Intelligent landscape lighting control system based on data fusion of distributed optical sensors

Abstract

The invention discloses a landscape lighting intelligent control system based on distributed optical sensor data fusion, and relates to the technical field of intelligent control, and the system comprises a data collection module which is used for obtaining environment data in real time; the processing fusion module is used for performing Bayesian fusion on the environmental data to obtain final environmental data estimation; the on-off control module is used for controlling light on-off of the landscape lighting system; the brightness adjusting module is used for adjusting the brightness of light of the landscape lighting system based on a fuzzy reasoning process according to the illumination intensity data and the personnel activity state; and the system evaluation module is used for evaluating the effect of the landscape intelligent adjustment control system according to the light on-off control response analysis of the landscape illumination system and in combination with the energy-saving effect realized through brightness adjustment. According to the method, the problems that the response environment change is not rapid, and system data processing and real-time control are not efficient are solved. Therefore, the purposes of saving energy, improving the lighting effect and enhancing the user experience are achieved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and more specifically, to a landscape lighting intelligent control system based on distributed optical sensor data fusion. Background Art

[0002] The landscape lighting intelligent control system with distributed optical sensor data fusion is a system that uses optical sensors to collect environmental data and fuses data through intelligent algorithms to achieve intelligent control of landscape lighting. This system can greatly improve the energy efficiency of landscape lighting, optimize lighting effects, and automatically adjust lighting strategies according to environmental changes.

[0003] Deficiencies of existing technologies: The data collected by different types of sensors may be noisy or inconsistent. How to effectively integrate data from different sources and make accurate decisions is a technical challenge. The control of landscape lighting needs to respond quickly to environmental changes. The system needs to have efficient data processing and real-time control capabilities. The system needs to determine whether to turn on landscape lighting based on light intensity data, or determine whether to adjust the light brightness by analyzing environmental changes. When the light becomes dim, the system automatically starts the light and adjusts the brightness according to the actual light intensity of the surrounding environment. When people are active, the light brightness may increase, and when no one is around, it will be dimmed or turned off.

[0004] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a landscape lighting intelligent control system with distributed optical sensor data fusion, which collects environmental data using optical sensors and performs data fusion through intelligent algorithms, thereby achieving the purpose of energy saving, improving lighting effects, and enhancing user experience, so as to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: The landscape lighting intelligent control system with distributed optical sensor data fusion includes: data collection module, processing fusion module, opening and closing control module, brightness adjustment module, and there are connections between the modules: A data collection module is used to obtain environmental data in real time according to the optical sensor; a processing and fusion module is used to perform denoising on the environmental data and perform Bayesian fusion on the environmental data collected by multiple sensors of the same type to obtain a final environmental data estimate, wherein the final environmental data estimate includes light intensity data and human activity information; The on / off control module is used to obtain the state of the landscape area through human activity information, and control the on / off of the landscape lighting system in combination with the light intensity and the preset light intensity threshold; The brightness adjustment module is used to obtain the activity status of personnel through human activity information when the lights of the landscape area lighting system are turned on, and adjust the brightness of the lights of the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of personnel; The system evaluation module is used to analyze the light on / off control response of the landscape lighting system, calculate the on / off control time response function, and evaluate the effect of the landscape intelligent adjustment control system in combination with the energy-saving effect achieved through brightness adjustment.

[0007] In a preferred embodiment, the optical sensor includes a light sensor and an infrared sensor; the light sensor is used to measure the light intensity of the environment; and the infrared sensor is used to detect human activities in the area.

[0008] In a preferred embodiment, the specific steps of Bayesian fusion of environmental data collected by multiple sensors of the same type are as follows: preliminarily estimate the environmental data and establish a prior distribution for the environmental data of each sensor; construct an observation model for each sensor to describe how the sensor perceives the environment and calculate the likelihood function of each sensor; according to Bayes' theorem, combine the sensor observation model and the prior distribution to update the posterior distribution of the environmental data; obtain the final environmental data estimate based on the mean of the posterior distribution, and optimize the fusion process by adjusting the prior distribution and the sensor noise variance.

[0009] In a preferred embodiment, the specific process of turning on and off the lights of the landscape lighting system is as follows: When the infrared sensor detects that there is no one in the landscape area, the landscape area status ; When the infrared sensor detects someone in the landscape area, the landscape area status The light intensity is compared with a preset light intensity threshold. When the light intensity is less than the preset light intensity threshold, or the infrared sensor detects that there is someone in the landscape area, the light will be turned on; when the light intensity is greater than the preset light intensity threshold and the infrared sensor detects that there is no one in the landscape area, the light will be turned off.

[0010] In a preferred embodiment, the specific steps of adjusting the brightness of the lights of the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of personnel are as follows: defining the light intensity data and the activity status of personnel as input variables, and dividing them into different fuzzy sets respectively; defining the brightness adjustment of the lights of the landscape lighting system as an output variable, and dividing them into fuzzy sets; Formulate fuzzy rules to describe the impact of light intensity data and personnel activity status on the brightness adjustment of the landscape lighting system; perform fuzzy reasoning based on the fuzzy rules to determine the brightness adjustment plan of the landscape lighting system.

[0011] In a preferred embodiment, the specific process of evaluating the effect of the landscape intelligent adjustment control system according to the opening and closing control time response function and the energy-saving effect achieved by brightness adjustment is as follows: comparing and analyzing the evaluation coefficient of the intelligent adjustment control system with a preset system evaluation threshold; if the evaluation coefficient of the intelligent adjustment control system is greater than the preset system evaluation threshold, the intelligent adjustment control system is effective and there is no need to optimize the system temporarily; if the evaluation coefficient of the intelligent adjustment control system is less than the preset system evaluation threshold, the intelligent adjustment control system is not effective and the opening and closing control and brightness adjustment modules of the system need to be optimized.

[0012] Technical effects and advantages of the landscape lighting intelligent control system based on distributed optical sensor data fusion of the present invention: 1. The present invention uses distributed optical sensors to monitor parameters such as light intensity, color temperature, and environmental changes in the landscape area in real time. According to different environmental data, the system can dynamically adjust the brightness, color, and switch status of the lights. For example, when the natural light intensity changes, the system automatically adjusts the brightness of the landscape lights to achieve intelligent lighting control. By accurately adjusting the brightness and switch time of the landscape lighting, energy consumption can be effectively reduced and unnecessary energy waste can be avoided. Through distributed optical sensors, the system can work independently in different areas, enhancing the fault tolerance of the system. If a sensor fails, other sensors can continue to work to ensure the stability and reliability of the system. Through multi-point data acquisition and data fusion algorithms, the system can fuse and denoise the data of multiple sensors to further improve the accuracy and reliability of the data.

[0013] 2. The present invention senses environmental changes in real time and intelligently adjusts landscape lighting according to environmental changes, thereby achieving better landscape effects by adjusting lighting effects; intelligent control can reduce energy waste, achieve green environmental protection goals, reduce unnecessary electricity consumption, and meet the requirements of energy conservation and emission reduction; the system is usually a centralized control platform, through which managers can centrally monitor and manage the entire landscape lighting system, and view the lighting status and energy consumption data of each area in real time; the history system can record historical data and conduct trend analysis to provide a basis for future lighting design and energy-saving measures. The data analysis results can also optimize future lighting plans and provide a more personalized lighting experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1This is a schematic diagram of the structure of the landscape lighting intelligent control system with distributed optical sensor data fusion according to the present invention. DETAILED DESCRIPTION

[0015] 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.

[0016] Embodiment 1, Figure 1 The invention provides a landscape lighting intelligent control system based on distributed optical sensor data fusion.

[0017] A data collection module, used for acquiring environmental data in real time based on optical sensors; The optical sensor includes a light sensor and an infrared sensor; The light sensor is used to measure the light intensity of the environment; The infrared sensor is used to detect human activities in the area.

[0018] Using light sensors and infrared sensors to monitor ambient light and human activities in real time, combined with landscape lighting control systems, can bring many benefits, especially in terms of energy saving, improved environmental comfort, and system intelligence. The following are the specific functions and benefits: 1. Energy saving and consumption reduction Function of light sensor: The light sensor can detect the light intensity in the environment in real time. If it is daytime or the environment is bright, the system can automatically adjust or turn off the landscape lighting to avoid unnecessary energy consumption. At night or when the light is weak, the lighting intensity will automatically increase to ensure the visibility of the landscape; Function of infrared sensor: infrared sensor can sense the activities of people in the area. When human activities are detected, the landscape lights can automatically turn on or increase the brightness; When no one is around, the lights will automatically dim or turn off, which effectively avoids the landscape lighting being on for a long time when no one is around, further saving energy. Comprehensive effect: The combination of light and infrared sensors enables the lighting system to be dynamically adjusted according to actual needs, reducing unnecessary lighting time and energy waste, and greatly improving energy efficiency.

[0019] 2. Extend equipment life Reduce switching frequency: Sensor-controlled intelligent lighting systems can avoid switching lights on and off too frequently by sensing light and human activity in real time, reducing mechanical wear and electrical burden on lamps, thereby extending the service life of landscape lighting equipment; Avoid over-lighting: Adjust the brightness of the lighting according to the ambient light intensity to avoid the extra burden of excessive lighting on the lamps and further extend the life of the equipment; 3. Improved security Automatic lighting: Infrared sensors can sense the movement of people, ensuring that when someone enters the landscape area, the lights can be automatically turned on, thereby providing sufficient lighting and improving the safety of pedestrians or visitors; Intelligent response at night: At night or when the light is insufficient, if the infrared sensor detects human activity, the light will automatically brighten to ensure that the walking and activity areas will not be in danger due to insufficient lighting; 4. Improve comfort and user experience Personalized adjustment: Dynamic adjustment based on light intensity and activity detection can provide lighting that is more adaptable to the environment. For example, in a quiet park or scenic spot at night, the light will automatically adjust according to the surrounding brightness and human activities, allowing tourists to enjoy the natural landscape while feeling a comfortable lighting environment. Avoid excessive light interference: Infrared sensors can accurately sense whether there is human activity, preventing unnecessary lighting from affecting the tranquility of the environment. For example, if there is no human activity, landscape lighting can be dimmed or turned off to avoid affecting nearby residents or the natural ecology at night; 5. Intelligent control and management Remote monitoring and management: The intelligent lighting system with integrated light sensors and infrared sensors can be managed through a centralized control platform. The system can provide real-time feedback on the light intensity and personnel activity information in different areas, making it easier for relevant managers to make remote adjustments and management. System optimization: Based on sensor feedback data, the lighting system can be continuously optimized, such as automatically adjusting the lighting mode according to time periods, seasonal changes and other factors, further improving the overall system performance and user experience; 6. Environmental protection and sustainable development Reduce carbon emissions: Through reasonable lighting control and personnel detection, unnecessary lighting time and power consumption can be reduced, which not only saves energy but also reduces carbon emissions caused by electricity production, which is conducive to environmental protection and sustainable development; Adapt to different scenarios: The intelligent lighting control system can flexibly adjust the lighting according to the needs of different scenarios, such as a quiet natural scenic spot at night or a busy city square, to avoid excessive impact on the ecological environment and residents' lives; 7. Improve the beauty of the landscape Dynamic lighting effects: The combination of light sensors and infrared sensors can create more flexible and layered lighting effects. For example, infrared sensors can be used to sense the flow of people on a specific path or area, thereby adjusting the light intensity according to the number of people or activities, creating a more harmonious landscape effect; Avoid light pollution: By dynamically adjusting the light brightness, it is possible to avoid excessive brightness in unmanned areas, reduce light pollution, and maintain the original appearance of the natural environment, especially in ecologically sensitive areas.

[0020] A processing and fusion module is used to pre-process the environmental data and perform Bayesian fusion on the environmental data collected by multiple sensors of the same type to obtain a final environmental data estimate; the final environmental data estimate includes light intensity data and human activity information; The preprocessing of environmental data includes denoising and normalization. The specific process is as follows: Sensor data may contain noise, which needs to be denoised by a median filter, taking the median of the data over a period of time to smooth the data; Different sensors have different dimensions, so the data usually needs to be normalized to ensure that the impact of each data on the control decision can be compared on the same scale.

[0021] The goal of data fusion is to combine data information from different sensors to form a comprehensive evaluation index for decision-making and control; The Bayesian method evaluates the state of the environment by calculating the joint probability distribution of different sensor data. In the Bayesian framework, given the observations of each sensor, the goal of the system is to calculate the most likely state through Bayes' theorem. The specific steps for Bayesian fusion of environmental data collected by multiple sensors of the same type are as follows: First, we need to establish a prior distribution that follows a Gaussian distribution for the environmental data of each sensor. Assume that we have a preliminary estimate of the environmental data, which can be based on historical data, environmental knowledge, or assumptions. Model the observation model of each sensor, describe how the sensor perceives the environment, and calculate the likelihood function of each sensor; According to Bayes' theorem, combining the likelihood function and prior distribution of the sensor, the posterior distribution of the environmental data is updated, where the posterior distribution is the product of the prior distribution and the likelihood functions of all sensors; Based on Gaussian distribution, the sensor observation data is combined into a Gaussian model, and the sensor observation data is combined with the prior distribution and the sensor likelihood function to obtain the mean and standard deviation of the posterior distribution according to the preset calculation formula; The final environmental data estimate is obtained based on the mean of the posterior distribution, and the fusion process is optimized by adjusting the prior distribution and the sensor noise variance. This estimate is based on the result of the fusion of all sensor data. Compared with the measurement result of a single sensor, it is usually more accurate because the accuracy differences of each sensor are taken into account during the fusion process; The fusion result may be affected by factors such as sensor noise level and sensor quality, so the fusion process can be optimized by adjusting the prior distribution and sensor noise variance.

[0022] The final light intensity data and human activity information are obtained through data fusion.

[0023] The on / off control module is used to obtain the state of the landscape area through human activity information, and to control the on / off of the landscape lighting system in combination with the light intensity data and the preset light intensity threshold; The specific process of obtaining the landscape area status through human activity information is as follows: When the infrared sensor detects that there is no one in the landscape area, the landscape area status ; When the infrared sensor detects someone in the landscape area, the landscape area status

[0024] The light intensity is compared with a preset light intensity threshold, and when the light intensity is less than the preset light intensity threshold, or when the infrared sensor detects a person in the landscape area, the light is turned on; When the light intensity is greater than the preset light intensity threshold and the infrared sensor detects that there is no one in the landscape area, the light turns off; The formula for turning on and off the lights of the landscape lighting system is as follows: ; In the formula, Indicates that the light is on. Indicates that the light is off, L is the light intensity, is the preset light intensity threshold, is the state of the landscape area, Indicates that there are people in the landscape area. Indicates that there is no one in the landscape area; The brightness adjustment module is used to obtain the activity status of personnel through human activity information when the lights of the landscape area lighting system are turned on, and adjust the brightness of the lights of the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of personnel.

[0025] When the lights of the landscape area lighting system are turned on, the activity status of people is obtained through human activity information. When there are few people, that is, the activity intensity is low, it is determined to be a low activity state; when there are many people, that is, the activity intensity is high, it is determined to be a high activity state; The specific steps for adjusting the brightness of the lights in the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of personnel are as follows: Step C1, define the light intensity data and personnel activity status as input variables, and divide them into different fuzzy sets.

[0026] For example, "Low", "Medium", "High" for light intensity data, "Low", "Medium", "High" for personnel activity status.

[0027] Step C2, the brightness adjustment of the lights of the landscape lighting system is defined as an output variable, which is divided into fuzzy sets, for example, "Low", "High", for adjusting the brightness of the lights of the landscape lighting system.

[0028] Step C3, formulate a set of fuzzy rules to describe the impact of different input variables on output variables. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example: The light intensity data is marked as L, and the activity status of the personnel is marked as , the brightness of the lights in the landscape lighting system is adjusted, marked as P, and can be defined Rule 1: If (L is Low) and ( is High) then (P is High) Rule 2: If (L is High) and ( is Low) then (P is Low) ... Step C4, performing fuzzy reasoning according to fuzzy rules to determine a light brightness adjustment scheme for the landscape lighting system.

[0029] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although this embodiment takes three fuzzy sets as examples, in fact, the light intensity data, personnel activity status, and brightness adjustment of the lights in the landscape lighting system can be divided into more than three sets to facilitate better and more accurate identification.

[0030] Furthermore, for light intensity data, the judgment of the level of personnel activity status can be made by setting thresholds according to actual conditions; when the light intensity data is higher than 1000lx, it is marked as "High", when the personnel activity status is higher than 10, it is marked as "High", and so on. I will not go into details here.

[0031] The system evaluation module is used to analyze the response of the landscape lighting system's light on / off control, calculate the on / off control time response function, and evaluate the effect of the landscape intelligent control system based on the energy-saving effect achieved through brightness adjustment.

[0032] The specific calculation formula for analyzing the light on / off control response of the landscape lighting system and calculating the on / off control time response function is as follows: ; In the formula, is the opening and closing control time response function, K is the system constant, indicating the final steady-state value, t is the time, is the time constant of the system, which is used to describe the speed of the system response; The energy saving effect achieved through brightness adjustment is to measure the energy consumption of the light at full brightness and after brightness adjustment, and calculate the energy saving rate after brightness adjustment. The specific calculation formula is as follows: ; Where J is the energy saving rate after brightness adjustment, Q is the energy consumption of the light at full brightness, is the energy consumption after adjusting the brightness; According to the opening and closing control time response function, combined with the energy-saving effect achieved by brightness adjustment, the specific calculation formula for evaluating the effect of the landscape intelligent adjustment control system is as follows: ; In the formula, G is the evaluation coefficient of the intelligent regulation control system, is the opening and closing control time response function, is the weight factor of the on / off control time response function, J is the energy saving rate after brightness adjustment, is the energy saving rate weight factor; Compare and analyze the evaluation coefficient of the intelligent regulation control system with the preset system evaluation threshold. If the evaluation coefficient of the intelligent regulation control system is greater than the preset system evaluation threshold, the intelligent regulation control system has a good effect and does not need to be optimized temporarily. If the evaluation coefficient of the intelligent adjustment control system is less than the preset system evaluation threshold, the intelligent adjustment control system is not effective and the system's on / off control and brightness adjustment modules need to be optimized.

[0033] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0034] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0035] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0036] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0037] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0038] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A landscape lighting intelligent control system based on distributed optical sensor data fusion, characterized in that: include: Data collection module, processing and fusion module, opening and closing control module, brightness adjustment module, there are connections between modules: A data collection module, used for acquiring environmental data in real time based on optical sensors; A processing and fusion module, which is used to perform denoising on the environmental data, perform Bayesian fusion on the environmental data collected by multiple sensors of the same type, and obtain a final environmental data estimate based on Gaussian distribution, wherein the final environmental data estimate includes light intensity data and human activity information; The on / off control module is used to obtain the state of the landscape area through human activity information, and control the on / off of the landscape lighting system in combination with the light intensity and the preset light intensity threshold; The brightness adjustment module is used to obtain the activity status of personnel through human activity information when the lights of the landscape area lighting system are turned on, and adjust the brightness of the lights of the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of personnel; The system evaluation module is used to analyze the response of the landscape lighting system's light on / off control, calculate the on / off control time response function, and evaluate the effect of the landscape intelligent control system based on the energy-saving effect achieved through brightness adjustment.

2. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 1 is characterized in that: The optical sensor includes a light sensor and an infrared sensor; the light sensor is used to measure the light intensity of the environment; the infrared sensor is used to detect human activities in the area.

3. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 2 is characterized in that: The specific steps of performing Bayesian fusion on the environmental data collected by multiple sensors of the same type are as follows: Preliminary estimation of environmental data, establishing a prior distribution that obeys Gaussian distribution for each sensor's environmental data; Build an observation model for each sensor, obtain the sensor's observation data, describe how the sensor perceives the environment, and calculate the likelihood function of each sensor; According to Bayes' theorem, the posterior distribution of environmental data is updated by combining the likelihood function and prior distribution of the sensor; Based on Gaussian distribution, the sensor observation data is combined into a Gaussian model, and the sensor observation data is combined with the prior distribution and the sensor likelihood function to obtain the mean and standard deviation of the posterior distribution according to the preset calculation formula; According to the mean of the posterior distribution, the final environmental data estimation is obtained, and the fusion process is optimized by adjusting the prior distribution and the sensor noise variance.

4. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 3 is characterized in that: The specific process of turning on and off the lights of the landscape lighting system is as follows: When the infrared sensor detects that there is no one in the landscape area, the landscape area status ; When the infrared sensor detects someone in the landscape area, the landscape area status ; The light intensity is compared with a preset light intensity threshold, and when the light intensity is less than the preset light intensity threshold, or when the infrared sensor detects a person in the landscape area, the light is turned on; When the light intensity is greater than the preset light intensity threshold and the infrared sensor detects that there is no one in the landscape area, the light turns off.

5. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 4 is characterized in that: The specific steps of adjusting the brightness of the lights of the landscape lighting system based on the fuzzy reasoning process according to the light intensity data and the activity status of the personnel are as follows: The light intensity data and personnel activity status are defined as input variables, and they are divided into different fuzzy sets respectively; The brightness adjustment of the lights in the landscape lighting system is defined as the output variable, which is divided into fuzzy sets; Formulate fuzzy rules to describe the impact of light intensity data and personnel activity status on the brightness adjustment of landscape lighting systems; Fuzzy reasoning is performed based on fuzzy rules to determine the light brightness adjustment plan for the landscape lighting system.

6. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 5 is characterized in that: The specific calculation formula for analyzing the light on / off control response of the landscape lighting system and calculating the on / off control time response function is as follows: ; In the formula, is the opening and closing control time response function, K is the system constant, indicating the final steady-state value, t is the time, is the time constant of the system, which describes how quickly the system responds.

7. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 6 is characterized in that: The specific calculation formula for the energy saving effect achieved by brightness adjustment is as follows: ; In the formula, J is the energy saving rate after brightness adjustment, Q is the energy consumption of the light at full brightness, It is the energy consumption after adjusting the brightness.

8. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 7 is characterized in that: According to the opening and closing control time response function, combined with the energy-saving effect achieved by brightness adjustment, the specific calculation formula for evaluating the effect of the landscape intelligent adjustment control system is as follows: ; In the formula, G is the evaluation coefficient of the intelligent regulation control system, is the opening and closing control time response function, is the weight factor of the on / off control time response function, J is the energy saving rate after brightness adjustment, is the energy saving rate weight factor.

9. The landscape lighting intelligent control system based on distributed optical sensor data fusion according to claim 8 is characterized in that: According to the opening and closing control time response function, the specific process of evaluating the effect of the landscape intelligent regulation control system combined with the energy saving effect achieved by brightness adjustment is as follows: Compare and analyze the intelligent regulation control system evaluation coefficient with the preset system evaluation threshold; If the intelligent regulation control system evaluation coefficient is greater than the preset system evaluation threshold, the intelligent regulation control system is effective and there is no need to optimize the system temporarily; If the evaluation coefficient of the intelligent adjustment control system is less than the preset system evaluation threshold, the intelligent adjustment control system is not effective and the system's on / off control and brightness adjustment modules need to be optimized.

Images