrian flow in different areas, first parameters for each air outlet of the central air conditioning system are generated, thereby achieving precise air conditioning control for each area, improving indoor air comfort and energy efficiency. First control commands are generated based on the first parameters and sent to the corresponding air outlets, causing the outlets to operate according to the indicated first parameters, achieving automated control. This reduces manual intervention and improves the automation level and operating efficiency of the air conditioning system. Through precise air conditioning control and intelligent adjustment based on pedestrian flow data in each area, it is possible to avoid fully activating the air conditioning and reduce unnecessary energy consumption.

[0116] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device as shown by a landing page for an app. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0117] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0118] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0119] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0120] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An air conditioning control method, characterized in that, The method is applied to a server, and the method includes: Real-time pedestrian flow data for each area in an indoor space is acquired, and the analysis results for each area are obtained by analyzing the real-time pedestrian flow data. The analysis results are used to generate first parameters corresponding to each air outlet of the central air conditioner, wherein each air outlet of the central air conditioner corresponds to each area of ​​the indoor space. Generate a first control command based on the first parameter; Send the first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command; The step of analyzing the real-time pedestrian flow data to obtain analysis results for each of the regions includes: analyzing the real-time pedestrian flow data to obtain the pedestrian flow situation for each region; sorting the pedestrian flow situation for each region to obtain the region ranking for each region; and generating the analysis results based on the pedestrian flow situation and the region ranking. The analysis of the real-time pedestrian flow data to obtain the pedestrian flow situation corresponding to the area includes: Extract pedestrian behavior data, pedestrian location, and pedestrian movement direction from the real-time pedestrian flow data; determine the pedestrian density in the area using the pedestrian location; determine the pedestrian flow trend in the area using the pedestrian location and pedestrian movement direction; determine the pedestrian activity type in the area using the pedestrian behavior data; and generate the pedestrian flow situation based on the pedestrian density, pedestrian flow trend, and pedestrian activity type. The step of generating the first parameter corresponding to each air outlet of the central air conditioning system using the analysis results includes: determining the air outlet direction based on the regional ranking and the personnel flow trend; determining the air outlet size based on the personnel activity type and the personnel density; and generating the first parameter based on the air outlet direction and the air outlet size.

2. The method according to claim 1, characterized in that, Determining the airflow direction based on the regional ranking and the population flow trend includes: The regions whose regional ranking is greater than the preset ranking are designated as target regions. Obtain the orientation information of the target area in the indoor space, and generate an initial airflow direction based on the orientation information; The initial airflow direction is adjusted using the population flow trend to obtain the final airflow direction.

3. The method according to claim 1, characterized in that, The step of determining the airflow size based on the type of personnel activity and the personnel density includes: Based on the mapping relationship between preset activity types and air outlet size, the initial air outlet size corresponding to the activity type of the person is obtained; The initial airflow size is adjusted based on the personnel density to obtain the airflow size.

4. The method according to claim 1, characterized in that, After sending the first control command to the corresponding air outlet, the method further includes: Obtain usage information for each region at the next time step; The first parameter is updated using the usage information to obtain the second parameter; A second control command is generated based on the second parameter, and the second control command is sent to the corresponding air outlet, wherein the air outlet is used to operate according to the second parameter indicated by the second control command.

5. An air conditioning control device, characterized in that, The device includes: The acquisition module is used to acquire real-time pedestrian flow data in various areas of the indoor space and analyze the real-time pedestrian flow data to obtain the analysis results corresponding to each area. The processing module is used to generate first parameters corresponding to each air outlet of the central air conditioner using the analysis results, wherein each air outlet of the central air conditioner corresponds to each area of ​​the indoor space. The generation module is used to generate a first control instruction based on the first parameter; A sending module is used to send the first control command to the corresponding air outlet, wherein the air outlet is used to operate according to the first parameter indicated by the first control command; The acquisition module includes: The analysis unit is used to extract people behavior data, people location, and people movement direction from real-time people flow data; determine people density in an area using people location; determine people flow trend in an area using people location and people movement direction; determine people activity type in an area using people behavior data; and generate people flow information based on people density, people flow trend, and people activity type. The sorting unit is used to sort the flow of people in each area and obtain the ranking of each area. The generation unit is used to generate analysis results based on pedestrian flow and regional ranking. The processing module includes: The first processing unit is used to determine the air outlet direction based on regional ranking and population flow trends. The second processing unit is used to determine the air outlet size based on the type of personnel activity and personnel density. The building unit is used to generate the first parameter based on the air outlet direction and air outlet size.

6. An electronic device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the method of any one of claims 1 to 4.

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