Full-automatic light color adjusting method and system for tourist attraction building

Abstract

According to the full-automatic light color adjusting method and system for the tourist attraction buildings, the environment and tourist flow of the tourist attraction are monitored in real time by deploying the high-density intelligent sensor network and the tourist flow counting equipment, and the unmanned aerial vehicle is used for high-altitude monitoring in the large-scale complex terrain tourist attraction; according to sunrise and sunset, seasonal change, holiday and astronomical event factors, light color schemes of different time periods and regions are preset, based on collected data and historical records, the system establishes a flow prediction model, time sequence data are processed in combination with LSTM, the light color brightness of each region is dynamically adjusted, and the intelligent power management system is combined with green energy facilities to realize intelligent power management. According to a human body biological clock and a circadian rhythm, light color, brightness and blue light components are optimized, light color is rapidly adjusted in an emergency mode to provide direction guidance, an interactive platform is arranged, user feedback is collected, a light color strategy is continuously optimized, the operation condition of a system is remotely monitored, problems are solved in time, and the on-site maintenance frequency is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of light color adjustment control systems, and in particular to a full-automatic light color adjustment method and system for buildings in tourist attractions. Background Art

[0002] With the rapid development of the tourism industry, more and more tourists choose to visit scenic spots at night or during non-traditional time periods. Traditional fixed lighting solutions can no longer meet the needs of modern tourist attractions, especially in large-scale scenic spots with complex terrain. The changes in tourist flow, changeable weather conditions, and lighting requirements at different time periods have put higher demands on the lighting systems of scenic spots. In recent years, the rapid development of technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data analysis has provided new possibilities for the intelligent management of tourist attractions.

[0003] Most existing systems rely on preset schedules to adjust light color and cannot dynamically adjust according to real-time environmental changes and tourist flow. Traditional lighting systems often use fixed brightness settings and fail to optimize according to the needs of different time periods and scenarios, resulting in energy waste. The lighting design of some scenic spots fails to fully consider the impact of the human body's biological clock and circadian rhythm, which may cause tourists to feel uncomfortable or tired. The existing system has limited emergency response capabilities in the event of an emergency and lacks the function of quickly adjusting light color and providing directional guidance. Summary of the Invention

[0004] The purpose of the present invention is to provide a fully automatic light color adjustment method and system for buildings in tourist attractions.

[0005] The problem to be solved by the present invention is: to solve the problem of intelligent management of the lighting environment in buildings in tourist attractions, ensure that the lighting is in line with the human body's biological clock and circadian rhythm, adapt to different weather, seasons and tourist flows, and monitor environmental parameters and tourist flows in real time through a high-density intelligent sensor network. The central control system dynamically adjusts the light color, brightness and blue light component of each area according to time synchronization and preset light color schemes, predicts tourist flow, and optimizes path visibility, especially during peak hours. The intelligent power management system combines green energy facilities to reduce energy consumption and achieve self-sufficient power supply. The emergency mode provides directional guidance, and the user feedback platform continuously optimizes the light color settings. The deep learning algorithm is used to further enhance the intelligence level of the system to ensure efficient operation.

[0006] A fully automatic light color adjustment method for tourist attraction buildings adopts the following technical solutions: S1: Deploy a high-density intelligent sensor network, including sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels. Use people counting devices to monitor visitor flow and send this data to a central control system. In large scenic areas with complex terrain, use drones for high-altitude monitoring. S2: The central control system is synchronized with the Internet time server, including time synchronization in multiple time zones around the world. Different light color schemes are pre-set to meet different atmosphere requirements according to different time periods of the day, seasonal changes, specific festivals and astronomical events. The light color effects are designed by incorporating local cultural elements, including but not limited to cool white light, warm yellow light, and colorful light. The light color theme is customized for each specific area based on the cultural background, natural landscape and architectural style of the scenic area. S3: Combine the data collected in S1 and establish a dynamic light color adjustment model based on historical data. Taking into account time changes, weather changes, and seasonal changes, the model automatically adjusts the light color and brightness during peak tourist hours and the environment, and adjusts the visibility of the ground and paths. S4: Equipped with an intelligent power management system, combined with green energy facilities, it provides self-sufficient power supply. It uses high-efficiency LED lamps and dimming controllers to meet lighting needs while reducing energy consumption. It dynamically adjusts the light color to suit different human body conditions based on the human body clock and circadian rhythm. S5: Set up an emergency mode to deal with emergencies, adjust the light color to provide clear directional guidance and emergency exit instructions, and send alarm information to tourists. Set up an interactive platform for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. Regularly analyze user feedback and continuously optimize the light color adjustment strategy; S6: Use deep learning algorithms to continuously optimize light color adjustment strategies, learn from practical cases, and predict future light color needs. Through the cloud service platform, technicians can remotely monitor the system's operating status, promptly identify and resolve potential problems, and reduce the number of on-site maintenance times.

[0007] Furthermore, a high-density intelligent sensor network is deployed in S1 to monitor tourist flow through people counting devices. In large and complex scenic areas, drones are used for high-altitude monitoring, including: Deploy sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels throughout the scenic area. These sensors are deployed in tourist areas, parking lots, and logistics service areas. Edge computing nodes are set up to initially process and analyze local sensor data, using multiple communication protocols and backup channels for data transmission. Smart cameras are installed to count the number of tourists and display them, and real-time heat maps are generated based on the collected tourist flow data. For large scenic spots with complex terrain, drones are used for high-altitude monitoring, with flight paths and mission points pre-set. The collected data will be transmitted back to the central control system in real time and integrated and analyzed with ground sensor data to form a complete image of the scenic area environment and tourist activities.

[0008] Furthermore, the central control system in S2 is synchronized with the Internet time server, pre-setting different light color schemes to adapt to different atmosphere requirements, and customizing light color themes for each specific area, including: The central control system is synchronized with the Internet time server through NTP, dynamically adjusting the time of each area according to the geographical location and sunrise and sunset times, and adjusting the light color changes to be consistent with the local natural light; Light color design is carried out according to the early morning, daytime, evening and night, and seasonal light color adjustments are made according to spring, summer, autumn and winter. Light color adjustments are made according to statutory holidays and traditional festivals, and according to solar eclipses, lunar eclipses and meteor showers. Buildings with historical value are reproduced through light color technology. According to the functions and characteristics of different areas in the scenic area, personalized light color themes are customized for classical buildings and modern buildings to reflect the characteristics of the corresponding elements.

[0009] Furthermore, S3 combines the data collected in S1 with historical data to establish a traffic prediction model, automatically adjusts the light color and brightness according to the environment during peak tourist hours, and adjusts the visibility of the ground and paths, including: S31: Remove outliers and missing values ​​from the data collected in S1 and extract features, including time as hour, day, week, month, weather conditions as sunny, cloudy, rainy, season as spring, summer, autumn, winter, whether it is a holiday, whether it is a special event, illumination, temperature, humidity, wind speed, PM2.5, PM10 air quality, noise level, and use LSTM to process long-term dependencies in time series data; S32: Establishing a model for automatically adjusting light color and brightness , ,in It is a piecewise function that describes the brightness changes at different time periods of the day. , A function that adjusts brightness based on the predicted tourist flow. , The current time is in hours, For weather conditions, is the seasonal coefficient, is the maximum brightness, is the minimum brightness, is the Sigmoid function, is the collective illuminance ,temperature ,humidity , wind speed , air quality , noise level The adjustment function, ; S33: Based on sunny = 1, cloudy = 0.5, rainy = 0.3, extreme weather = 0.1 Assign values ​​according to spring = 0.8, summer = 0.7, autumn = 0.9, winter = 0.6 Assign a value, , , , , , ; S34: Based on the calculation results, the central control system automatically adjusts the light color and brightness of each area, adjusts the visibility of the ground and paths, increases the brightness to improve path clarity during peak tourist periods, and reduces the brightness during low-traffic periods. The system dynamically adjusts the light color and brightness in real time according to the crowd density and environment.

[0010] Furthermore, the S4 dynamically adjusts different suitable light colors for the human body according to the human body clock principle and circadian rhythm, including: S41: Establishing a light intensity adjustment function ,in , adjust the light intensity according to different time periods, and the change of light intensity follows the natural law of the human body's biological clock; S42: Establish color temperature adjustment function ,in , adjust the color temperature according to different time periods, and adjust the color of the light to meet the needs of the human body's biological clock; S43: Establishing a blue light component adjustment function ,in , adjust the blue light content according to different time periods, and adjust the lighting so as not to have a negative impact on tourists' melatonin secretion; S44: The central control system is based on the current time , combined with the light intensity adjustment function , color temperature adjustment function and blue light component adjustment function , calculate the light color and brightness of each area, and adjust the light color, brightness and blue light component of each area in real time according to the human body clock principle and circadian rhythm.

[0011] Furthermore, a fully automatic light color adjustment system for a tourist attraction building is provided, which is used to implement any of the above-mentioned fully automatic light color adjustment methods for a tourist attraction building. The fully automatic light color adjustment system for a tourist attraction building comprises: an intelligent sensor network and data acquisition module, a central control system and time zone synchronization module, a light color dynamic adjustment module, an intelligent power management and green energy facility module, an emergency mode and user feedback module, and a deep learning optimization and remote monitoring module. Smart sensor network and data acquisition module: Deploy a high-density smart sensor network to monitor the scenic area's environmental parameters, including light intensity, temperature, humidity, wind speed, air quality, and noise level, in real time. Combined with crowd counting equipment and drone high-altitude monitoring, this module can determine visitor flow and the overall environmental conditions of the scenic area. Edge computing nodes process and analyze local data, enabling rapid response and efficient transmission. Central control system and time zone synchronization module: responsible for the time zone synchronization and light color scheme preset of the central control system, synchronized with the Internet time server through the NTP protocol, dynamically adjusting the light color and brightness of each area according to sunrise and sunset times, seasonal changes, holidays, and astronomical events, integrating local cultural elements to create a unique atmosphere experience; Dynamic light color adjustment module: Based on the collected real-time and historical data, it establishes a traffic prediction model and an automatic light color brightness adjustment model. It processes time series data through LSTM to predict future tourist traffic and dynamically adjusts the light color brightness of each area according to weather, season, and time period factors, adjusting the visibility of the ground and paths. Smart power management and green energy facility module: Integrates green energy facilities for self-sufficient power supply. Through smart power management systems and high-efficiency LED lamps, light color, brightness, and blue light content are dynamically adjusted according to the human body clock and circadian rhythm to minimize energy consumption. Emergency mode and user feedback module: When an emergency occurs, it automatically switches to emergency mode, adjusts the light color to provide clear directional guidance and emergency exit instructions, and sends alert information to tourists through multiple channels. At the same time, an interactive platform is set up for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. User feedback is regularly analyzed to continuously optimize the light color adjustment strategy; Deep learning optimization and remote monitoring module: uses deep learning algorithms to continuously optimize light color adjustment strategies, learns from practical cases to predict future light color requirements, remotely monitors the operating status of the system, promptly discovers and resolves potential problems, reduces the number of on-site maintenance, and has self-diagnosis functions that can automatically alarm and provide preliminary solutions when problems arise.

[0012] The beneficial effects of the present invention are: through a high-density intelligent sensor network, the illumination, temperature, humidity, wind speed, air quality, and noise level environmental parameters in the scenic area are monitored in real time. Combined with crowd counting equipment and drone high-altitude monitoring, the tourist flow and the overall environmental conditions of the scenic area are fully understood, providing data support for decision-making. Based on the collected real-time and historical data, a flow prediction model and an automatic light color and brightness adjustment model are established to adjust the lighting environment to always be in the optimal state, reduce manual intervention, and improve management efficiency. Integrating green energy facilities such as solar photovoltaic panels and wind turbines to achieve self-sufficient power supply, reduce dependence on external electricity, lower carbon emissions, and promote the sustainable development of the scenic area. High-efficiency LED lamps and intelligent dimming controllers are used to dynamically adjust brightness according to actual needs, minimize energy consumption, extend lamp life, and reduce maintenance costs. Through the cloud service platform, the system's operating status can be remotely monitored to promptly identify and resolve potential problems and reduce the number of on-site repairs. Different light and color schemes are pre-set according to different time periods of the day, seasonal changes, holidays and astronomical events, incorporating local cultural elements to create a unique atmosphere and enhance tourists' sense of immersion and experience. According to the circadian rhythm, the light intensity, color temperature and blue light content are dynamically adjusted to ensure that the lighting environment meets lighting needs without negatively affecting tourists' physiological rhythms, thereby improving tourists' comfort and health. The brightness is automatically increased during peak tourist periods to ensure clear visibility of the ground and paths and reduce safety hazards; while the brightness is appropriately reduced during low-traffic periods to save energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of a fully automatic light color adjustment method for tourist attraction buildings; Figure 2 This is a module diagram of a fully automatic light color adjustment system for tourist attraction buildings. DETAILED DESCRIPTION

[0014] The present invention is further clearly and completely described below, but the protection scope of the present invention is not limited thereto.

[0015] A fully automatic light color adjustment method for tourist attraction buildings adopts the following technical solutions: S1: Deploy a high-density intelligent sensor network, including sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels. Use people counting devices to monitor visitor flow and send this data to a central control system. In large scenic areas with complex terrain, use drones for high-altitude monitoring. S2: The central control system is synchronized with the Internet time server, including time synchronization in multiple time zones around the world. Different light color schemes are pre-set to meet different atmosphere requirements according to different time periods of the day, seasonal changes, specific festivals and astronomical events. The light color effects are designed by incorporating local cultural elements, including but not limited to cool white light, warm yellow light, and colorful light. The light color theme is customized for each specific area based on the cultural background, natural landscape and architectural style of the scenic area. S3: Combine the data collected in S1 and establish a dynamic light color adjustment model based on historical data. Taking into account time changes, weather changes, and seasonal changes, the model automatically adjusts the light color and brightness during peak tourist hours and the environment, and adjusts the visibility of the ground and paths. S4: Equipped with an intelligent power management system, combined with green energy facilities, it provides self-sufficient power supply. It uses high-efficiency LED lamps and dimming controllers to meet lighting needs while reducing energy consumption. It dynamically adjusts the light color to suit different human body conditions based on the human body clock and circadian rhythm. S5: Set up an emergency mode to deal with emergencies, adjust the light color to provide clear directional guidance and emergency exit instructions, and send alarm information to tourists. Set up an interactive platform for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. Regularly analyze user feedback and continuously optimize the light color adjustment strategy; S6: Use deep learning algorithms to continuously optimize light color adjustment strategies, learn from practical cases, and predict future light color needs. Through the cloud service platform, technicians can remotely monitor the system's operating status, promptly identify and resolve potential problems, and reduce the number of on-site maintenance times.

[0016] refer to Figure 1 The figure shows a flow chart of a fully automatic light color adjustment method for tourist attraction buildings.

[0017] Furthermore, a high-density intelligent sensor network is deployed in S1 to monitor tourist flow through people counting devices. In large and complex scenic areas, drones are used for high-altitude monitoring, including: Deploy sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels throughout the scenic area. These sensors are deployed in tourist areas, parking lots, and logistics service areas. Edge computing nodes are set up to initially process and analyze local sensor data, using multiple communication protocols and backup channels for data transmission. Smart cameras are installed to count the number of tourists and display them, and real-time heat maps are generated based on the collected tourist flow data. For large scenic spots with complex terrain, drones are used for high-altitude monitoring, with flight paths and mission points pre-set. The collected data will be transmitted back to the central control system in real time and integrated and analyzed with ground sensor data to form a complete image of the scenic area environment and tourist activities.

[0018] Furthermore, the central control system in S2 is synchronized with the Internet time server, pre-setting different light color schemes to adapt to different atmosphere requirements, and customizing light color themes for each specific area, including: The central control system is synchronized with the Internet time server through NTP, dynamically adjusting the time of each area according to the geographical location and sunrise and sunset times, and adjusting the light color changes to be consistent with the local natural light; Light color design is carried out according to the early morning, daytime, evening and night, and seasonal light color adjustments are made according to spring, summer, autumn and winter. Light color adjustments are made according to statutory holidays and traditional festivals, and according to solar eclipses, lunar eclipses and meteor showers. Buildings with historical value are reproduced through light color technology. According to the functions and characteristics of different areas in the scenic area, personalized light color themes are customized for classical buildings and modern buildings to reflect the characteristics of the corresponding elements.

[0019] Furthermore, S3 combines the data collected in S1 with historical data to establish a traffic prediction model, automatically adjusts the light color and brightness according to the environment during peak tourist hours, and adjusts the visibility of the ground and paths, including: S31: Remove outliers and missing values ​​from the data collected in S1 and extract features, including time as hour, day, week, month, weather conditions as sunny, cloudy, rainy, season as spring, summer, autumn, winter, whether it is a holiday, whether it is a special event, illumination, temperature, humidity, wind speed, PM2.5, PM10 air quality, noise level, and use LSTM to process long-term dependencies in time series data; S32: Establishing a model for automatically adjusting light color and brightness , ,in It is a piecewise function that describes the brightness changes at different time periods of the day. , A function that adjusts brightness based on the predicted tourist flow. , The current time is in hours, For weather conditions, is the seasonal coefficient, is the maximum brightness, is the minimum brightness, is the Sigmoid function, is the collective illuminance ,temperature ,humidity , wind speed , air quality , noise level The adjustment function, ; S33: Based on sunny = 1, cloudy = 0.5, rainy = 0.3, extreme weather = 0.1 Assign values ​​according to spring = 0.8, summer = 0.7, autumn = 0.9, winter = 0.6 Assign a value, , , , , , ; S34: Based on the calculation results, the central control system automatically adjusts the light color and brightness of each area, adjusts the visibility of the ground and paths, increases the brightness to improve path clarity during peak tourist periods, and reduces the brightness during low-traffic periods. The system dynamically adjusts the light color and brightness in real time according to the crowd density and environment.

[0020] Furthermore, the S4 dynamically adjusts different suitable light colors for the human body according to the human body clock principle and circadian rhythm, including: S41: Establishing a light intensity adjustment function ,in , adjust the light intensity according to different time periods, and the change of light intensity follows the natural law of the human body's biological clock; S42: Establish color temperature adjustment function ,in , adjust the color temperature according to different time periods, and adjust the color of the light to meet the needs of the human body's biological clock; S43: Establishing a blue light component adjustment function ,in , adjust the blue light content according to different time periods, and adjust the lighting so as not to have a negative impact on tourists' melatonin secretion; S44: The central control system is based on the current time , combined with the light intensity adjustment function , color temperature adjustment function and blue light component adjustment function , calculate the light color and brightness of each area, and adjust the light color, brightness and blue light component of each area in real time according to the human body clock principle and circadian rhythm.

[0021] Furthermore, a fully automatic light color adjustment system for a tourist attraction building is provided, which is used to implement any of the above-mentioned fully automatic light color adjustment methods for a tourist attraction building. The fully automatic light color adjustment system for a tourist attraction building comprises: an intelligent sensor network and data acquisition module, a central control system and time zone synchronization module, a light color dynamic adjustment module, an intelligent power management and green energy facility module, an emergency mode and user feedback module, and a deep learning optimization and remote monitoring module. Smart sensor network and data acquisition module: Deploy a high-density smart sensor network to monitor the scenic area's environmental parameters, including light intensity, temperature, humidity, wind speed, air quality, and noise level, in real time. Combined with crowd counting equipment and drone high-altitude monitoring, this module can determine visitor flow and the overall environmental conditions of the scenic area. Edge computing nodes process and analyze local data, enabling rapid response and efficient transmission. Central control system and time zone synchronization module: responsible for the time zone synchronization and light color scheme preset of the central control system, synchronized with the Internet time server through the NTP protocol, dynamically adjusting the light color and brightness of each area according to sunrise and sunset times, seasonal changes, holidays, and astronomical events, integrating local cultural elements to create a unique atmosphere experience; Dynamic light color adjustment module: Based on the collected real-time and historical data, it establishes a traffic prediction model and an automatic light color brightness adjustment model. It processes time series data through LSTM to predict future tourist traffic and dynamically adjusts the light color brightness of each area according to weather, season, and time period factors, adjusting the visibility of the ground and paths. Smart power management and green energy facility module: Integrates green energy facilities for self-sufficient power supply. Through smart power management systems and high-efficiency LED lamps, light color, brightness, and blue light content are dynamically adjusted according to the human body clock and circadian rhythm to minimize energy consumption. Emergency mode and user feedback module: When an emergency occurs, it automatically switches to emergency mode, adjusts the light color to provide clear directional guidance and emergency exit instructions, and sends alert information to tourists through multiple channels. At the same time, an interactive platform is set up for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. User feedback is regularly analyzed to continuously optimize the light color adjustment strategy; Deep learning optimization and remote monitoring module: uses deep learning algorithms to continuously optimize light color adjustment strategies, learns from practical cases to predict future light color requirements, remotely monitors the operating status of the system, promptly discovers and resolves potential problems, reduces the number of on-site maintenance, and has self-diagnosis functions that can automatically alarm and provide preliminary solutions when problems arise.

[0022] refer to Figure 2 The figure shows a module diagram of a fully automatic light color adjustment system for a tourist attraction building.

[0023] The present invention provides a fully automatic light color adjustment method and system for buildings in tourist attractions. By deploying a high-density intelligent sensor network and people counting equipment, the scenic area environment and tourist flow are monitored in real time. Unmanned aerial vehicles are used for high-altitude monitoring in large and complex terrain scenic areas. Light color schemes for different time periods and areas are pre-set according to sunrise and sunset, seasonal changes, holidays and astronomical events. Based on the collected data and historical records, the system establishes a traffic prediction model, combines LSTM to process time series data, and dynamically adjusts the light color and brightness of each area. The intelligent power management system is combined with green energy facilities to optimize light color, brightness and blue light content according to the human body's biological clock and circadian rhythm. In emergency mode, light color is quickly adjusted to provide directional guidance. An interactive platform is set up to collect user feedback, continuously optimize light color strategies, remotely monitor system operation status, solve problems in a timely manner, and reduce the number of on-site maintenance times.

Claims

1. A fully automatic light color adjustment method for tourist attraction buildings, characterized in that: include: S1: Deploy a high-density intelligent sensor network, including sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels. Use people counting devices to monitor visitor flow and send this data to a central control system. In large scenic areas with complex terrain, use drones for high-altitude monitoring. S2: The central control system is synchronized with the Internet time server, including time synchronization in multiple time zones around the world. Different light color schemes are pre-set to meet different atmosphere requirements according to different time periods of the day, seasonal changes, specific festivals and astronomical events. The light color effects are designed by incorporating local cultural elements, including but not limited to cool white light, warm yellow light, and colorful light. The light color theme is customized for each specific area based on the cultural background, natural landscape and architectural style of the scenic area. S3: Combine the data collected in S1 and establish a dynamic light color adjustment model based on historical data. Taking into account time changes, weather changes, and seasonal changes, the model automatically adjusts the light color and brightness during peak tourist hours and the environment, and adjusts the visibility of the ground and paths. S4: Equipped with an intelligent power management system, combined with green energy facilities, it provides self-sufficient power supply. It uses high-efficiency LED lamps and dimming controllers to meet lighting needs while reducing energy consumption. It dynamically adjusts the light color to suit different human body conditions based on the human body clock and circadian rhythm. S5: Set up an emergency mode to deal with emergencies, adjust the light color to provide clear directional guidance and emergency exit instructions, and send alarm information to tourists. Set up an interactive platform for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. Regularly analyze user feedback and continuously optimize the light color adjustment strategy; S6: Use deep learning algorithms to continuously optimize light color adjustment strategies, learn from practical cases, and predict future light color needs. Through the cloud service platform, technicians can remotely monitor the system's operating status, promptly identify and resolve potential problems, and reduce the number of on-site maintenance times.

2. A fully automatic light color adjustment method for a tourist attraction building according to claim 1, characterized in that: S1 deploys a high-density intelligent sensor network, monitors tourist traffic through people counting devices, and uses drones for high-altitude monitoring in large and complex scenic areas, including: Deploy sensors for light intensity, temperature, humidity, wind speed, PM2.5, PM10 air quality, and noise levels throughout the scenic area. These sensors are deployed in tourist areas, parking lots, and logistics service areas. Edge computing nodes are set up to initially process and analyze local sensor data, using multiple communication protocols and backup channels for data transmission. Smart cameras are installed to count the number of tourists and display them, and real-time heat maps are generated based on the collected tourist flow data. For large scenic spots with complex terrain, drones are used for high-altitude monitoring, with flight paths and mission points pre-set. The collected data will be transmitted back to the central control system in real time and integrated and analyzed with ground sensor data to form a complete image of the scenic area environment and tourist activities.

3. The fully automatic light color adjustment method for a tourist attraction building according to claim 1, characterized in that: The central control system in S2 is synchronized with the Internet time server, pre-setting different light color schemes to adapt to different atmosphere requirements, and customizing light color themes for each specific area, including: The central control system is synchronized with the Internet time server through NTP, dynamically adjusting the time of each area according to the geographical location and sunrise and sunset times, and adjusting the light color changes to be consistent with the local natural light; Light color design is carried out according to the early morning, daytime, evening and night, and seasonal light color adjustments are made according to spring, summer, autumn and winter. Light color adjustments are made according to statutory holidays and traditional festivals, and according to solar eclipses, lunar eclipses and meteor showers. Buildings with historical value are reproduced through light color technology. According to the functions and characteristics of different areas in the scenic area, personalized light color themes are customized for classical buildings and modern buildings to reflect the characteristics of the corresponding elements.

4. The fully automatic light color adjustment method for a tourist attraction building according to claim 1, characterized in that: S3 combines the data collected in S1 with historical data to establish a traffic prediction model, automatically adjusts the light color and brightness according to the environment during peak tourist hours, and adjusts the visibility of the ground and paths, including: S31: Remove outliers and missing values ​​from the data collected in S1 and extract features, including time as hour, day, week, month, weather conditions as sunny, cloudy, rainy, season as spring, summer, autumn, winter, whether it is a holiday, whether it is a special event, illumination, temperature, humidity, wind speed, PM2.5, PM10 air quality, noise level, and use LSTM to process long-term dependencies in time series data; S32: Establishing a model for automatically adjusting light color and brightness , ,in It is a piecewise function that describes the brightness changes at different time periods of the day. , A function that adjusts brightness based on the predicted tourist flow. , The current time is in hours, For weather conditions, is the seasonal coefficient, is the maximum brightness, is the minimum brightness, is the Sigmoid function, is the collective illuminance ,temperature ,humidity , wind speed , air quality , noise level The adjustment function, ; S33: Based on sunny = 1, cloudy = 0.5, rainy = 0.3, extreme weather = 0.1 Assign values ​​according to spring = 0.8, summer = 0.7, autumn = 0.9, winter = 0.6 Assign a value, , , , , , ; S34: Based on the calculation results, the central control system automatically adjusts the light color and brightness of each area, adjusts the visibility of the ground and paths, increases the brightness to improve path clarity during peak tourist periods, and reduces the brightness during low-traffic periods. The system dynamically adjusts the light color and brightness in real time according to the crowd density and environment.

5. The fully automatic light color adjustment method for a tourist attraction building according to claim 1, characterized in that: The S4 dynamically adjusts different suitable light colors for the human body according to the human body clock principle and circadian rhythm, including: S41: Establishing a light intensity adjustment function ,in , adjust the light intensity according to different time periods, and the change of light intensity follows the natural law of the human body's biological clock; S42: Establish color temperature adjustment function ,in , adjust the color temperature according to different time periods, and adjust the color of the light to meet the needs of the human body's biological clock; S43: Establishing a blue light component adjustment function ,in , adjust the blue light content according to different time periods, and adjust the lighting so as not to have a negative impact on tourists' melatonin secretion; S44: The central control system is based on the current time , combined with the light intensity adjustment function , color temperature adjustment function and blue light component adjustment function , calculate the light color and brightness of each area, and adjust the light color, brightness and blue light component of each area in real time according to the human body clock principle and circadian rhythm.

6. A fully automatic light color adjustment system for tourist attraction buildings, characterized in that: A method for implementing any one of the above-mentioned fully automatic light color adjustment methods for tourist attraction buildings, wherein the fully automatic light color adjustment system for tourist attraction buildings comprises: an intelligent sensor network and data acquisition module, a central control system and time zone synchronization module, a light color dynamic adjustment module, an intelligent power management and green energy facility module, an emergency mode and user feedback module, and a deep learning optimization and remote monitoring module; Smart sensor network and data acquisition module: Deploy a high-density smart sensor network to monitor the scenic area's environmental parameters, including light intensity, temperature, humidity, wind speed, air quality, and noise level, in real time. Combined with crowd counting equipment and drone high-altitude monitoring, this module can determine visitor flow and the overall environmental conditions of the scenic area. Edge computing nodes process and analyze local data, enabling rapid response and efficient transmission. Central control system and time zone synchronization module: responsible for the time zone synchronization and light color scheme preset of the central control system, synchronized with the Internet time server through the NTP protocol, dynamically adjusting the light color and brightness of each area according to sunrise and sunset times, seasonal changes, holidays, and astronomical events, integrating local cultural elements to create a unique atmosphere experience; Dynamic light color adjustment module: Based on the collected real-time and historical data, it establishes a traffic prediction model and an automatic light color brightness adjustment model. It processes time series data through LSTM to predict future tourist traffic and dynamically adjusts the light color brightness of each area according to weather, season, and time period factors, adjusting the visibility of the ground and paths. Smart power management and green energy facility module: Integrates green energy facilities for self-sufficient power supply. Through smart power management systems and high-efficiency LED lamps, light color, brightness, and blue light content are dynamically adjusted according to the human body clock and circadian rhythm to minimize energy consumption. Emergency mode and user feedback module: When an emergency occurs, it automatically switches to emergency mode, adjusts the light color to provide clear directional guidance and emergency exit instructions, and sends alert information to tourists through multiple channels. At the same time, an interactive platform is set up for tourists to submit their opinions and suggestions on the current light color settings through mobile applications and on-site touch screens. User feedback is regularly analyzed to continuously optimize the light color adjustment strategy; Deep learning optimization and remote monitoring module: uses deep learning algorithms to continuously optimize light color adjustment strategies, learns from practical cases to predict future light color requirements, remotely monitors the operating status of the system, promptly discovers and resolves potential problems, reduces the number of on-site maintenance, and has self-diagnosis functions that can automatically alarm and provide preliminary solutions when problems arise.

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