Control system for mosquito killing lamp and control method thereof

Abstract

The invention relates to the technical field of automatic control, in particular to a control system for a mosquito killing lamp and a control method thereof, and the control system comprises the following modules: a mosquito behavior analysis module, a spectral efficiency analysis module, a trap lamp parameter configuration module, a voltage parameter adjustment module and an automatic counting module. By analyzing the relationship between the mosquito activity number and various environmental conditions, identifying the mosquito activity mode, combining with real-time monitoring of the environmental conditions, optimizing the start-stop parameters and spectral band selection of the mosquito killer lamp, improving the adaptability and trapping effect of the trap lamp, reducing the invalid working time, and improving the efficiency of the trap lamp. Real-time parameter adjustment of a high-voltage power grid, optimization of the working efficiency of the power grid and reduction of energy consumption are achieved by analyzing voltage parameters needed for killing various mosquitoes, the number of trapped mosquitoes is counted in real time by analyzing current changes, the trapping efficiency is evaluated, the working parameters of a lamp and the power grid are dynamically optimized according to a result, and the trapping effect is improved. And the working efficiency and the resource utilization efficiency are improved.

Description

Technical Field

[0001] The invention relates to the field of automatic control technology, in particular to a control system and a control method for a mosquito-killing lamp. Background Art

[0002] The field of automatic control technology aims to improve efficiency, accuracy and safety and reduce human intervention by designing, developing and implementing systems, including sensors for monitoring the environment or equipment status, controllers for processing detection information, and using drivers to execute control commands to adjust operations. It is applied to multiple industries such as industrial automation, robotics, aerospace, transportation, energy management and home automation. By enhancing the intelligence level of the system, autonomously learning and adapting to changing environmental conditions, combined with the Internet of Things and artificial intelligence, it can achieve real-time analysis and processing of data, improve response speed and the intelligence level of operations.

[0003] Among them, the control system for mosquito killer lamps is used for automatic control of mosquito killer lamps, aiming to intelligently manage the operation of mosquito killer lamps, including automatic monitoring of mosquito activity, and adjusting the operating status of mosquito killer lamps according to detection and monitoring data to achieve effective mosquito control. Mosquito activity data is analyzed through intelligent algorithms, and mosquito killer lamps are automatically turned on during peak mosquito activity and turned off when not in use, thereby optimizing energy use and improving mosquito killing effects. The efficacy of mosquito killer lamps is improved, and the light wave band of the insect attractant lamp is adjusted according to the type and activity pattern of the mosquito to enhance its ability to lure and kill.

[0004] The control technology used in traditional mosquito killer lamps relies on fixed preset programs to control the switching of mosquito killer lamps. It cannot make real-time dynamic adjustments to mosquito activities under different environmental conditions, and cannot adjust the working mode of mosquito killer lamps according to temperature, humidity and light conditions. As a result, mosquito killer lamps cannot achieve the maximum mosquito killing effect at the best time. There is a lack of intelligent response mechanism, and it is impossible to make precise adjustments in real time according to the activity status of mosquitoes. There is no targeted energy consumption optimization and real-time adjustment of working status, resulting in energy waste. In terms of high-voltage power grid control, a single voltage setting is used, and there is a lack of consideration for the active time period of mosquitoes, resulting in electricity waste. The evaluation of the trapping efficiency of insect traps relies on manual statistics, and it is difficult to achieve automatic feedback and optimization of working parameters. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a control system and a control method for mosquito killer lamps, which can identify the activity patterns of mosquitoes by analyzing the relationship between the number of mosquito activities and various environmental conditions, and optimize the start and stop parameters and spectral band selection of mosquito killer lamps in combination with real-time monitoring of environmental conditions, thereby improving the adaptability and trapping effect of insect attractant lamps, reducing ineffective working time, optimizing energy use, and realizing real-time parameter adjustment of high-voltage power grids by analyzing the voltage parameters required for killing various mosquitoes, optimizing the working efficiency of the power grid and reducing energy consumption. By analyzing the current changes, the number of trapped mosquitoes can be counted in real time, the trapping efficiency can be evaluated, and the working parameters of the lamps and power grids can be dynamically optimized according to the results, thereby improving working efficiency and resource utilization efficiency. In order to solve the above technical problems, the present invention provides the following technical solutions: A control system for a mosquito killer lamp, the system comprising: The mosquito behavior analysis module collects temperature, humidity and light data in real time based on mosquito activity monitoring data. It analyzes the number of mosquito activities under various environmental conditions, evaluates the intensity and frequency of mosquito activities under various conditions, and generates activity pattern prediction results. The spectral efficiency analysis module analyzes the attractiveness of multiple spectral bands to mosquitoes based on the activity pattern prediction results, considers the energy consumption of the insect attractant lamps in multiple spectral bands, identifies the optimal spectral bands for attracting and killing multiple mosquitoes, and generates an insect attractant spectrum matching list; The insect attractant lamp parameter configuration module adjusts the working parameters of the insect attractant lamp, including the start and stop time and the spectral band selection, based on the insect attractant spectrum matching list and in combination with the real-time environmental monitoring data, and generates real-time adjustment control parameters; The voltage parameter adjustment module adjusts the voltage parameters of the high-voltage power grid in multiple time periods based on the real-time adjustment control parameters, according to the active time period information of various mosquitoes, and takes into account the working energy consumption of the power grid, and generates a power grid parameter optimization result; The automatic counting module monitors the current data of the high-voltage power grid in real time through the power grid parameter optimization results, counts the number of trapped mosquitoes by analyzing the current changes, analyzes the trapping efficiency and optimizes the working parameters of the insect trap lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

[0006] The following is a further optimization of the above technical solution by the present invention: The activity pattern prediction result includes the predicted number of mosquito activity record data, the predicted activity intensity change information, and real-time environmental monitoring information; the insect attractant spectrum matching list includes the spectral band attraction score, the optimal spectral band, and the spectral band working energy consumption data; the real-time adjustment control parameters include the start and stop time of the insect attractant lamp, the selected spectral band, and the working parameter adjustment value according to the environmental conditions; the power grid parameter optimization result includes the high-voltage power grid voltage value parameter, the power grid working time period, and the high-voltage power grid energy consumption data; the trapping efficiency evaluation result includes the number of mosquitoes trapped, the trapping efficiency change trend, and the working parameter adjustment record.

[0007] Further optimization: The mosquito behavior analysis module includes: The environmental data collection submodule uses temperature and humidity sensors and light sensors to collect temperature, humidity and light data in real time based on mosquito activity monitoring data to generate an environmental monitoring data set; The activity number analysis submodule generates mosquito activity analysis results by analyzing the active number of mosquitoes under various environmental conditions based on the environmental monitoring data set, calculating the correlation between mosquito activity and various environmental conditions; The active time prediction submodule analyzes and predicts the active periods of mosquitoes under various environmental conditions based on the mosquito activity analysis results, and generates activity pattern prediction results.

[0008] Further optimization: The specific formula for calculating the correlation between mosquito activity and various environmental conditions is: ; in, represents the correlation coefficient between mosquito activity and environmental conditions, Representative in the The environmental conditions at each time point, including temperature, humidity, and light, Representative in the The mosquito activity value at each time point, represents the average value of environmental conditions, represents the average mosquito activity level. represents the total number of data points, that is, the number of observed time points, An index representing a time point.

[0009] Further optimization: The spectral efficiency analysis module includes: The working energy consumption analysis submodule collects the energy consumption data of the insect attractant lamp working in multiple spectral bands based on the activity mode prediction result, and generates an insect attractant lamp energy consumption data set; The attraction evaluation submodule is based on the energy consumption data set of the insect attractant lamp, and by identifying the influence of multiple spectral bands on the number of active mosquitoes, calculates the attraction of multiple spectral bands to multiple mosquitoes, and generates spectral attraction evaluation data; The spectral band identification submodule identifies the optimal spectral bands for trapping various mosquitoes based on the spectral attraction evaluation data and taking into account the working energy consumption, and generates an insect attractant spectrum matching list.

[0010] Further optimization: The specific formula for calculating the attraction of multiple spectral bands to multiple mosquitoes is: ; in, Represents the attractiveness score of a specific spectral band to mosquitoes, Represents the number of active mosquitoes observed in the current spectral band, represents the maximum number of mosquitoes observed in all tested spectral bands, It represents the duration of mosquitoes' continuous activity in this band. represents the total observation time, Represents the frequency of mosquitoes flying in this band. represents the maximum flight frequency observed in all tested bands, Represents the average distance between mosquitoes and the light source in this band. Represents the maximum measurement distance of the observation area.

[0011] Further optimization: The insect attractant lamp parameter configuration module includes: The environmental parameter analysis submodule predicts and identifies the activity time periods of various mosquitoes based on the insect attractant spectrum matching list and real-time environmental monitoring data, including temperature, humidity and light intensity, and generates real-time environmental analysis results; The working period configuration submodule identifies the working time period required for the insect attractant lamp based on the real-time environmental analysis result and the active periods of various mosquitoes, and generates the start and stop parameter configuration of the insect attractant lamp; The control parameter setting submodule is based on the start and stop parameter configuration of the insect attractant lamp, and according to the active mosquito species in the target period, adjusts the working spectrum band of the insect attractant lamp at the target time to generate real-time adjustment control parameters.

[0012] Further optimization: the voltage parameter adjustment module includes: The voltage demand analysis submodule analyzes the voltage intensity required to kill various mosquitoes based on the real-time adjustment control parameters, and generates voltage demand analysis data; The power grid parameter configuration submodule adjusts the voltage operating parameters of the high-voltage power grid in multiple time periods based on the voltage demand analysis data and the active time periods of various mosquitoes to generate an operating voltage parameter configuration; The power grid energy consumption recording submodule is based on the working voltage parameter configuration, monitors the working energy consumption of the high-voltage power grid in real time, records the energy consumption data, and generates power grid parameter optimization results.

[0013] Further optimization: the automatic counting module includes: The current change analysis submodule is based on the power grid parameter optimization result, and identifies the current characteristics corresponding to various mosquitoes by analyzing the current changes corresponding to the high-voltage power grid killing mosquitoes, and generates a current characteristic analysis result; The real-time current monitoring submodule monitors the current data of the high-voltage power grid in real time based on the current characteristic analysis result, identifies the current change and records the number of various mosquitoes killed, and generates current change monitoring data; The trapping efficiency optimization submodule uses the current change monitoring data to analyze the trapping efficiency of the mosquito killer lamp, and adjusts the working parameters of the mosquito killer lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

[0014] The present invention also provides a control method for a mosquito killer lamp. The method is based on the control system for the mosquito killer lamp, and the method comprises: S1: Based on the mosquito activity monitoring data, the environmental temperature, humidity and light intensity data are collected in real time. By analyzing the number of mosquito activities under various environmental conditions, the activity intensity and frequency of various mosquitoes are identified, and the activity pattern prediction results are generated; S2: According to the activity pattern prediction results, the attraction and working energy consumption of multiple spectral bands to mosquitoes are evaluated, the optimal spectral band of the insect attractant lamp is identified, and an insect attractant spectrum matching list is generated; S3: using the insect attractant spectrum matching list and combining it with real-time environmental monitoring data, adjusting the start and stop time and spectral band of the insect attractant lamp to generate real-time adjustment control parameters; S4: adjusting the control parameters in real time, according to the various mosquito activity time periods, taking into account the working energy consumption of the high-voltage power grid, adjusting the working voltage parameters of the high-voltage power grid, and generating a power grid parameter optimization result; S5: Based on the grid parameter optimization result, by analyzing the current change corresponding to the high-voltage grid killing mosquitoes, recording the types and numbers of mosquitoes killed, and generating mosquito trapping data records; S6: Using the mosquito trapping data records, evaluating the trapping efficiency, and optimizing the working parameters of the insect trap lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

[0015] The present invention adopts the above technical scheme, which is ingenious in conception. By analyzing the relationship between the number of mosquito activities and various environmental conditions, the activity pattern of mosquitoes is identified, and combined with real-time monitoring of environmental conditions, the start and stop parameters and spectral band selection of mosquito killer lamps are optimized, the adaptability and trapping effect of insect attractant lamps are improved, the invalid working time is reduced, and energy use is optimized. By analyzing the voltage parameters required for killing various mosquitoes, real-time parameter adjustment of the high-voltage power grid is achieved, the working efficiency of the power grid is optimized and energy consumption is reduced. By analyzing the current changes, the number of trapped mosquitoes is counted in real time, the trapping efficiency is evaluated, and the working parameters of the lamps and power grids are dynamically optimized according to the results, thereby improving work efficiency and resource utilization efficiency.

[0016] The present invention is further described below in conjunction with the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system flow chart of an embodiment of the present invention; Figure 2 Schematic diagram of a system framework in an embodiment of the present invention; Figure 3 This is a flow chart of a mosquito behavior analysis module in an embodiment of the present invention; Figure 4 is a flow chart of a spectral efficiency analysis module in an embodiment of the present invention; Figure 5 This is a flow chart of the parameter configuration module of the insect attractant lamp in an embodiment of the present invention; Figure 6 This is a flow chart of a voltage parameter adjustment module in an embodiment of the present invention; Figure 7 This is a flow chart of an automatic counting module in an embodiment of the present invention; Figure 8 Schematic diagram of the method steps in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] like Figure 1-7 As shown, a control system for a mosquito killer lamp, the processing flow of the system includes the following modules: The mosquito behavior analysis module collects temperature, humidity and light data in real time based on mosquito activity monitoring data. It analyzes the number of mosquito activities under various environmental conditions, evaluates the intensity and frequency of mosquito activities under various conditions, and generates activity pattern prediction results. The spectral efficiency analysis module analyzes the attractiveness of multiple spectral bands to mosquitoes based on the activity pattern prediction results, considers the energy consumption of insect attractant lamps in multiple spectral bands, identifies the optimal spectral bands for attracting and killing multiple mosquitoes, and generates an insect attractant spectrum matching list; The insect attractant lamp parameter configuration module adjusts the working parameters of the insect attractant lamp, including the start and stop time and spectral band selection, based on the insect attractant spectrum matching list and combined with real-time environmental monitoring data, and generates real-time adjustment control parameters; The voltage parameter adjustment module adjusts the control parameters in real time, based on the active time period information of various mosquitoes, takes into account the working energy consumption of the power grid, adjusts the voltage parameters of the high-voltage power grid in multiple time periods, and generates power grid parameter optimization results; The automatic counting module monitors the current data of the high-voltage power grid in real time through the optimization results of the power grid parameters, counts the number of trapped mosquitoes by analyzing the current changes, analyzes the trapping efficiency and optimizes the working parameters of the insect trap lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

[0019] The activity pattern prediction results include the predicted number of mosquito activity records, predicted activity intensity change information, and real-time environmental monitoring information. The insect attractant spectrum matching list includes the spectral band attraction score, the optimal spectral band, and the spectral band working energy consumption data. The real-time adjustment of control parameters includes the start and stop time of the insect attractant lamp, the selected spectral band, and the working parameter adjustment value according to environmental conditions. The power grid parameter optimization results include the high-voltage power grid voltage value parameters, the power grid working time period, and the high-voltage power grid energy consumption data. The trapping efficiency evaluation results include the number of mosquitoes trapped, the trapping efficiency change trend, and the working parameter adjustment record.

[0020] See also Figure 2 and Figure 3 , the mosquito behavior analysis module includes: The environmental data collection submodule uses temperature and humidity sensors and light sensors to collect temperature, humidity and light data in real time based on mosquito activity monitoring data to generate an environmental monitoring data set; In the environmental data acquisition submodule, based on the mosquito activity monitoring data, real-time collection of temperature, humidity and light data is performed. The temperature and humidity sensors collect the temperature and humidity information of the environment. The target data is output through analog or digital signals and converted into a readable digital format after signal conditioning, including analog-to-digital conversion. The light sensor measures the light intensity in the environment, uses the photoelectric effect to convert the light signal into an electrical signal, and performs signal conditioning. The collected data is transmitted to the central data processing unit via wireless or wired means. The data is formatted and stored in the environmental monitoring data set to provide raw input for subsequent analysis. The data synchronization and time marking technology involved in the process ensure the integrity of the data set and the accuracy of time series analysis.

[0021] The activity number analysis submodule is based on the environmental monitoring data set. It analyzes the number of active mosquitoes under various environmental conditions, calculates the correlation between mosquito activity and various environmental conditions, and generates mosquito activity analysis results. The specific formula for calculating the correlation between mosquito activity and various environmental conditions is: ; in, represents the correlation coefficient between mosquito activity and environmental conditions, Representative in the The environmental conditions at each time point, including temperature, humidity, and light, Representative in the The mosquito activity value at each time point, represents the average value of environmental conditions, represents the average mosquito activity level. represents the total number of data points, that is, the number of observed time points, An index representing a time point.

[0022] formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: The formula is used to calculate the correlation coefficient between mosquito activity and environmental conditions, and to identify the degree of correlation between mosquito activity and environmental conditions; Parameter meaning and setting value: Representative in the The environmental condition value at a time point, assuming that the temperature data is collected 5 times within an hour. ; Representative in the The mosquito activity at five time points. Assume that the number of mosquitoes measured at the same five time points is 2, 5, 3, 4, and 6, that is, ; represents the average value of environmental conditions, ; represents the average mosquito activity level. ; Substitute the parameters into the formula for calculation: Calculate the numerator part: ; ; Calculate the denominator: ; ; Calculate the correlation coefficient: ; result The results show that there is a strong positive correlation between mosquito activity and environmental conditions, and temperature has a significant effect on mosquito activity. The values ​​are used to provide data support for the adjustment and optimization of mosquito lamp parameters.

[0023] The active time prediction submodule analyzes and predicts the active periods of mosquitoes under various environmental conditions based on the mosquito activity analysis results, and generates activity pattern prediction results; In the active time prediction submodule, based on the results of mosquito activity analysis, the autoregressive moving average model is used to predict the active periods of mosquitoes under various environmental conditions. According to the time series data of mosquito activities, the stationarity of the data is determined by the ADF test. Combined with differential processing, the parameters of the model, including the number of lag terms, are determined through autocorrelation function and partial autocorrelation function chart analysis. Statistical software is used to fit the model, such as the forecast package of R language, for model training and verification. According to the predicted data output by the model, the high-activity time period of mosquitoes is determined to help optimize the timeliness and efficiency of mosquito control measures. The generated activity pattern prediction results describe in detail the future activity trends of non-stop mosquitoes.

[0024] See also Figure 2 and Figure 4 , the spectral efficiency analysis module includes: The working energy consumption analysis submodule collects the energy consumption data of insect trap lamps working in multiple spectral bands based on the activity pattern prediction results, and generates an insect trap lamp energy consumption data set; In the working energy consumption analysis submodule, based on the activity pattern prediction results, energy consumption data collection of insect attractant lamps working in different spectral bands is performed. The data is collected by setting up an energy consumption monitoring system. The energy consumption of each spectral band is continuously monitored by current sensors and power meters. The data acquisition system includes multiple sensors, each sensor corresponds to a spectral band, and transmits power consumption data to the central processing unit in real time. The collected energy consumption data is preliminarily filtered and cleaned to remove abnormal data points caused by equipment failure or external interference. The data is sent to the cloud server via a wireless network for storage and analysis. The technologies used include data compression and encryption technology to ensure the security and integrity of the data during transmission. The collected and processed data form an insect attractant lamp energy consumption data set, which records the energy consumption in each spectral band and provides accurate basic data for subsequent attraction evaluation.

[0025] The attraction evaluation submodule is based on the energy consumption dataset of insect trap lamps. It identifies the effects of multiple spectral bands on the number of active mosquitoes, calculates the attraction of multiple spectral bands to multiple mosquitoes, and generates spectral attraction evaluation data. The specific formula for calculating the attractiveness of multiple spectral bands to multiple mosquitoes is: ; in, Represents the attractiveness score of a specific spectral band to mosquitoes, Represents the number of active mosquitoes observed in the current spectral band, represents the maximum number of mosquitoes observed in all tested spectral bands, It represents the duration of mosquitoes' continuous activity in this band. represents the total observation time, Represents the frequency of mosquitoes flying in this band. represents the maximum flight frequency observed in all tested bands, Represents the average distance between mosquitoes and the light source in this band. Represents the maximum measurement distance of the observation area.

[0026] formula: ; Detailed explanation of the formula and the process of formula calculation and derivation: The formula is used to calculate the attractiveness of different spectral bands to mosquitoes and evaluate the attractiveness of multiple spectral bands to multiple mosquitoes; Parameter meaning and setting value: According to laboratory monitoring data: Represents the number of active mosquitoes observed in the current spectral band. Assume that the number of active target mosquito species measured by the infrared sensor at a wavelength of 520nm is 82; Represents the maximum number of mosquitoes observed in all tested spectral bands, assuming that the maximum number of mosquitoes monitored in all bands is 95; It represents the duration of mosquito activity in this band. Assume that mosquitoes are continuously active for 38 minutes in the 520nm band through time-series video recording; Represents the total observation time, assuming the observation time is 60 minutes; High-speed camera statistics show that the average flight frequency of target mosquitoes in the 520nm band is 42 times / minute; Represents the maximum flight frequency observed in all test bands, assuming that the maximum flight frequency of all-band monitoring is 55 times / minute; Represents the average distance between mosquitoes and the light source in this band. Assume that the average distance of target mosquitoes in the 520nm band is 0.4 meters; Represents the maximum measurement distance of the observation area, assuming the observation radius is 2 meters; Substitute the parameters into the formula for calculation: ; ; ; ; The result of 0.382 indicates that the 520nm band has a moderate attraction to the target mosquitoes. The numerical value is used to evaluate the attraction of multiple spectral bands to mosquitoes and select the optimal working parameters of mosquito traps.

[0027] The spectral band identification submodule identifies the optimal spectral bands for trapping various mosquitoes based on the spectral attraction evaluation data and considering the working energy consumption, and generates a list of insect attractant spectrum matching; In the spectral band identification submodule, the optimal spectral band is identified based on the spectral attraction evaluation data. The decision support system is used to combine the attraction evaluation data and energy consumption data to determine the optimal spectral band through cost-benefit analysis, including setting multiple evaluation indicators, such as attraction efficiency, energy consumption cost and durability. The weighted scoring method is used to calculate the comprehensive score for each spectral band. During the scoring process, the weights are allocated based on historical data and expert experience, and are adjusted through optimization algorithms such as genetic algorithms to achieve the optimal weight allocation. Through target analysis and decision-making processes, an insect attractant spectrum matching list is generated. The list details the optimal spectral bands obtained based on the attraction and energy consumption data analysis, providing precise guidance for the actual configuration of insect attractants.

[0028] See also Figure 2 and Figure 5 , the insect trap lamp parameter configuration module includes: The environmental parameter analysis submodule predicts and identifies the activity time periods of various mosquitoes based on the insect attractant spectrum matching list and real-time environmental monitoring data, including temperature, humidity, and light intensity, and generates real-time environmental analysis results; In the environmental parameter analysis submodule, based on the insect attractant spectrum matching list, predictive analysis of temperature, humidity, and light intensity data is performed. Data prediction technology, including the random forest model of machine learning, is used to process real-time environmental monitoring data. Real-time data of temperature, humidity, and light intensity are collected from the environmental sensor system. The target data is preliminarily cleaned and formatted to meet the input requirements of the prediction model. During the preprocessing process, outliers in the data are identified and corrected, and the data is normalized to reduce the impact of different measurement ranges and units. The data is analyzed using the random forest algorithm. Model training relies on historical monitoring data and known mosquito activity patterns. Environmental factors related to mosquito activity intensity are identified, and how each environmental factor affects the mosquito activity time period is predicted. Real-time environmental analysis results are generated. The results illustrate the mosquito activity time period under current and predicted environmental conditions, providing a basis for adjusting the insect attractant light strategy.

[0029] The working period configuration submodule is based on the real-time environmental analysis results and the active periods of various mosquitoes to identify the working time period of the insect trap lamp and generate the start and stop parameter configuration of the insect trap lamp; In the working period configuration submodule, the working time period configuration is executed based on the real-time environmental analysis results, and the start and stop time of the insect trap lamp is optimized using the linear programming model. According to the various mosquito active periods predicted in the real-time environmental analysis results, the potential working time window of the insect trap lamp is set. The time window in the model is divided into multiple small time periods, and each time period is assigned a start or stop decision variable to maximize the mosquito trapping efficiency and minimize energy consumption. The constraints include the operating restrictions and safety standards of the equipment. The mosquito activity intensity provided by the historical data and the prediction model is used to determine the optimal working time period by solving the linear programming model. The optimization software CPLEX or Gurobi is used for calculation. The generated insect trap lamp start and stop parameter configuration lists the working status of the insect trap lamp in each time period to ensure that it is started during the most active period of mosquitoes, thereby improving energy utilization efficiency and trapping effect.

[0030] The control parameter setting submodule is based on the start and stop parameter configuration of the insect attractant lamp, and according to the active mosquito species in the target period, adjusts the working spectrum band of the insect attractant lamp at the target time and generates real-time adjustment control parameters; In the control parameter setting submodule, based on the start and stop parameter configuration of the insect trap lamp, the working spectral band of the insect trap lamp is adjusted, and the dynamic programming method is used to optimize the selection of spectral bands. According to the active mosquito species in the target period and their response to different spectral bands, the optimal spectral band that the insect trap lamp should use in each time period is set. The dynamic programming algorithm takes into account the multi-dimensional data of spectral efficiency, energy consumption and mosquito attraction. By constructing state transfer equations and decision equations, the most appropriate spectral setting for each time period is gradually determined. Each decision step is based on the optimal solution of the previous time period and the environmental conditions of the current time period to ensure the continuity and efficiency of the overall strategy. The generated real-time adjustment control parameters specify in detail the spectral band that the insect trap lamp should use in each time period to achieve the most efficient trapping of specific mosquito species.

[0031] See also Figure 2 and Figure 6 , the voltage parameter adjustment module includes: The voltage demand analysis submodule adjusts the control parameters in real time, analyzes the voltage intensity required to kill various mosquitoes, and generates voltage demand analysis data; In the voltage demand analysis submodule, based on real-time adjustment of control parameters, voltage intensity demand analysis is performed. Electrical engineering analysis and load demand prediction models are used to analyze the working status of insect traps at different times and in different spectral bands, and determine the current demand in each state. The steps involve detailed measurements of the electrical characteristics of the insect traps, including resistance, power factor and maximum load capacity. The tool used is an electric power analyzer. Through load prediction models such as time series analysis, the total current demand in each time period is predicted. Taking into account the start and stop cycle of the insect trap and the expected working intensity, the model is adjusted according to historical power usage data and the operation log of the insect trap to ensure the accuracy of the prediction. The analysis results generate voltage demand analysis data. The target data lists in detail the voltage and current requirements of the insect traps in different working periods, providing a basis for the adjustment of power grid parameters.

[0032] The grid parameter configuration submodule adjusts the voltage operating parameters of the high-voltage grid in multiple time periods based on the voltage demand analysis data and the active time periods of various mosquitoes, and generates the operating voltage parameter configuration; In the grid parameter configuration submodule, based on the voltage demand analysis data, the voltage working parameter adjustment of the high-voltage grid is executed. The dynamic adjustment technology in the grid management system is used to adjust the voltage parameters. The target voltage level is set according to the voltage demand analysis data to ensure that there is sufficient power supply in each time period to meet the operating requirements of the insect attractant lamp. In the process, the load management system is used to monitor and adjust the high-voltage grid in real time, including peak reduction and valley filling strategies to optimize the use of power resources. Predictive control algorithms are used to predict and respond to changes in grid load to ensure the timeliness and accuracy of voltage adjustment. Through the target comprehensive control and management strategy, the working voltage parameter configuration is generated, and the voltage setting of the high-voltage grid in each time period is specified, providing the necessary power support to ensure the effective operation of the insect attractant lamp.

[0033] The power grid energy consumption recording submodule is based on the working voltage parameter configuration, monitors the working energy consumption of the high-voltage power grid in real time, records the energy consumption data, and generates the power grid parameter optimization results; In the power grid energy consumption recording submodule, based on the working voltage parameter configuration, the energy consumption monitoring and recording of the high-voltage power grid are performed. The process uses the energy consumption monitoring system, including electricity meters and data acquisition equipment, to record the energy consumption of the power grid in real time. The collection of energy consumption data involves multiple detection points, including main transmission lines and distribution branches, to ensure the comprehensiveness and representativeness of the data. After the data is collected, it is processed and analyzed through the data analysis platform, including energy consumption trend analysis and abnormal consumption detection. The energy efficiency evaluation model is used to compare the energy consumption efficiency under different intervals and voltage settings, which helps to identify energy waste and potential energy-saving measures. Through a strict monitoring and analysis process, the power grid parameter optimization results are generated. The target results show in detail the energy consumption and optimization potential of the power grid in actual operation, providing a scientific basis for energy efficiency improvement and cost control.

[0034] See also Figure 2 and Figure 7 , the automatic counting module includes: The current change analysis submodule is based on the grid parameter optimization results. By analyzing the current changes corresponding to the high-voltage grid killing mosquitoes, it identifies the current characteristics corresponding to various mosquitoes and generates current characteristic analysis results. In the current change analysis submodule, based on the grid parameter optimization results, the current change analysis during high-voltage grid mosquito control is performed. Fourier transform analysis is used to identify and analyze the characteristic frequencies in the current waveform. The current changes associated with the mosquito killing activities are recorded in detail, and current data is collected from the grid monitoring system. The data includes time series records of the current, recording the current fluctuations during grid operation. The current signal in the time domain is converted into a frequency domain signal using FFT, and specific current fluctuation patterns are identified. Each type of mosquito forms a unique frequency component in the current waveform due to its different body shape and resistance. The identified frequency components are used to distinguish different types of mosquitoes and classify the current characteristics of each mosquito. The generated current characteristic analysis results provide detailed information about the current changes corresponding to different mosquitoes, which is crucial for the optimization of subsequent monitoring and killing activities.

[0035] The real-time current monitoring submodule monitors the current data of the high-voltage power grid in real time based on the current characteristic analysis results, identifies current changes and records the number of various mosquitoes killed, and generates current change monitoring data; In the real-time current monitoring submodule, based on the current characteristic analysis results, real-time monitoring of the current data of the high-voltage power grid is performed. The process uses current sensors and real-time data acquisition systems to monitor the current changes of the entire power grid. The monitoring system regularly receives data from the sensors and uses data acquisition software to record current readings. The collected current data is analyzed through pattern recognition technology and support vector machines to identify waveforms that match known mosquito current characteristics. The killing events of different mosquitoes are recorded and classified in real time. The generated current change monitoring data reflects the current state of the power grid, provides instant feedback on the efficiency of mosquito control, and provides data support for adjusting strategies and optimizing energy consumption.

[0036] The trapping efficiency optimization submodule uses the current change monitoring data to analyze the trapping efficiency of the mosquito killer lamp, and adjusts the working parameters of the insect trap lamp and the high-voltage power grid to generate the trapping efficiency evaluation results; In the trapping efficiency optimization submodule, the current change monitoring data is used to perform trapping efficiency analysis and adjustment of the insect trap lamp. Statistical analysis methods, such as regression analysis, are used to evaluate the insect trapping efficiency under different spectral bands and current settings. The data obtained from the real-time current monitoring module is used to calculate the insect trapping success rate under each setting, and combined with the energy consumption data for cost-benefit analysis. Tableau is used in the analysis process to graphically present the relationship between the trapping rate and energy consumption, helping decision makers understand the efficiency of different configurations. According to the target analysis results, the parameters of the insect trap lamp and the high-voltage power grid are adjusted to optimize the light intensity and power grid voltage to achieve the best energy efficiency ratio. The generated trapping efficiency evaluation results describe the trapping efficiency under various parameter configurations in detail, providing a scientific basis for optimizing the insect trapping strategy.

[0037] See also Figure 8 A control method for a mosquito killer lamp is provided. The control method for a mosquito killer lamp is used to execute the control system for the mosquito killer lamp. The method comprises: S1: Based on the mosquito activity monitoring data, the environmental temperature, humidity and light intensity data are collected in real time. By analyzing the number of mosquito activities under various environmental conditions, the activity intensity and frequency of various mosquitoes are identified, and the activity pattern prediction results are generated; S2: Based on the activity pattern prediction results, evaluate the attractiveness and working energy consumption of multiple spectral bands to mosquitoes, identify the optimal spectral band of the insect attractant lamp, and generate an insect attractant spectrum matching list; S3: Using the insect attractant spectrum matching list and combining it with real-time environmental monitoring data, the start and stop time and spectral band of the insect attractant lamp are adjusted to generate real-time adjustment control parameters; S4: Based on the real-time adjustment of control parameters, according to the various mosquito activity time periods, considering the working energy consumption of the high-voltage power grid, adjusting the working voltage parameters of the high-voltage power grid, and generating power grid parameter optimization results; S5: Based on the optimization results of the power grid parameters, by analyzing the current changes corresponding to the high-voltage power grid killing mosquitoes, recording the types and numbers of mosquitoes killed, and generating mosquito trapping data records; S6: Use mosquito trapping data records to evaluate trapping efficiency, optimize the working parameters of insect trap lamps and high-voltage power grid, and generate trapping efficiency evaluation results.

[0038] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0039] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0040] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0041] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0042] Those skilled in the art will appreciate that the units 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 the present invention.

[0043] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0044] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0045] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0046] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0047] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0048] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A control system for a mosquito killer lamp, characterized in that: The system includes: The mosquito behavior analysis module collects temperature, humidity and light data in real time based on mosquito activity monitoring data. It analyzes the number of mosquito activities under various environmental conditions, evaluates the intensity and frequency of mosquito activities under various conditions, and generates activity pattern prediction results. The spectral efficiency analysis module analyzes the attractiveness of multiple spectral bands to mosquitoes based on the activity pattern prediction results, considers the energy consumption of the insect attractant lamps in multiple spectral bands, identifies the optimal spectral bands for attracting and killing multiple mosquitoes, and generates an insect attractant spectrum matching list; The insect attractant lamp parameter configuration module adjusts the working parameters of the insect attractant lamp, including the start and stop time and the spectral band selection, based on the insect attractant spectrum matching list and in combination with the real-time environmental monitoring data, and generates real-time adjustment control parameters; The voltage parameter adjustment module adjusts the voltage parameters of the high-voltage power grid in multiple time periods based on the real-time adjustment control parameters, according to the active time period information of various mosquitoes, and takes into account the working energy consumption of the power grid, and generates a power grid parameter optimization result; The automatic counting module monitors the current data of the high-voltage power grid in real time through the power grid parameter optimization results, counts the number of trapped mosquitoes by analyzing the current changes, analyzes the trapping efficiency and optimizes the working parameters of the insect trap lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

2. The control system for a mosquito killer lamp according to claim 1, characterized in that: The activity pattern prediction result includes the predicted number of mosquito activity record data, the predicted activity intensity change information, and real-time environmental monitoring information; the insect attractant spectrum matching list includes the spectral band attraction score, the optimal spectral band, and the spectral band working energy consumption data; the real-time adjustment control parameters include the start and stop time of the insect attractant lamp, the selected spectral band, and the working parameter adjustment value according to the environmental conditions; the power grid parameter optimization result includes the high-voltage power grid voltage value parameter, the power grid working time period, and the high-voltage power grid energy consumption data; the trapping efficiency evaluation result includes the number of mosquitoes trapped, the trapping efficiency change trend, and the working parameter adjustment record.

3. The control system for a mosquito killer lamp according to claim 2, characterized in that: The mosquito behavior analysis module includes: The environmental data collection submodule uses temperature and humidity sensors and light sensors to collect temperature, humidity and light data in real time based on mosquito activity monitoring data to generate an environmental monitoring data set; The activity number analysis submodule generates mosquito activity analysis results by analyzing the active number of mosquitoes under various environmental conditions based on the environmental monitoring data set, calculating the correlation between mosquito activity and various environmental conditions; The active time prediction submodule analyzes and predicts the active periods of mosquitoes under various environmental conditions based on the mosquito activity analysis results, and generates activity pattern prediction results.

4. The control system for a mosquito killer lamp according to claim 3, characterized in that: The specific formula for calculating the correlation between mosquito activity and various environmental conditions is: ； in, represents the correlation coefficient between mosquito activity and environmental conditions, Representative in the The environmental conditions at each time point, including temperature, humidity, and light, Representative in the The mosquito activity value at each time point, represents the average value of environmental conditions, represents the average mosquito activity level. represents the total number of data points, that is, the number of observed time points, An index representing a time point.

5. The control system for a mosquito killer lamp according to claim 4, characterized in that: The spectral efficiency analysis module includes: The working energy consumption analysis submodule collects the energy consumption data of the insect attractant lamp working in multiple spectral bands based on the activity mode prediction result, and generates an insect attractant lamp energy consumption data set; The attraction evaluation submodule is based on the energy consumption data set of the insect attractant lamp, and by identifying the influence of multiple spectral bands on the number of active mosquitoes, calculates the attraction of multiple spectral bands to multiple mosquitoes, and generates spectral attraction evaluation data; The spectral band identification submodule identifies the optimal spectral bands for trapping various mosquitoes based on the spectral attraction evaluation data and taking into account the working energy consumption, and generates an insect attractant spectrum matching list.

6. The control system for a mosquito killer lamp according to claim 5, characterized in that: The specific formula for calculating the attraction of multiple spectral bands to multiple mosquitoes is: ； in, Represents the attractiveness score of a specific spectral band to mosquitoes, Represents the number of active mosquitoes observed in the current spectral band, represents the maximum number of mosquitoes observed in all tested spectral bands, It represents the duration of mosquitoes' continuous activity in this band. represents the total observation time, Represents the frequency of mosquitoes flying in this band. represents the maximum flight frequency observed in all tested bands, Represents the average distance between mosquitoes and the light source in this band. Represents the maximum measurement distance of the observation area.

7. The control system for a mosquito killer lamp according to claim 6, characterized in that: The insect attractant lamp parameter configuration module includes: The environmental parameter analysis submodule predicts and identifies the activity time periods of various mosquitoes based on the insect attractant spectrum matching list and real-time environmental monitoring data, including temperature, humidity and light intensity, and generates real-time environmental analysis results; The working period configuration submodule identifies the working time period required for the insect attractant lamp based on the real-time environmental analysis result and the active periods of various mosquitoes, and generates the start and stop parameter configuration of the insect attractant lamp; The control parameter setting submodule is based on the start and stop parameter configuration of the insect attractant lamp, and according to the active mosquito species in the target period, adjusts the working spectrum band of the insect attractant lamp at the target time to generate real-time adjustment control parameters.

8. The control system for a mosquito killer lamp according to claim 7, characterized in that: The voltage parameter adjustment module comprises: The voltage demand analysis submodule analyzes the voltage intensity required to kill various mosquitoes based on the real-time adjustment control parameters, and generates voltage demand analysis data; The power grid parameter configuration submodule adjusts the voltage operating parameters of the high-voltage power grid in multiple time periods based on the voltage demand analysis data and the active time periods of various mosquitoes to generate an operating voltage parameter configuration; The power grid energy consumption recording submodule is based on the working voltage parameter configuration, monitors the working energy consumption of the high-voltage power grid in real time, records the energy consumption data, and generates power grid parameter optimization results.

9. The control system for a mosquito killer lamp according to claim 8, characterized in that: The automatic counting module comprises: The current change analysis submodule is based on the power grid parameter optimization result, and identifies the current characteristics corresponding to various mosquitoes by analyzing the current changes corresponding to the high-voltage power grid killing mosquitoes, and generates a current characteristic analysis result; The real-time current monitoring submodule monitors the current data of the high-voltage power grid in real time based on the current characteristic analysis result, identifies the current change and records the number of various mosquitoes killed, and generates current change monitoring data; The trapping efficiency optimization submodule uses the current change monitoring data to analyze the trapping efficiency of the mosquito killer lamp, and adjusts the working parameters of the mosquito killer lamp and the high-voltage power grid to generate a trapping efficiency evaluation result.

10. A control method for a mosquito killer lamp, based on the control system for a mosquito killer lamp according to any one of claims 1 to 9, characterized in that: The method comprises: Based on mosquito activity monitoring data, real-time data on environmental temperature, humidity and light intensity are collected. By analyzing the number of mosquito activities under various environmental conditions, the activity intensity and frequency of various mosquitoes are identified, and activity pattern prediction results are generated; According to the activity pattern prediction results, the attraction and working energy consumption of multiple spectral bands to mosquitoes are evaluated, the optimal spectral band of the insect attractant lamp is identified, and a list of insect attractant spectrum matching is generated; Using the insect attractant spectrum matching list and combining it with real-time environmental monitoring data, the start and stop time and spectral band of the insect attractant lamp are adjusted to generate real-time adjustment control parameters; According to the real-time adjustment control parameters, according to various mosquito activity time periods, considering the working energy consumption of the high-voltage power grid, adjusting the working voltage parameters of the high-voltage power grid, and generating power grid parameter optimization results; Based on the power grid parameter optimization result, by analyzing the current change corresponding to the high-voltage power grid killing mosquitoes, recording the types and numbers of mosquitoes killed, and generating mosquito trapping data records; The mosquito trapping data records are used to evaluate the trapping efficiency, and the working parameters of the insect trap lamp and the high-voltage power grid are optimized to generate a trapping efficiency evaluation result.

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