Environment sensing intelligent fan lamp control method, device, equipment and medium

Abstract

The invention relates to an environment sensing intelligent fan lamp control method and device, equipment and a medium. The method comprises the steps that infrared sensing data are acquired, and personnel position information is acquired according to the infrared sensing data; acquiring environment temperature data, and inputting the environment temperature data and the personnel position information into an environment wind power curve preset by a system to obtain wind power calculation data; acquiring environment gas data, and when marked gas data in the environment gas data reaches a marked gas threshold value set by a system, generating perfume output dose data according to the wind power calculation data; acquiring environment brightness data, and inputting the environment brightness data and the personnel position information into a brightness calculation model preset by the system to obtain brightness calculation data; and generating a corresponding fan lamp adjusting instruction according to the wind power calculation data, the perfume output dose data and the brightness calculation data. The fan lamp has the effect of improving the environment perception capability of the fan lamp.

Description

Technical Field

[0001] The present invention relates to the technical field of fan lamps, and in particular to an environment-aware intelligent fan lamp control method, device, equipment and medium. Background Art

[0002] At present, with the continuous development of smart home technology, smart fan lights, as a smart home product that integrates lighting and ventilation, are becoming more and more popular among consumers.

[0003] Existing, traditional smart fan lights usually only have basic lighting and fan speed adjustment functions, lack the ability to perceive and respond to environmental parameters, and require users to manually adjust according to different environments. Traditional smart fan lights also lack integrated perfume spray functions and cannot meet users' needs for space fragrance. It is difficult to provide a personalized user experience based on user needs.

[0004] The above-mentioned prior art solutions have the following defects: the traditional intelligent fan lights have poor perception and response capabilities to the environment, so there is room for improvement. Summary of the invention

[0005] In order to improve the environmental perception effect of a fan light, the present application provides an environmental perception intelligent fan light control method, device, equipment and medium.

[0006] The above-mentioned invention objective of the present application is achieved through the following technical solutions: An environment-aware intelligent fan light control method, the environment-aware intelligent fan light control method comprising: Acquire infrared sensor data, and acquire personnel location information according to the infrared sensor data; Acquire ambient temperature data, input the ambient temperature data and personnel location information into an ambient wind force curve preset by the system, and obtain wind force calculation data; Acquire environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; Acquire environmental brightness data, and input the environmental brightness data and personnel location information into a brightness calculation model preset by the system to obtain brightness calculation data; A corresponding fan light adjustment instruction is generated according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0007] By adopting the above technical solution, since traditional smart fan lights usually only have basic lighting and fan speed adjustment functions, and lack the ability to perceive and respond to environmental parameters, users are required to manually adjust according to different environments, which makes it difficult to provide personalized user experience according to user needs. At the same time, the existing smart fan lights lack integrated perfume spraying functions and cannot meet users' needs for space fragrance. Therefore, when the infrared sensor data is obtained, the present application will obtain personnel location information based on the infrared sensor data to facilitate the subsequent adjustment of relevant parameters of the fan light based on the personnel location and other environmental factors; by obtaining ambient temperature data, the ambient temperature data and personnel location information are input into the system preset ambient wind force curve to obtain wind force calculation data, which can reasonably calculate the fan wind force according to the ambient temperature and personnel position, improve the wind force energy efficiency and user experience, and also reduce energy consumption and unnecessary waste; by obtaining ambient gas data, when the marker gas data in the ambient gas data reaches the marker gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data, which can monitor the concentration of specific marker gas, and when it exceeds the set threshold, it will automatically trigger the meter. The system can calculate the spray volume of perfume to generate subsequent perfume spraying instructions, thereby improving air quality and further improving the user experience; by obtaining ambient brightness data, the ambient brightness data and personnel location information are input into the system preset brightness calculation model to obtain brightness calculation data, and the brightness of the light can be intelligently calculated according to the personnel location, thereby providing users with a suitable lighting environment; by combining multiple data for comprehensive calculation, the system can generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements; by generating corresponding fan light adjustment instructions based on wind force calculation data, perfume output dosage data and brightness calculation data, it can combine multiple data for comprehensive calculation to generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements, and automatically adjust the status of the equipment without human intervention, thereby improving the convenience of life and work.

[0008] In a preferred example, the present application can be further configured as follows: the construction of the environmental wind force curve specifically includes: Acquire temperature and wind test data, generate a first wind data set according to the temperature and wind test data, and analyze the first wind data set using a linear regression algorithm to obtain a first wind linear curve; Acquire location wind force test data, generate a second wind force data set according to the location wind force test data, and analyze the second wind force data set using a linear regression algorithm to obtain a second wind force linear curve; The first wind linear curve and the second wind linear curve are combined to obtain the environmental wind curve.

[0009] By adopting the above technical solution, by obtaining temperature and wind test data, a first wind data set is generated according to the temperature and wind test data, and a linear regression algorithm is used to analyze the first wind data set to obtain a first wind linear curve, which can linearly analyze the relationship between ambient temperature and required wind force, thereby providing more accurate wind force calculation data and creating a better and more comfortable environment for users; by obtaining position wind test data, a second wind data set is generated according to the position wind test data, and a linear regression algorithm is used to analyze the second wind data set to obtain a second wind linear curve, which can obtain the fan wind force data required by personnel at different positions, thereby improving the control of wind force in different areas and further improving the user experience. At the same time, the relationship curve obtained according to the linear regression algorithm can better adapt to environmental changes, thereby improving the stability of the system and reducing the probability of errors.

[0010] In a preferred example, the present application can be further configured as follows: the environmental gas data is acquired, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data, specifically including: The output dosage of the perfume is calculated according to the system's built-in perfume dosage calculation formula Q=(R+V)*t, where Q is the output dosage of the perfume, R is the basic spraying rate of the perfume, V is the wind force calculation data, and t is the spraying time interval.

[0011] By adopting the above technical solution, the output dosage of the perfume is calculated according to the system's built-in perfume dosage calculation formula Q=(R+V)*t. The output dosage of the perfume can be reasonably calculated according to actual needs to avoid excessive use, thereby saving perfume costs and reducing the frequency of replenishment. At the same time, the output amount of the perfume can be automatically controlled, thereby reducing the user's manual intervention and providing a more convenient user experience.

[0012] In a preferred example, the present application can be further configured as follows: the acquisition of the ambient brightness data, inputting the ambient brightness data and the personnel location information into a brightness calculation model preset by the system, and obtaining the brightness calculation data, specifically includes: Input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, analyze the personnel location and behavior pattern according to the brightness calculation model, and obtain the analysis result after the analysis is completed; Generate corresponding brightness calculation data according to the analysis result.

[0013] By adopting the above technical solution, by inputting the ambient brightness data and personnel location information into the system's preset brightness calculation model, analyzing the personnel position and behavior pattern according to the brightness calculation model, and obtaining the analysis results after the analysis, the lighting can be intelligently adjusted according to the personnel position and behavior pattern to provide a more adaptable and comfortable lighting environment, thereby more effectively adjusting the lighting equipment, reducing unnecessary energy consumption, and achieving effective use of energy. At the same time, it is conducive to providing a lighting experience that better meets user needs.

[0014] In a preferred example, the present application can be further configured as follows: the construction of the brightness calculation model specifically includes: Acquire historical personnel location data and corresponding equipment brightness data and generate training preparation data, filter the training preparation data according to the personnel distance threshold set by the system, and obtain a model training data set; The machine learning model is iteratively trained according to the model training data set to generate the brightness calculation model.

[0015] By adopting the above technical solution, by obtaining historical personnel location data and corresponding equipment brightness data and generating training preparation data, the training preparation data is screened according to the personnel distance threshold set by the system to obtain a model training data set, which can reduce the dimension and scope of the training preparation data, and more accurately control the data range required for model training, thereby improving the efficiency and accuracy of subsequent model training; by iteratively training the machine learning model according to the model training data set to generate a brightness calculation model, the machine learning model can continuously understand the relationship between the data in the model training data set, so that it can respond more quickly when faced with real situations.

[0016] In a preferred example, the present application may be further configured as follows: after generating the corresponding fan light adjustment instruction according to the wind force calculation data, the perfume output dosage data and the brightness calculation data, it also includes: Controlling the device to make corresponding adjustments according to the fan light adjustment instruction, and obtaining real-time data of the adjusted device; The real-time data of the device is compared with the adjustment data corresponding to the fan light adjustment instruction, and when the comparison result is that the real-time data of the device is different from the adjustment data, a device adjustment abnormality message is generated.

[0017] By adopting the above technical solution, by controlling the device to make corresponding adjustments according to the fan light adjustment instruction and obtaining the real-time data of the adjusted device, it is possible to monitor the status changes of the device in real time, and promptly discover and feedback any abnormal conditions that occur; by comparing the real-time data of the device with the adjustment data corresponding to the fan light adjustment instruction, when the comparison result is that the real-time data of the device is different from the adjustment data, an abnormal device adjustment message is generated, which can provide timely fault warnings and help to quickly troubleshoot and repair faults, thereby improving the stability and reliability of the equipment, reducing the risk of equipment failures due to abnormal conditions, and at the same time, providing a better user experience and reducing the inconvenience caused by equipment problems.

[0018] The second object of the invention is achieved by the following technical solutions: An environment-aware intelligent fan light control device, the environment-aware intelligent fan light control device comprising: A location acquisition module, used to acquire infrared sensor data, and acquire personnel location information according to the infrared sensor data; A wind force calculation module is used to obtain ambient temperature data, input the ambient temperature data and personnel location information into an ambient wind force curve preset by the system, and obtain wind force calculation data; A dosage calculation module is used to obtain environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; A brightness calculation module is used to obtain environmental brightness data, input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, and obtain brightness calculation data; The instruction generation module is used to generate corresponding fan light adjustment instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0019] By adopting the above technical solution, since traditional smart fan lights usually only have basic lighting and fan speed adjustment functions, and lack the ability to perceive and respond to environmental parameters, users are required to manually adjust according to different environments, which makes it difficult to provide personalized user experience according to user needs. At the same time, the existing smart fan lights lack integrated perfume spraying functions and cannot meet users' needs for space fragrance. Therefore, when the infrared sensor data is obtained, the present application will obtain personnel location information based on the infrared sensor data to facilitate the subsequent adjustment of relevant parameters of the fan light based on the personnel location and other environmental factors; by obtaining ambient temperature data, the ambient temperature data and personnel location information are input into the system preset ambient wind force curve to obtain wind force calculation data, which can reasonably calculate the fan wind force according to the ambient temperature and personnel position, improve the wind force energy efficiency and user experience, and also reduce energy consumption and unnecessary waste; by obtaining ambient gas data, when the marker gas data in the ambient gas data reaches the marker gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data, which can monitor the concentration of specific marker gas, and when it exceeds the set threshold, it will automatically trigger the meter. The system can calculate the spray volume of perfume to generate subsequent perfume spraying instructions, thereby improving air quality and further improving the user experience; by obtaining ambient brightness data, the ambient brightness data and personnel location information are input into the system preset brightness calculation model to obtain brightness calculation data, and the brightness of the light can be intelligently calculated according to the personnel location, thereby providing users with a suitable lighting environment; by combining multiple data for comprehensive calculation, the system can generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements; by generating corresponding fan light adjustment instructions based on wind force calculation data, perfume output dosage data and brightness calculation data, it can combine multiple data for comprehensive calculation to generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements, and automatically adjust the status of the equipment without human intervention, thereby improving the convenience of life and work.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned environment-aware intelligent fan light control method when executing the computer program.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned environment-aware intelligent fan light control method.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. By acquiring temperature and wind test data, a first wind data set is generated according to the temperature and wind test data, and a linear regression algorithm is used to analyze the first wind data set to obtain a first wind linear curve, which can linearly analyze the relationship between ambient temperature and required wind force, thereby providing more accurate wind force calculation data and creating a better and more comfortable environment for users; by acquiring position wind test data, a second wind data set is generated according to the position wind test data, and a linear regression algorithm is used to analyze the second wind data set to obtain a second wind linear curve, which can obtain the fan wind force data required by personnel at different positions, thereby improving the control of wind force at different regional locations, and further improving the user experience. At the same time, the relationship curve obtained according to the linear regression algorithm can better adapt to environmental changes, thereby improving the stability of the system and reducing the probability of errors; 2. By obtaining historical personnel location data and corresponding equipment brightness data and generating training preparation data, the training preparation data is screened according to the personnel distance threshold set by the system to obtain the model training data set, which can reduce the dimension and range of the training preparation data and more accurately control the data range required for model training, thereby improving the efficiency and accuracy of subsequent model training; by iteratively training the machine learning model according to the model training data set and generating a brightness calculation model, the machine learning model can continuously understand the relationship between the data in the model training data set, so that it can respond faster when faced with real situations; 3. By controlling the device to make corresponding adjustments according to the fan light adjustment instructions and obtaining the real-time data of the adjusted device, the device status changes can be monitored in real time, and abnormal situations can be discovered and fed back in time; by comparing the device real-time data with the adjustment data corresponding to the fan light adjustment instructions, when the comparison result is that the device real-time data is different from the adjustment data, a device adjustment abnormality message is generated, which can provide timely fault warnings and help to quickly troubleshoot and repair faults, thereby improving the stability and reliability of the equipment, reducing the risk of equipment failures caused by abnormal conditions, and at the same time, providing a better user experience and reducing the inconvenience caused by equipment problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of an environment-aware intelligent fan light control method in an embodiment of the present application; Figure 2 It is a flowchart for realizing the construction of the environmental wind force curve in the environmental perception intelligent fan light control method in one embodiment of the present application; Figure 3 It is a flowchart for implementing step S30 in the environment-aware intelligent fan light control method in one embodiment of the present application; Figure 4 is a flowchart for implementing step S40 in the environment-aware intelligent fan light control method in one embodiment of the present application; Figure 5 It is a flowchart for implementing the construction of a brightness calculation model in the environment-aware intelligent fan light control method in one embodiment of the present application; Figure 6 is another implementation flow chart of the environment-aware intelligent fan light control method in one embodiment of the present application; Figure 7 This is a principle block diagram of an environment-aware intelligent fan light control device in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses an environment-aware intelligent fan light control method, which specifically includes the following steps: S10: Acquire infrared sensor data, and acquire personnel location information according to the infrared sensor data.

[0026] In this embodiment, the infrared sensor data refers to the infrared data collected by the infrared sensor installed in the device. The personnel position information refers to the distance data between the personnel and the fan light.

[0027] Specifically, infrared sensor data within a range is acquired in real time through an infrared sensor installed in the fan light, and personnel position information in the infrared sensor data is acquired with the fan light as the center.

[0028] S20: Acquire ambient temperature data, input the ambient temperature data and personnel location information into the ambient wind force curve preset by the system, and obtain wind force calculation data.

[0029] In this embodiment, the ambient temperature data refers to the temperature data detected by the temperature sensor. The ambient wind force curve refers to the curve used to calculate the wind force that the fan light needs to adjust. The wind force calculation data refers to the wind force that the fan light needs to adjust.

[0030] Specifically, the ambient temperature of the area where the fan light is located is obtained through a temperature sensor, and the ambient temperature and personnel location information are input into the environmental wind curve that has been entered and set in advance by the system for calculation, and the wind force size suitable for the current environment and personnel location is obtained as wind calculation data.

[0031] S30: Acquire environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data.

[0032] In this embodiment, the environmental gas data refers to the data of different gas types and contents in the environment detected by the gas sensor. The marked gas data refers to the gas data pre-entered and calibrated by the system. The perfume output dosage data refers to the dosage of the perfume sprayed.

[0033] Specifically, different gas types and contents in the environment are obtained as environmental gas data through gas sensors, and compared with the marker gas data. For example, if the marker gas data is hydrogen sulfide, ammonia, methyl mercaptan and other common odor gases in life, when the content of the marker gas data reaches the marker gas threshold set by the system, it is necessary to spray perfume to improve the indoor odor. Before that, it is necessary to calculate the amount of perfume spray needed at the current wind volume as the perfume output dosage data.

[0034] S40: Acquire environmental brightness data, input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, and obtain brightness calculation data.

[0035] In this embodiment, the ambient brightness data refers to the ambient brightness detected by the brightness sensor. The brightness calculation model refers to a model used to calculate the lighting brightness required by the fan lamp. The brightness calculation data refers to the lighting brightness that the fan lamp needs to adjust.

[0036] Specifically, the current ambient brightness is obtained through a brightness sensor, and the ambient brightness and personnel location information are input into a brightness calculation model to analyze the more suitable lighting brightness under the current ambient brightness and the different usage requirements of users in different locations, and obtain brightness calculation data after the analysis is completed.

[0037] S50: Generate a corresponding fan light adjustment instruction according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0038] In this embodiment, the fan light adjustment instruction refers to an instruction for controlling the brightness and wind speed of the fan light.

[0039] Specifically, the system will obtain wind force calculation data, perfume output dosage data and brightness calculation data in real time, and when the data is obtained, it will generate fan light adjustment instructions corresponding to the data based on the obtained data. For example, when the wind force calculation data is obtained, a wind force adjustment instruction is generated to control the fan light to adjust the wind force of the fan to the size of the wind force calculation data.

[0040] In this embodiment, since the traditional intelligent fan lamp usually only has basic lighting and fan speed adjustment functions, and lacks the ability to perceive and respond to environmental parameters, users are required to manually adjust according to different environments, which makes it difficult to provide personalized user experience according to user needs. At the same time, the existing intelligent fan lamp lacks an integrated perfume spray function and cannot meet the user's demand for space fragrance. Therefore, when the infrared sensor data is obtained, the present application will obtain the personnel position information according to the infrared sensor data to facilitate the subsequent adjustment of the relevant parameters of the fan lamp according to the personnel position and other environmental factors; by obtaining the ambient temperature data, the ambient temperature data and the personnel position information are input into the system preset ambient wind force curve to obtain the wind force calculation data, which can reasonably calculate the fan wind force according to the ambient temperature and the personnel position, improve the wind force energy efficiency and user experience, and also reduce energy consumption and unnecessary waste; by obtaining the ambient gas data, when the marker gas data in the ambient gas data reaches the marker gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data, which can monitor the concentration of the specific marker gas, and when it exceeds the set threshold, it will automatically trigger the meter. The system can calculate the spray volume of perfume to generate subsequent perfume spraying instructions, thereby improving air quality and further improving the user experience; by obtaining ambient brightness data, the ambient brightness data and personnel location information are input into the system preset brightness calculation model to obtain brightness calculation data, and the brightness of the light can be intelligently calculated according to the personnel location, thereby providing users with a suitable lighting environment; by combining multiple data for comprehensive calculation, the system can generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements; by generating corresponding fan light adjustment instructions based on wind force calculation data, perfume output dosage data and brightness calculation data, it can combine multiple data for comprehensive calculation to generate personalized fan light adjustment instructions to provide a customized experience based on user preferences and environmental requirements, and automatically adjust the status of the equipment without human intervention, thereby improving the convenience of life and work.

[0041] In one embodiment, if Figure 2 As shown, in step S20, i.e., constructing the environmental wind force curve, specifically includes: S201: Acquire temperature and wind test data, generate a first wind data set according to the temperature and wind test data, and use a linear regression algorithm to analyze the first wind data set to obtain a first wind linear curve.

[0042] In this embodiment, the temperature and wind test data refers to the test data of different temperatures and corresponding wind forces of the equipment during the test phase. The first wind force data set refers to the set of temperature and wind force test data. The first wind force linear curve refers to the relationship curve between temperature and wind force.

[0043] Specifically, during the test phase, the test personnel will continuously adjust the wind force of the fan under the fan at different ambient temperatures, and detect the body surface temperature of the test personnel. The ambient temperature and wind force corresponding to the temperature that is more comfortable for the human body are used as temperature and wind test data, and are packaged as a first wind force data set. Subsequently, a linear regression algorithm is used to analyze the data set to obtain the linear relationship between different ambient temperatures and the required wind force, and a first wind force linear curve is generated based on the linear relationship.

[0044] S202: Acquire location wind force test data, generate a second wind force data set according to the location wind force test data, and use a linear regression algorithm to analyze the second wind force data set to obtain a second wind force linear curve.

[0045] Specifically, during the test phase, the wind force of the fan will be continuously adjusted under the same ambient temperature and the body surface temperature of people at different positions away from the equipment will be obtained. The position and wind force corresponding to the more comfortable temperature for the human body will be selected as the wind force test data, and the data will be encapsulated as the second wind force data set. Subsequently, a linear regression algorithm is used to analyze the data set to obtain the linear relationship between different positions and the required wind force, and a second wind force linear curve is generated based on the linear relationship.

[0046] S203: Combining the first wind linear curve and the second wind linear curve to obtain an environmental wind curve.

[0047] Specifically, taking wind force as a common item, the first wind force linear curve and the second wind force linear curve are combined to obtain an environmental wind force curve.

[0048] In one embodiment, if Figure 3 As shown, in step S30, the ambient gas data is obtained. When the marked gas data in the ambient gas data reaches the marked gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data, which specifically includes: S31: The output dose of the perfume is calculated according to the system's built-in perfume dose calculation formula Q=(R+V)*t, where Q is the output dose of the perfume, R is the basic spraying rate of the perfume, V is the wind force calculation data, and t is the spraying time interval.

[0049] Specifically, the device is equipped with a perfume sprayer that can spray perfume at intervals. When the device is needed to spray perfume, the dosage required will be calculated according to the formula set in advance within the system, so as to reduce the waste of perfume while better improving the air atmosphere.

[0050] In one embodiment, if Figure 4As shown, in step S40, the ambient brightness data is obtained, and the ambient brightness data and the personnel position information are input into the brightness calculation model preset by the system to obtain the brightness calculation data, which specifically includes: S41: Inputting the environmental brightness data and the personnel position information into the brightness calculation model preset by the system, analyzing the personnel position and behavior pattern according to the brightness calculation model, and obtaining the analysis result after the analysis is completed.

[0051] Specifically, the system has a pre-trained brightness calculation model that is used to intelligently calculate the brightness required by the lamp. When the brightness calculation model receives ambient brightness data and personnel location information, it will analyze the personnel location information and obtain the brightness that is more suitable for personnel to use at that distance as the analysis result.

[0052] S42: Generate corresponding brightness calculation data according to the analysis result.

[0053] Specifically, the ambient brightness data is compensated according to the analysis result, that is, the brightness that is more suitable for use by personnel, and combined with the ambient brightness data to obtain the brightness calculation data.

[0054] In one embodiment, if Figure 5 As shown, in step S40, the construction of the brightness calculation model specifically includes: S401: Obtain historical personnel location data and corresponding equipment brightness data and generate training preparation data, filter the training preparation data according to the personnel distance threshold set by the system, and obtain a model training data set.

[0055] Specifically, during the testing phase, the brightness of the light will be continuously adjusted according to the position of the personnel, and the brightness data of the personnel's current position will be obtained. The position data corresponding to the brightness data that is more suitable for personnel use will be selected as the historical personnel position data, and the brightness of the equipment light will be selected as the equipment brightness data, and encapsulated as training preparation data. Subsequently, the training preparation data will be screened and limited according to the personnel distance threshold set by the system. For example, when the brightness of the light has reached the maximum value, the distance will be used as the personnel distance threshold. At this time, when the personnel is farther away, the light is still at the maximum value. The farther distance will be removed as a redundant part, reducing the factors affecting model training. At the same time, it can also reduce the amount of data, improve the efficiency of model training, and use the screened data set as the model training data set.

[0056] S402: Iteratively train the machine learning model according to the model training data set to generate a brightness calculation model.

[0057] Specifically, the machine learning model is iteratively trained according to the model training data set, so that the machine learning model continuously understands the relationship between different distances and required brightness, and stops the iteration when the accuracy between the device brightness data output after inputting the ambient brightness and the position of the personnel and the established device brightness reaches 95%, thereby obtaining the brightness calculation model.

[0058] In one embodiment, if Figure 6 As shown, after step S50, that is, after generating the corresponding fan light adjustment instruction according to the wind force calculation data, the perfume output dosage data and the brightness calculation data, it also includes: S501: Control the device to make corresponding adjustments according to the fan light adjustment instruction, and obtain the real-time data of the adjusted device.

[0059] Specifically, after generating corresponding device control instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data, the response data of the fan light is adjusted, and after the adjustment is completed, the real-time data of the device is obtained.

[0060] S502: Compare the real-time data of the device with the adjustment data corresponding to the fan light adjustment instruction, and when the comparison result is that the real-time data of the device is different from the adjustment data, generate a device adjustment abnormality message.

[0061] In this embodiment, the device adjustment abnormality message refers to a message triggered when the device adjustment function is abnormal.

[0062] Specifically, the acquired real-time data of the device is compared with the adjustment data that needs to be adjusted. When the two are different, it means that the system has set the adjustment data but the device has not been adjusted to the data. At this time, the adjustment function of the device is abnormal, triggering the device adjustment abnormality message, reminding the user that the device has an abnormality and needs to be processed in time.

[0063] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0064] In one embodiment, an environment-aware intelligent fan light control device is provided, and the environment-aware intelligent fan light control device corresponds one-to-one with the environment-aware intelligent fan light control method in the above embodiment. Figure 7 As shown, the environment-aware intelligent fan light control device includes a position acquisition module, a wind force calculation module, a dosage calculation module, a brightness calculation module, and an instruction generation module. The detailed description of each functional module is as follows: A location acquisition module is used to acquire infrared sensor data and obtain personnel location information based on the infrared sensor data; The wind force calculation module is used to obtain the ambient temperature data, input the ambient temperature data and the personnel position information into the ambient wind force curve preset by the system, and obtain the wind force calculation data; The dosage calculation module is used to obtain the environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, the perfume output dosage data is generated according to the wind force calculation data; The brightness calculation module is used to obtain the ambient brightness data, input the ambient brightness data and the personnel position information into the brightness calculation model preset by the system, and obtain the brightness calculation data; The instruction generation module is used to generate corresponding fan light adjustment instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0065] Optionally, the construction of the environmental wind curve includes: A temperature processing module is used to obtain temperature and wind test data, generate a first wind data set according to the temperature and wind test data, and analyze the first wind data set using a linear regression algorithm to obtain a first wind linear curve; A position processing module, used for acquiring position wind force test data, generating a second wind force data set according to the position wind force test data, and analyzing the second wind force data set by using a linear regression algorithm to obtain a second wind force linear curve; The curve generating module is used to combine the first wind linear curve and the second wind linear curve to obtain an environmental wind curve.

[0066] Optionally, the dose calculation module specifically includes: The dosage calculation submodule is used to calculate the output dosage of the perfume according to the system's built-in perfume dosage calculation formula Q=(R+V)*t, where Q is the output dosage of the perfume, R is the basic spraying rate of the perfume, V is the wind force calculation data, and t is the spraying time interval.

[0067] Optionally, the brightness calculation module specifically includes: The position analysis submodule is used to input the ambient brightness data and the personnel position information into the brightness calculation model preset by the system, analyze the personnel position and behavior pattern according to the brightness calculation model, and obtain the analysis results after the analysis is completed; The brightness calculation submodule is used to generate corresponding brightness calculation data according to the analysis results.

[0068] Optionally, the construction of a brightness calculation model includes: The data preparation module is used to obtain historical personnel location data and corresponding equipment brightness data and generate training preparation data, and filter the training preparation data according to the personnel distance threshold set by the system to obtain the model training data set; The model building module is used to iteratively train the machine learning model according to the model training data set to generate a brightness calculation model.

[0069] Optionally, the environment-aware intelligent fan light control method further includes: The data monitoring module is used to control the device to make corresponding adjustments according to the fan light adjustment instructions and obtain the real-time data of the adjusted device; The data comparison module is used to compare the real-time data of the device with the adjustment data corresponding to the fan light adjustment instruction. When the comparison result is that the real-time data of the device is different from the adjustment data, an abnormal device adjustment message is generated.

[0070] For the specific definition of the environment-aware intelligent fan light control device, please refer to the definition of the environment-aware intelligent fan light control method above, which will not be repeated here. Each module in the above-mentioned environment-aware intelligent fan light control device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0071] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. . The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an environment-aware intelligent fan light control method is implemented.

[0072] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Acquire infrared sensor data, and obtain personnel location information based on the infrared sensor data; Obtain ambient temperature data, input the ambient temperature data and personnel location information into the ambient wind force curve preset by the system, and obtain wind force calculation data; Acquire environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; Acquire environmental brightness data, input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, and obtain brightness calculation data; Generate corresponding fan light adjustment instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0073] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Acquire infrared sensor data, and obtain personnel location information based on the infrared sensor data; Obtain ambient temperature data, input the ambient temperature data and personnel location information into the ambient wind force curve preset by the system, and obtain wind force calculation data; Acquire environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; Acquire environmental brightness data, input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, and obtain brightness calculation data; Generate corresponding fan light adjustment instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

[0074] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0075] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0076] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An environment-aware intelligent fan light control method, characterized in that: The environment-aware intelligent fan light control method comprises: Acquire infrared sensor data, and acquire personnel location information according to the infrared sensor data; Acquire ambient temperature data, input the ambient temperature data and personnel location information into an ambient wind force curve preset by the system, and obtain wind force calculation data; Acquire environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; Acquire environmental brightness data, and input the environmental brightness data and personnel location information into a brightness calculation model preset by the system to obtain brightness calculation data; A corresponding fan light adjustment instruction is generated according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

2. The environment-aware intelligent fan light control method according to claim 1, characterized in that: The construction of the environmental wind force curve specifically includes: Acquire temperature and wind test data, generate a first wind data set according to the temperature and wind test data, and analyze the first wind data set using a linear regression algorithm to obtain a first wind linear curve; Acquire location wind force test data, generate a second wind force data set according to the location wind force test data, and analyze the second wind force data set using a linear regression algorithm to obtain a second wind force linear curve; The first wind linear curve and the second wind linear curve are combined to obtain the environmental wind curve.

3. The environment-aware intelligent fan light control method according to claim 1, characterized in that: The step of acquiring the ambient gas data and generating the perfume output dosage data according to the wind force calculation data when the marked gas data in the ambient gas data reaches the marked gas threshold set by the system specifically includes: The output dosage of the perfume is calculated according to the system's built-in perfume dosage calculation formula Q=(R+V)*t, where Q is the output dosage of the perfume, R is the basic spraying rate of the perfume, V is the wind force calculation data, and t is the spraying time interval.

4. The environment-aware intelligent fan light control method according to claim 1, characterized in that: The step of obtaining the ambient brightness data and inputting the ambient brightness data and the personnel position information into a brightness calculation model preset by the system to obtain the brightness calculation data specifically includes: Input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, analyze the personnel location and behavior pattern according to the brightness calculation model, and obtain the analysis result after the analysis is completed; Generate corresponding brightness calculation data according to the analysis result.

5. The environment-aware intelligent fan light control method according to claim 4, characterized in that: The construction of the brightness calculation model specifically includes: Acquire historical personnel location data and corresponding equipment brightness data and generate training preparation data, filter the training preparation data according to the personnel distance threshold set by the system, and obtain a model training data set; The machine learning model is iteratively trained according to the model training data set to generate the brightness calculation model.

6. The environment-aware intelligent fan light control method according to claim 1, characterized in that: After generating the corresponding fan light adjustment instruction according to the wind force calculation data, the perfume output dosage data and the brightness calculation data, the method further includes: Controlling the device to make corresponding adjustments according to the fan light adjustment instruction, and obtaining real-time data of the adjusted device; The real-time data of the device is compared with the adjustment data corresponding to the fan light adjustment instruction, and when the comparison result is that the real-time data of the device is different from the adjustment data, a device adjustment abnormality message is generated.

7. An environment-aware intelligent fan light control device, characterized in that: The environment-aware intelligent fan light control device comprises: A location acquisition module, used to acquire infrared sensor data, and acquire personnel location information according to the infrared sensor data; A wind force calculation module is used to obtain ambient temperature data, input the ambient temperature data and personnel location information into an ambient wind force curve preset by the system, and obtain wind force calculation data; A dosage calculation module is used to obtain environmental gas data, and when the marked gas data in the environmental gas data reaches the marked gas threshold set by the system, generate perfume output dosage data according to the wind force calculation data; A brightness calculation module is used to obtain environmental brightness data, input the environmental brightness data and personnel location information into a brightness calculation model preset by the system, and obtain brightness calculation data; The instruction generation module is used to generate corresponding fan light adjustment instructions according to the wind force calculation data, the perfume output dosage data and the brightness calculation data.

8. The environment-aware intelligent fan light control device according to claim 7, characterized in that: The construction of the environmental wind force curve specifically includes: A temperature processing module, used for acquiring temperature and wind force test data, generating a first wind force data set according to the temperature and wind force test data, and analyzing the first wind force data set by using a linear regression algorithm to obtain a first wind force linear curve; A position processing module, used for acquiring position wind force test data, generating a second wind force data set according to the position wind force test data, and analyzing the second wind force data set by using a linear regression algorithm to obtain a second wind force linear curve; The curve generating module is used to combine the first wind linear curve and the second wind linear curve to obtain the environmental wind curve.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the environment-aware intelligent fan light control method as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the environment-aware intelligent fan light control method as claimed in any one of claims 1 to 6 are implemented.

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