Self-adaptive intelligent LED mining lamp adjusting system based on AI visual capture technology

Abstract

The invention relates to the technical field of intelligent lighting, and discloses a self-adaptive intelligent LED mining lamp adjusting system based on an AI visual capture technology. The system not only can automatically adjust the light brightness according to the environment illumination intensity, the temperature and humidity, the personnel activity frequency and the noise level so as to avoid the phenomenon of over-bright or insufficient illumination, but also can carry out denoising and abnormal value processing on the collected data through the data processing module so as to ensure the accuracy of the adjustment process and improve the adjustment efficiency. The intelligent dimming control module generates a light adjusting monitoring report based on comprehensive data, so that management personnel can grasp the lighting state in real time and autonomously set parameters, the use efficiency of lighting resources is remarkably improved, the energy consumption is reduced, the operation cost is reduced, and the safety and comfort of the industrial and mining environment are improved. Not only is the adaptive capacity to a complex environment enhanced, but also industrial and mining illumination is promoted to develop towards a more efficient and safer direction.

Description

Technical Field

[0001] The present invention relates to the field of intelligent lighting technology, and in particular to an adaptive intelligent LED mining lamp adjustment system based on AI vision capture technology. Background Art

[0002] In modern industrial and mining environments, reasonable lighting not only directly affects work efficiency and operational safety, but also affects the physical and mental health of employees. Adjusting the light brightness can provide optimal lighting conditions based on environmental changes, personnel activities and actual work needs. Timely lighting adjustment can not only reduce energy waste and reduce operating costs, but also effectively improve the comfort and safety of the workplace, allowing employees to focus more on work in a good visual environment, thereby improving overall productivity.

[0003] However, existing industrial and mining lighting systems often use fixed brightness settings and lack flexibility and intelligence. Traditional lighting control systems often cannot respond to environmental changes in real time, such as light intensity, temperature and humidity, human activities and other factors, resulting in over-brightness or insufficient lighting in some cases. In addition, existing technologies usually rely on data from a single sensor and cannot fully reflect the complexity of the environment, resulting in a waste of lighting resources or safety hazards. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides an adaptive intelligent LED industrial and mining lamp adjustment system based on AI visual capture technology. The system can not only automatically adjust the light brightness according to the ambient light intensity, temperature and humidity, personnel activity frequency and noise level, thereby avoiding excessive or insufficient lighting, but also perform denoising and outlier processing on the collected data through the data processing module to ensure the accuracy of the adjustment process. The intelligent dimming control module generates a light adjustment monitoring report based on the comprehensive data, so that managers can grasp the lighting status in real time and set parameters independently, thereby significantly improving the utilization efficiency of lighting resources, reducing energy consumption, reducing operating costs, and improving the safety and comfort of the industrial and mining environment. This intelligent lighting management system not only enhances the adaptability to complex environments, but also promotes industrial and mining lighting to develop in a more efficient and safer direction, solving the above problems.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology, comprising a multi-sensor fusion module, a data processing module, an intelligent dimming control module and a remote monitoring module;

[0008] The multi-sensor fusion module is used to collect ambient light intensity data through a photosensitive sensor, detect whether there is human activity in the area where the industrial and mining lamp is located through AI visual capture, collect temperature data and humidity data of the current environment through a temperature and humidity sensor, and collect ambient noise data through a noise sensor;

[0009] The data processing module receives the data from the multi-sensor fusion module, performs data denoising and outlier removal, and calculates the environmental brightness adaptation value, personnel activity frequency, temperature adaptation factor, humidity adaptation factor, noise monitoring value, and light energy consumption rate and sends them to the intelligent dimming control module;

[0010] The intelligent lighting control module uses lighting adjustment technology to adjust the brightness of LED industrial and mining lights according to the values ​​of environmental brightness adaptation value, personnel activity frequency, temperature adaptation factor, humidity adaptation factor, noise monitoring value and lighting energy consumption rate. After the adjustment is completed, a lighting adjustment monitoring report will be generated and sent to the remote monitoring module;

[0011] The remote monitoring module is an LED display interface, and the management personnel can independently set the brightness parameters of the LED mining lamps according to the received light adjustment monitoring report.

[0012] Preferably, the formula for data denoising is as follows:

[0013]

[0014] In the formula, D n represents the denoised data value, x n-i Represents the ni-th data value in the original data sequence, k represents the first k data points used to calculate the average, and i represents the counting subscript.

[0015] Preferably, the formula for removing outliers is as follows:

[0016] MAD=median(|x i -median(x)|)

[0017] The outlier threshold is:

[0018] Yc=m*MAD

[0019] Judging criteria:

[0020] |x i -median(x)|>Yc

[0021] In the formula, MAD stands for median deviation, x i represents a single data point in the data set for which an outlier needs to be identified, m represents the outlier judgment multiple, which is 3, Yc represents the outlier threshold, |x iWhen the value of -median(x)| is greater than the abnormal value Yc, it means that the data is abnormal data.

[0022] Preferably, the calculation formula of the ambient brightness adaptation value is as follows:

[0023] L adapt =e*L ambient +(1-e)*L current

[0024] In the formula, L adapt represents the ambient brightness adaptation value, e represents the importance factor of ambient light intensity, and its value range is 0-1, L ambient Indicates the ambient light intensity, the reading from the photosensor, L current Indicates the current brightness of the LED mining lamp.

[0025] Preferably, the calculation formula of the personnel activity frequency is as follows:

[0026]

[0027] In the formula, F activity Indicates the frequency of personnel activities, N detection It represents the number of activities detected in a time period. The data comes from the infrared sensor, and T represents the observation time period.

[0028] Preferably, the temperature adaptation factor calculation formula is as follows:

[0029]

[0030] In the formula, Wd adapt represents the temperature adaptation factor, T current Represents the current humidity value from the temperature sensor, T base Indicates the reference temperature, T target Indicates the target temperature.

[0031] Preferably, the humidity adaptation factor calculation formula is as follows:

[0032]

[0033] In the formula, H adapt Represents humidity adaptation factor, H current Indicates the current temperature from the temperature and humidity sensor, H base Indicates the reference humidity, H target Indicates the target humidity.

[0034] Preferably, the noise monitoring value calculation formula is as follows:

[0035]

[0036] In the formula, N monitor Indicates the noise monitoring value, N i represents the noise level at time point i, which comes from the reading of the noise sensor, T represents the noise monitoring time, and i represents the count subscript.

[0037] Preferably, the light energy consumption rate calculation formula is as follows:

[0038] E consut =P LED *Ts

[0039] In the formula, E consut Indicates the lighting energy consumption, P LED It indicates the power of LED lamp, and Ts indicates the working time of the lamp.

[0040] Preferably, the intelligent lighting control module adjusts the brightness of the LED lamp through PWM lighting adjustment technology.

[0041] Compared with the prior art, the present invention provides an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology, which has the following beneficial effects:

[0042] The present invention can automatically adjust the light brightness according to the ambient light intensity, temperature and humidity, frequency of human activities and noise level, so as to avoid over-brightness or insufficient lighting. It can also denoise and process the collected data through the data processing module to ensure the accuracy of the adjustment process. The intelligent dimming control module generates a light adjustment monitoring report based on the comprehensive data, so that managers can grasp the lighting status in real time and set parameters independently, thereby significantly improving the utilization efficiency of lighting resources, reducing energy consumption, reducing operating costs, and improving the safety and comfort of industrial and mining environments. This intelligent lighting management system not only enhances the adaptability to complex environments, but also promotes industrial and mining lighting to develop in a more efficient and safer direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] Traditional lighting control systems often fail to respond to environmental changes in real time, such as light intensity, temperature and humidity, and human activities, which leads to over-brightness or insufficient lighting in some cases. In addition, existing technologies usually rely on data from a single sensor and cannot fully reflect the complexity of the environment, resulting in waste of lighting resources or potential safety hazards. Therefore, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is proposed. Please refer to Figure 1 ,The system includes a multi-sensor fusion module, a data processing module, an intelligent dimming control module, and a remote monitoring module;

[0046] The multi-sensor fusion module adopts advanced sensing technology and realizes comprehensive monitoring and intelligent response to the industrial and mining environment through the collaborative work of multiple sensors. Specifically, the photosensitive sensor collects the light intensity data of the surrounding environment in real time to accurately determine whether the brightness of the LED industrial and mining lamp needs to be adjusted. At the same time, AI visual capture technology is used to detect whether there is human activity in the light coverage area through high-resolution cameras and computer vision algorithms. This technology can analyze video streams, identify motion patterns, and combine with lighting data to ensure sufficient lighting when there are people. In terms of ambient temperature and humidity, the temperature and humidity sensor is responsible for monitoring the temperature and humidity changes of the current environment. The data is used to evaluate the comfort of the working environment and optimize the energy consumption of lamps. In addition, the noise sensor monitors the noise level of the surrounding environment. By collecting and analyzing noise data, it provides additional decision-making basis for dimming, thereby avoiding interference in noisy environments.

[0047] The data processing module is the core component of the system, responsible for receiving multi-dimensional data input from the multi-sensor fusion module. This module uses advanced data preprocessing technology to first denoise the acquired data and eliminate possible noise interference through a variety of algorithms (such as moving average method and median absolute deviation method, etc.) to ensure the accuracy of subsequent analysis. At the same time, the data processing module uses outlier detection algorithms (such as Z score method and quartile method) to identify and remove unreasonable data points to reduce the impact of edge cases.

[0048] After data cleaning, the module continuously monitors the environmental status, obtains the environmental brightness adaptation value through comprehensive calculation, compares the reading of the light sensor with the current light intensity, and generates real-time adjustment suggestions. The calculation of the frequency of human activity is based on the data collected by the infrared sensor, and is quantified by the number of activities within a time unit to ensure that appropriate brightness is provided when there are human activities. At the same time, the calculation of the temperature adaptation factor and the humidity adaptation factor is based on the data of the temperature and humidity sensors. These two parameters are important references in light adjustment.

[0049] In addition, the acquisition of noise monitoring values ​​is achieved through noise sensors, which can evaluate the noise level of the environment in real time and provide additional input information for the lighting adjustment model. Finally, the lighting energy consumption rate is calculated based on the power and operating time of the current lamps to achieve effective energy management. After all the processing results are calculated and aggregated, the data processing module integrates them and sends them to the intelligent dimming control module to ensure that the system can dynamically adjust the lighting settings according to the actual environment and usage needs, thereby realizing an intelligent lighting control system;

[0050] The calculation formula of the ambient brightness adaptation value is as follows:

[0051] L adapt =e*L ambient +(1-e)*L current

[0052] Based on the real-time collected ambient light intensity data, the ambient brightness adaptation value can effectively determine the adjustment requirements of the LED lights. When the ambient light is insufficient, the system will automatically increase the light brightness, and when the light is sufficient, it will reduce the brightness, thereby achieving the best utilization of energy efficiency. In the formula, L adapt represents the ambient brightness adaptation value, e represents the importance factor of ambient light intensity, and its value range is 0-1, L ambient Indicates the ambient light intensity, the reading from the photosensor, L current Indicates the current brightness of the LED mining lamp, which automatically adjusts the light brightness to adapt to environmental changes and provide workers with a comfortable working environment. Appropriate lighting intensity can reduce visual fatigue, improve work efficiency and safety, especially in places where people work for long periods of time;

[0053] The calculation formula for personnel activity frequency is as follows:

[0054]

[0055] By monitoring and calculating the frequency of human activities in the area, the system can accurately determine whether there are people present. When it senses that the number of people is increasing, the system can immediately increase the brightness of the light to ensure sufficient lighting and protect the safety of workers. In the formula, F activity Indicates the frequency of personnel activities, N detection Indicates the number of activities detected within a time period. This data comes from the infrared sensor. T represents the observation period. Continuous monitoring of personnel activity information can be used to improve regional safety. If there is no sign of activity in the area that needs lighting, the system may reduce the brightness of the light, reduce energy consumption and reduce potential safety risks.

[0056] The temperature adaptation factor calculation formula is as follows:

[0057]

[0058] The calculation of the temperature adaptation factor can help the system automatically adjust the working state of the lamp according to the change of ambient temperature. The appropriate temperature range can improve the work efficiency and comfort of workers, thereby effectively reducing the decline in production efficiency caused by environmental discomfort. In the formula, Wd adapt represents the temperature adaptation factor, T current Represents the current humidity value from the temperature sensor, T base Indicates the reference temperature, T target Indicates the target temperature. In an environment with too high temperature, the adaptive lighting strategy can effectively reduce the burden on the light source and reduce heat generation. At the same time, it can timely reduce power consumption according to temperature changes, avoid the impact of overheating on LED lamps, and extend the service life of the equipment;

[0059] The calculation formula of humidity adaptation factor is as follows:

[0060]

[0061] Analysis of the humidity adaptation factor can help determine changes in environmental humidity and automatically adjust the intensity of the light to adapt to the environment. In a relatively humid environment, proper lighting can help keep equipment and processes safe and prevent equipment failures caused by excessive humidity. In the formula, H adapt Represents humidity adaptation factor, H current Indicates the current temperature from the temperature and humidity sensor, H base Indicates the reference humidity, H target Indicates target humidity. By analyzing the relationship between humidity and the production process, we can ensure that the environmental humidity is appropriate to optimize production quality and efficiency. Too low or too high humidity may affect the production process, so adjusting the light helps to ensure a balance between dryness and moisture.

[0062] The noise monitoring value calculation formula is as follows:

[0063]

[0064] By real-time monitoring of the noise level of the surrounding environment, the system can adjust the status of the lamps in time to reduce the interference caused by noise. This is particularly important in industrial or manufacturing environments, which can improve employees' work concentration and reduce the impact of noise on production efficiency. In the formula, N monitor Indicates the noise monitoring value, N i It represents the noise level at time point i. This value comes from the reading of the noise sensor. T represents the noise monitoring time, and i represents the count subscript. Being in a high-noise environment for a long time may cause employees to have increased psychological stress. Using noise monitoring data to adjust lighting can not only optimize lighting conditions, but also create a relatively quiet and comfortable environment, which helps to improve overall job satisfaction.

[0065] The formula for calculating the lighting energy consumption rate is as follows:

[0066] E consut =P LED *Ts

[0067] By calculating the light energy consumption rate, the system can comprehensively evaluate the power consumption of LED lamps, optimize the operation strategy, and ensure the maximum energy saving effect while meeting the lighting needs. In the formula, E consut Indicates the lighting energy consumption, P LED Indicates the power of the LED lamp, Ts indicates the working time of the light. The energy consumption monitoring results will help the management team to budget and manage energy according to the electricity cost, and then take appropriate measures (such as adjusting the working mode and working time) to save costs while ensuring the normal operation of the industrial and mining working environment;

[0068] The intelligent lighting control module is a highly integrated system. Relying on advanced lighting control technology, it processes and analyzes data from multiple key parameters such as ambient brightness adaptation value, personnel activity frequency, temperature adaptation factor, humidity adaptation factor, noise monitoring value, and lighting energy consumption rate in real time. This module uses intelligent algorithms and control logic to quickly analyze the data collected by sensors and automatically determine the optimal light intensity of LED industrial and mining lamps to ensure the best lighting effect under different environmental conditions. For example, when the ambient light is insufficient, the system will increase the light brightness according to the ambient brightness adaptation value. In areas where personnel frequently move, the system may increase the brightness in real time to ensure safety.

[0069] In addition, the control module has a built-in machine learning model that can continuously optimize the control strategy based on historical data and real-time feedback, improve response speed and control accuracy. For extreme temperature and humidity changes, the system will use the calculation results of the temperature and humidity adaptation factor to automatically adjust the working mode to avoid equipment damage and reduce energy consumption. The analysis of noise monitoring values ​​can further adjust the lighting level to reduce interference with workers' work. When all adjustments are completed, the module will generate a comprehensive lighting adjustment monitoring report, which records in detail the brightness adjustment process, energy consumption changes, and environmental adaptation strategies. These monitoring reports will be sent to the remote monitoring module in real time;

[0070] The remote monitoring module is equipped with a high-resolution LED display interface that can display the current lighting status and adjustment suggestions in real time. After receiving the light adjustment monitoring report, managers can easily view the current lighting data and environmental parameters, and independently set the brightness parameters of LED industrial and mining lamps according to specific needs or management strategies. The module also supports users to make manual adjustments through an interactive interface, allowing managers to personalize configurations for specific operations or activities to improve overall work efficiency and safety. In addition, the built-in data recording and analysis functions of the remote monitoring module can track past adjustment history to help managers make more accurate decisions. The entire system uses seamless communication and intelligent feedback, which not only improves the operating efficiency of industrial and mining lamps, but also realizes scientific management and optimization of lighting systems.

[0071] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology, characterized by: Including multi-sensor fusion module, data processing module, intelligent dimming control module and remote monitoring module; The multi-sensor fusion module is used to collect ambient light intensity data through a photosensitive sensor, detect whether there is human activity in the area where the industrial and mining lamp is located through AI visual capture, collect temperature data and humidity data of the current environment through a temperature and humidity sensor, and collect ambient noise data through a noise sensor; The data processing module receives the data from the multi-sensor fusion module, performs data denoising and outlier removal, and calculates the environmental brightness adaptation value, personnel activity frequency, temperature adaptation factor, humidity adaptation factor, noise monitoring value, and light energy consumption rate and sends them to the intelligent dimming control module; The intelligent lighting control module uses lighting adjustment technology to adjust the brightness of LED industrial and mining lights according to the values ​​of environmental brightness adaptation value, personnel activity frequency, temperature adaptation factor, humidity adaptation factor, noise monitoring value and lighting energy consumption rate. After the adjustment is completed, a lighting adjustment monitoring report will be generated and sent to the remote monitoring module; The remote monitoring module is an LED display interface, and the management personnel can independently set the brightness parameters of the LED mining lamps according to the received light adjustment monitoring report.

2. According to claim 1, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized by: The formula for data denoising is as follows: In the formula, D n represents the denoised data value, x n-i represents the ni-th data value in the original data sequence, k represents the first k data points used to calculate the average, and i represents the counting subscript.

3. According to claim 2, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized by: The formula for outlier removal is as follows: MAD=median(|x i -median(x)|) The outlier threshold is: Yc=m*MAD Judging criteria: |x i -median(x)|>Yc In the formula, MAD stands for median deviation, x i represents a single data point in the data set for which an outlier needs to be identified, m represents the outlier judgment multiple, which is 3, Yc represents the outlier threshold, |x i When the value of -median(x)| is greater than the abnormal value Yc, it means that the data is abnormal data.

4. According to claim 3, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized in that: The calculation formula of the ambient brightness adaptation value is as follows: THE adapt =e*L ambient +(1-e)*L current In the formula, L adapt represents the ambient brightness adaptation value, e represents the importance factor of ambient light intensity, and its value range is 0-1, L ambient Indicates the ambient light intensity, the reading from the photosensor, L current Indicates the current brightness of the LED mining lamp.

5. According to claim 4, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized in that: The calculation formula for the personnel activity frequency is as follows: In the formula, F activity Indicates the frequency of personnel activities, N detection It represents the number of activities detected in a time period. The data comes from the infrared sensor, and T represents the observation time period.

6. According to claim 5, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized in that: The temperature adaptation factor calculation formula is as follows: In the formula, Wd adapt represents the temperature adaptation factor, T current Represents the current humidity value from the temperature sensor, T base Indicates the reference temperature, T target Indicates the target temperature.

7. According to claim 6, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized by: The calculation formula of the humidity adaptation factor is as follows: In the formula, H adapt Represents humidity adaptation factor, H current Indicates the current temperature from the temperature and humidity sensor, H base Indicates the reference humidity, H target Indicates the target humidity.

8. According to claim 7, an adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology is characterized by: The noise monitoring value calculation formula is as follows: In the formula, N monitor Indicates the noise monitoring value, N i represents the noise level at time point i, which comes from the reading of the noise sensor, T represents the noise monitoring time, and i represents the count subscript.

9. The adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology according to claim 8 is characterized by: The calculation formula of the lighting energy consumption rate is as follows: E consut =P LED *Ts In the formula, E consut Indicates the lighting energy consumption, P LDE It indicates the power of LED lamp, and Ts indicates the working time of the lamp.

10. The adaptive intelligent LED mining lamp adjustment system based on AI visual capture technology according to claim 9 is characterized in that: The intelligent lighting control module adjusts the brightness of the LED lamp through PWM lighting control technology.

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