Intelligent traffic signal lamp monitoring system based on Internet of Things

Abstract

The invention discloses an intelligent traffic signal lamp monitoring system based on the Internet of Things, particularly relates to the field of photovoltaic power generation, and comprises a data acquisition time division module, a photovoltaic power generation data acquisition module, a photovoltaic power generation data analysis module, a signal lamp data acquisition module, a signal lamp data analysis module, a comprehensive analysis module and an early warning module. A clear time frame is provided for data analysis through the data acquisition time division module, the photovoltaic power generation data acquisition and data analysis module ensures accurate evaluation of the performance of a photovoltaic panel, and the signal lamp data acquisition and data analysis module provides real-time monitoring and diagnosis for the working state of a signal lamp. Through application of the comprehensive analysis module and the early warning module, comprehensive indexes are provided for performance evaluation and optimization of the whole intelligent traffic signal lamp system, potential problems can be found and early warned in time, stable operation of the system is guaranteed, the intelligent level of the traffic signal lamp is improved, and the reliability and efficiency of the system are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and more specifically, to an intelligent traffic signal light monitoring system based on the Internet of Things. Background Art

[0002] With the rapid development of urban transportation, traffic lights play a key role in ensuring road safety and smooth operation. In recent years, photovoltaic power generation technology has gradually been applied to traffic light systems due to its clean and renewable characteristics, in order to reduce dependence on traditional energy and improve energy efficiency. However, some current traffic light systems still have many problems in actual use.

[0003] On the one hand, these systems are not accurate enough in evaluating the performance of photovoltaic power generation, and cannot timely and accurately understand the changes in the working efficiency of photovoltaic panels in different time periods. This may lead to inefficiency of the photovoltaic power generation system and fail to fully play its due role. At the same time, the monitoring and diagnosis of the working status of traffic lights are not comprehensive enough, and it is difficult to quantify and evaluate the actual efficiency of traffic lights, so that possible problems with traffic lights cannot be discovered and solved in time, thus affecting the normal operation of traffic lights.

[0004] On the other hand, the existing system lacks comprehensive indicators in overall performance evaluation and optimization, and cannot effectively improve the performance of the system from a global perspective. In addition, when the system fails or an abnormal situation occurs, it cannot issue a warning signal in time to notify managers to deal with it, which may cause traffic chaos and even cause safety accidents. Therefore, there is an urgent need for a more intelligent and efficient traffic light monitoring system based on photovoltaic power generation to solve these problems and improve the reliability and stability of traffic lights. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent traffic signal light monitoring system based on the Internet of Things, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solution: an intelligent traffic signal light monitoring system based on the Internet of Things, comprising:

[0007] Data collection time division module: used to determine the data collection time of the target intelligent traffic light as the target time zone, divide the target time zone into various sub-time zones by equal time division, and mark them as 1, 2...n in sequence;

[0008] Photovoltaic power generation data acquisition module: used to collect basic performance data of photovoltaic panels, internal electronic data of photovoltaic panels and light absorption data of photovoltaic panels in each sub-time zone, and transmit the collected data to the photovoltaic power generation data analysis module;

[0009] Photovoltaic power generation data analysis module: including photovoltaic panel basic performance data analysis unit, photovoltaic panel internal electronic data analysis unit and photovoltaic panel light absorption data analysis unit, used for analyzing the data transmitted by the photovoltaic power generation data acquisition module and transmitting the analysis results to the comprehensive analysis module;

[0010] Traffic light data collection module: used to collect traffic light identification data, traffic light special situation data and traffic light intelligent control data in each sub-time zone, and transmit the collected data to the traffic light data analysis module;

[0011] Traffic light data analysis module: including a traffic light recognition data analysis unit, a traffic light special situation data analysis unit and a traffic light intelligent control data analysis unit, which are used to analyze the data transmitted by the traffic light data acquisition module and transmit the analysis results to the comprehensive analysis module;

[0012] Comprehensive analysis model: used to establish a comprehensive analysis model, import the data transmitted by the traffic light data analysis module and the photovoltaic power generation data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of the target time area, and transmit it to the early warning module;

[0013] Early warning module: used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of the target time area according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

[0014] Preferably, the basic performance data of the photovoltaic panel include the dust particle density on the surface of the photovoltaic panel, the tilt angle of the photovoltaic panel, the thermal expansion coefficient of the photovoltaic panel material, and the electron migration rate inside the photovoltaic panel, which are marked as Fd, Ft, Fh, and Fm, respectively; the internal electronic data of the photovoltaic panel include the quantum efficiency, non-radiative recombination rate, photogenerated carrier lifetime, and instantaneous power fluctuation amplitude of photovoltaic power generation, which are marked as Eq, Ev, El, and Ef, respectively; the light absorption data of the photovoltaic panel include the light absorption ratio of the photovoltaic panel at the standard wavelength, the parasitic capacitance value of the photovoltaic panel, the leakage current size, and the response time of the maximum power point tracking, which are marked as La, Lp, Lc, and Lt, respectively.

[0015] Preferably, the photovoltaic panel basic performance data analysis unit is used to establish a photovoltaic panel basic performance data analysis model, import the photovoltaic panel basic performance data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel basic performance data analysis model, and calculate the photovoltaic panel basic characteristic value of each sub-time zone, which is specifically expressed as: PFi represents the basic characteristic value of the photovoltaic panel in the i-th sub-time zone, Fd i represents the dust particle density on the photovoltaic panel surface in the i-th sub-time zone, Ft i represents the photovoltaic panel tilt angle in the i-th sub-time zone, Fh i represents the thermal expansion coefficient of the photovoltaic panel material in the i-th sub-time period, Fm i Represents the electron migration rate inside the photovoltaic panel in the i-th sub-time region.

[0016] Preferably, the photovoltaic panel internal electronic data analysis unit is used to establish a photovoltaic panel internal electronic data analysis model, import the photovoltaic panel internal electronic data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel internal electronic data analysis model, and calculate the photovoltaic electronic efficiency evaluation value of each sub-time zone, which is specifically expressed as: PE i represents the photovoltaic electronic efficiency evaluation value of the i-th sub-time zone, Eq i represents the quantum efficiency of the photovoltaic panel in the i-th sub-time zone, Ev i represents the non-radiative recombination rate in the ith sub-time region, El i represents the lifetime of photogenerated carriers in the ith sub-time region, Ef i represents the instantaneous power fluctuation amplitude of photovoltaic power generation in the i-th sub-time zone, Eq max Indicates the maximum quantum efficiency of the photovoltaic panel in the target time period, Ef max Indicates the maximum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone, Ef min Indicates the minimum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone.

[0017] Preferably, the photovoltaic panel light absorption data analysis unit is used to establish a photovoltaic panel light absorption data analysis model, import the photovoltaic panel light absorption data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel light absorption data analysis model, and calculate the photovoltaic panel light absorption efficiency value of each sub-time zone, which is specifically expressed as: PL i represents the light absorption efficiency value of the photovoltaic panel in the i-th sub-time zone, La i Indicates the light absorption ratio of the photovoltaic panel at the standard wavelength in the i-th sub-time zone, Lp i represents the parasitic capacitance value of the photovoltaic panel in the i-th sub-time zone, Lc i Indicates the leakage current size of the ith sub-time zone, Lt i represents the response time of the maximum power point tracking in the i-th time sub-region.

[0018] Preferably, the photovoltaic power generation data analysis module calculates the photovoltaic power generation comprehensive efficiency value of the i-th sub-time region through the photovoltaic panel basic characteristic value of the i-th sub-time region, the photovoltaic electronic efficiency evaluation value of the i-th sub-time region, and the photovoltaic panel light absorption efficiency value of the i-th sub-time region, which is specifically expressed as: κ i =PF i ×PE i ×PL i , κ i Represents the comprehensive efficiency value of photovoltaic power generation in the i-th sub-time zone.

[0019] Preferably, the signal light recognition data includes the recognition accuracy of the signal light for different types of vehicles, the visibility distance of the signal light in foggy weather, the length of time the signal light is blocked by reflections from surrounding buildings, and the driver's reaction time to the color change of the signal light, which are marked as Ra, Rv, Ro, and Rt, respectively; the signal light special situation data includes the synchronization error between the intelligent traffic light and the adjacent signal light, the number of times the signal light is blocked by birds in different time periods, the signal light's success rate in receiving special vehicle signals, and the number of effective warnings for pedestrians running red lights, which are marked as Se, Sb, Sc, and Sr, respectively; the signal light intelligent control data includes the memory occupancy rate of the signal light intelligent control system, the download speed of the signal light program update, the interaction frequency of the signal light and the intelligent navigation system, and the temperature change of the signal light control chip, which are marked as Cm, Cv, Cf, and Ce, respectively.

[0020] Preferably, the signal light recognition data analysis unit is used to establish a signal light recognition data analysis model, import the signal light recognition data transmitted by the signal light data acquisition module into the signal light recognition data analysis model, and calculate the signal light recognition efficiency evaluation value of each sub-time zone, which is specifically expressed as: DR i represents the traffic light recognition efficiency evaluation value of the i-th sub-time zone, Ra i Rv represents the recognition accuracy of the traffic lights in the ith sub-time zone for different vehicle models, i represents the visibility distance of the traffic light in foggy weather in the i-th sub-time zone, Ro i Rt represents the duration of time that the traffic light in the i-th sub-time zone is blocked by the reflection of surrounding buildings. i Rv represents the driver's reaction time to the change of the signal light color in the i-th sub-time zone, max Indicates the maximum visibility distance of traffic lights in foggy weather in the target time area.

[0021] Preferably, the signal light special situation data analysis unit is used to establish a signal light special situation data analysis model, import the signal light special situation data transmitted by the signal light data acquisition module into the signal light special situation data analysis model, and calculate the signal light special scene evaluation value of each sub-time zone, which is specifically expressed as: DS i represents the special scene evaluation value of the traffic light in the i-th sub-time zone, Se i represents the synchronization error between the intelligent traffic light in the ith sub-time zone and the adjacent traffic lights, Sb i represents the number of times the traffic light is blocked by birds in different time periods of the i-th sub-time zone, Sc i Sr represents the success rate of receiving special vehicle signals by the traffic lights in the i-th sub-time zone, i Indicates the number of effective warnings for pedestrian red light running in the i-th sub-time zone.

[0022] Preferably, the traffic light intelligent control data analysis unit is used to establish a traffic light intelligent control data analysis model, import the traffic light intelligent control data transmitted by the traffic light data acquisition module into the traffic light intelligent control data analysis model, and calculate the traffic light intelligent control efficiency value of each sub-time zone, which is specifically expressed as: RC i represents the intelligent control efficiency value of the traffic light in the ith sub-time zone, Cm i represents the memory usage of the traffic light intelligent control system in the i-th sub-time zone, Cv i represents the download speed of the signal light program update in the i-th sub-time zone, Cf i represents the interaction frequency between the traffic light and the intelligent navigation system in the ith sub-time zone, Ce i represents the temperature change of the signal light control chip in the i-th sub-time zone, Cv max Indicates the maximum download speed of the semaphore program updates for the target time zone.

[0023] Preferably, the traffic light data analysis module calculates the comprehensive traffic light efficiency value of the ith sub-time zone through the traffic light recognition efficiency evaluation value of the ith sub-time zone, the traffic light special scene evaluation value of the ith sub-time zone, and the traffic light intelligent control efficiency value of the ith sub-time zone, which is specifically expressed as: τ i =DR i +DS i +DC i , τ i Represents the comprehensive performance value of the traffic light in the i-th sub-time zone.

[0024] Preferably, the comprehensive analysis model is specifically expressed as: η represents the comprehensive optimization index of the target time zone, κ i represents the comprehensive efficiency value of photovoltaic power generation in the i-th sub-time zone, τ i represents the comprehensive efficiency value of the traffic light in the i-th sub-time zone, β1 represents the weight of the comprehensive efficiency value of photovoltaic power generation, β2 represents the weight of the comprehensive efficiency value of the traffic light, and λ represents other influencing factors of the comprehensive optimization index.

[0025] Preferably, the preset value of the comprehensive optimization index is marked as η Def , when η Def <η, it means that the comprehensive optimization index of the target time zone is greater than the preset value of the comprehensive optimization index, indicating that the quality of the target traffic light is good. Def >η, it means that the comprehensive optimization index of the target time zone is greater than the preset value of the comprehensive optimization index, indicating that the quality of the target traffic light is poor, and a warning signal is sent to the management terminal.

[0026] Technical effects and advantages of the present invention:

[0027] The present invention divides the target time area into various sub-time areas through the data acquisition time division module, and marks them in sequence, which is helpful for fine management of data in different time periods and provides a clear time frame for subsequent data analysis; the photovoltaic panel basic performance data, internal electronic data and light absorption data collected by the photovoltaic power generation data acquisition module provide a comprehensive data source for subsequent photovoltaic power generation efficiency analysis, ensuring accurate evaluation of photovoltaic power generation performance; the photovoltaic power generation data analysis module calculates the photovoltaic power generation comprehensive efficiency value of each sub-time area through photovoltaic panel basic performance data analysis, internal electronic data analysis and light absorption data analysis units, which is helpful for identifying the working efficiency of photovoltaic panels in different time periods and provides a scientific basis for optimizing photovoltaic power generation systems; the signal light recognition data, special situation data and intelligent control data collected by the signal light data acquisition module provide signal light performance evaluation. It provides comprehensive and detailed data support, which is helpful for real-time monitoring and diagnosis of the working status of traffic lights; through the analysis of traffic light data by the traffic light data analysis module, the comprehensive efficiency value of traffic lights in each sub-time zone is calculated, which provides a quantitative evaluation method for the working efficiency of traffic lights, which is helpful for timely discovery of possible problems with traffic lights and maintenance; through the comprehensive analysis module, the data transmitted by the photovoltaic power generation data analysis module and the traffic light data analysis module are imported into the comprehensive analysis model, and the comprehensive optimization index of the target time zone is calculated, which provides a comprehensive indicator for the performance evaluation and optimization of the entire intelligent traffic light system, and helps to improve the overall performance of the system; through the early warning module, a preset value of the comprehensive optimization index is established, and judgment is made based on the actual comprehensive optimization index, and an early warning signal is issued, which is helpful for timely discovery of possible problems in the intelligent traffic light system, and notifies management personnel to deal with them, so as to ensure the stable operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] refer to Figure 1 An intelligent traffic light monitoring system based on the Internet of Things is shown, including a data acquisition time division module, a photovoltaic power generation data acquisition module, a photovoltaic power generation data analysis module, a traffic light data acquisition module, a traffic light data analysis module, a comprehensive analysis module, and an early warning module.

[0031] The data collection time division module is used to determine the data collection time of the target intelligent traffic light as a target time zone, divide the target time zone into various sub-time zones by equal time division, and mark them as 1, 2...n in sequence.

[0032] The photovoltaic power generation data acquisition module is used to collect basic performance data of photovoltaic panels, internal electronic data of photovoltaic panels and light absorption data of photovoltaic panels in each sub-time zone, and transmit the collected data to the photovoltaic power generation data analysis module.

[0033] The basic performance data of the photovoltaic panel include the dust particle density on the surface of the photovoltaic panel, the tilt angle of the photovoltaic panel, the thermal expansion coefficient of the photovoltaic panel material, and the electron migration rate inside the photovoltaic panel, which are marked as Fd, Ft, Fh, and Fm respectively. The internal electronic data of the photovoltaic panel include the quantum efficiency, non-radiative recombination rate, photogenerated carrier lifetime, and instantaneous power fluctuation amplitude of photovoltaic power generation, which are marked as Eq, Ev, El, and Ef respectively. The light absorption data of the photovoltaic panel include the light absorption ratio of the photovoltaic panel at the standard wavelength, the parasitic capacitance value of the photovoltaic panel, the leakage current size, and the response time of the maximum power point tracking, which are marked as La, Lp, Lc, and Lt respectively.

[0034] The photovoltaic power generation data analysis module includes a photovoltaic panel basic performance data analysis unit, a photovoltaic panel internal electronic data analysis unit and a photovoltaic panel light absorption data analysis unit, which are used to analyze the data transmitted by the photovoltaic power generation data acquisition module and transmit the analysis results to the comprehensive analysis module.

[0035] The photovoltaic panel basic performance data analysis unit is used to establish a photovoltaic panel basic performance data analysis model, import the photovoltaic panel basic performance data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel basic performance data analysis model, and calculate the photovoltaic panel basic characteristic value of each sub-time zone, which is specifically expressed as: PF i represents the basic characteristic value of the photovoltaic panel in the i-th sub-time zone, Fd i represents the dust particle density on the photovoltaic panel surface in the i-th sub-time zone, Ft i represents the photovoltaic panel tilt angle in the i-th sub-time zone, Fh i represents the thermal expansion coefficient of the photovoltaic panel material in the i-th sub-time period, Fm i Represents the electron migration rate inside the photovoltaic panel in the i-th sub-time region.

[0036] The photovoltaic panel internal electronic data analysis unit is used to establish a photovoltaic panel internal electronic data analysis model, import the photovoltaic panel internal electronic data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel internal electronic data analysis model, and calculate the photovoltaic electronic efficiency evaluation value of each sub-time zone, which is specifically expressed as: PE i represents the photovoltaic electronic efficiency evaluation value of the i-th sub-time zone, Eq i represents the quantum efficiency of the photovoltaic panel in the i-th sub-time zone, Ev i represents the non-radiative recombination rate in the ith sub-time region, El i represents the lifetime of photogenerated carriers in the ith sub-time region, Ef i represents the instantaneous power fluctuation amplitude of photovoltaic power generation in the i-th sub-time zone, Eq max Indicates the maximum quantum efficiency of the photovoltaic panel in the target time period, Ef max Indicates the maximum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone, Ef min Indicates the minimum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone.

[0037] The photovoltaic panel light absorption data analysis unit is used to establish a photovoltaic panel light absorption data analysis model, import the photovoltaic panel light absorption data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel light absorption data analysis model, and calculate the photovoltaic panel light absorption efficiency value of each sub-time zone, which is specifically expressed as: PL i represents the light absorption efficiency value of the photovoltaic panel in the i-th sub-time zone, La i Indicates the light absorption ratio of the photovoltaic panel at the standard wavelength in the i-th sub-time zone, Lp i represents the parasitic capacitance value of the photovoltaic panel in the i-th sub-time zone, Lc i Indicates the leakage current size of the ith sub-time zone, Lt i represents the response time of the maximum power point tracking in the i-th time sub-region.

[0038] The photovoltaic power generation data analysis module calculates the photovoltaic power generation comprehensive efficiency value of the i-th sub-time region through the photovoltaic panel basic characteristic value of the i-th sub-time region, the photovoltaic electronic efficiency evaluation value of the i-th sub-time region, and the photovoltaic panel light absorption efficiency value of the i-th sub-time region, which is specifically expressed as: κ i =PF i ×PE i ×PL i , κ i Represents the comprehensive efficiency value of photovoltaic power generation in the i-th sub-time zone.

[0039] The signal light data acquisition module is used to collect signal light identification data, signal light special situation data and signal light intelligent control data in each sub-time zone, and transmit the collected data to the signal light data analysis module.

[0040] The signal light recognition data includes the recognition accuracy of the signal light for different types of vehicles, the visibility distance of the signal light in foggy weather, the length of time the signal light is blocked by reflections from surrounding buildings, and the driver's reaction time to the color change of the signal light, which are marked as Ra, Rv, Ro, and Rt respectively. The signal light special situation data includes the synchronization error between the intelligent traffic light and the adjacent signal light, the number of times the signal light is blocked by birds in different time periods, the signal light's success rate in receiving special vehicle signals, and the number of effective warnings for pedestrians running red lights, which are marked as Se, Sb, Sc, and Sr respectively. The signal light intelligent control data includes the memory occupancy rate of the signal light intelligent control system, the download speed of the signal light program update, the interaction frequency of the signal light and the intelligent navigation system, and the temperature change of the signal light control chip, which are marked as Cm, Cv, Cf, and Ce respectively.

[0041] What needs to be specifically explained in this embodiment is that the special vehicle signals in the traffic light's success rate of receiving special vehicle signals are specifically priority signals sent by police cars, ambulances and fire trucks, indicating their identity as special vehicles so that the traffic light can give them priority right of way. The traffic light's success rate of receiving special vehicle signals is collected by installing a wireless communication device on the intelligent traffic light.

[0042] The signal light data analysis module includes a signal light recognition data analysis unit, a signal light special situation data analysis unit and a signal light intelligent control data analysis unit, which are used to analyze the data transmitted by the signal light data acquisition module and transmit the analysis results to the comprehensive analysis module.

[0043] The signal light recognition data analysis unit is used to establish a signal light recognition data analysis model, import the signal light recognition data transmitted by the signal light data acquisition module into the signal light recognition data analysis model, and calculate the signal light recognition efficiency evaluation value of each sub-time zone, which is specifically expressed as: DR i represents the traffic light recognition efficiency evaluation value of the i-th sub-time zone, Ra i Rv represents the recognition accuracy of the traffic lights in the ith sub-time zone for different vehicle models, i represents the visibility distance of the traffic light in foggy weather in the i-th sub-time zone, Ro i Rt represents the duration of time that the traffic light in the i-th sub-time zone is blocked by the reflection of surrounding buildings. i Rv represents the driver's reaction time to the change of the signal light color in the i-th sub-time zone, maxIndicates the maximum visibility distance of traffic lights in foggy weather in the target time area.

[0044] The signal light special situation data analysis unit is used to establish a signal light special situation data analysis model, import the signal light special situation data transmitted by the signal light data acquisition module into the signal light special situation data analysis model, and calculate the signal light special scene evaluation value of each sub-time zone, which is specifically expressed as: DS i represents the special scene evaluation value of the traffic light in the i-th sub-time zone, Se i represents the synchronization error between the intelligent traffic light in the ith sub-time zone and the adjacent traffic lights, Sb i represents the number of times the traffic light is blocked by birds in different time periods of the i-th sub-time zone, Sc i Sr represents the success rate of receiving special vehicle signals by the traffic lights in the i-th sub-time zone, i Indicates the number of effective warnings for pedestrians running red lights in the i-th sub-time zone.

[0045] The signal light intelligent control data analysis unit is used to establish a signal light intelligent control data analysis model, import the signal light intelligent control data transmitted by the signal light data acquisition module into the signal light intelligent control data analysis model, and calculate the signal light intelligent control efficiency value of each sub-time zone, which is specifically expressed as: RC i represents the intelligent control efficiency value of the traffic light in the ith sub-time zone, Cm i represents the memory usage of the traffic light intelligent control system in the i-th sub-time zone, Cv i represents the download speed of the signal light program update in the i-th sub-time zone, Cf i represents the interaction frequency between the traffic light and the intelligent navigation system in the ith sub-time zone, Ce i represents the temperature change of the signal light control chip in the i-th sub-time zone, Cv max Indicates the maximum download speed of the semaphore program updates for the target time zone.

[0046] The traffic light data analysis module calculates the comprehensive traffic light efficiency value of the ith sub-time zone through the traffic light recognition efficiency evaluation value of the ith sub-time zone, the traffic light special scene evaluation value of the ith sub-time zone, and the traffic light intelligent control efficiency value of the ith sub-time zone, which is specifically expressed as: i =DR i +DS i +DC i , τ i Represents the comprehensive performance value of the traffic light in the i-th sub-time zone.

[0047] The comprehensive analysis model is used to establish a comprehensive analysis model, import the data transmitted by the traffic light data analysis module and the photovoltaic power generation data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of the target time area, and transmit it to the early warning module.

[0048] The comprehensive analysis model is specifically expressed as: η represents the comprehensive optimization index of the target time zone, κ i represents the comprehensive efficiency value of photovoltaic power generation in the i-th sub-time zone, τ i represents the comprehensive efficiency value of the traffic light in the i-th sub-time zone, β1 represents the weight of the comprehensive efficiency value of photovoltaic power generation, β2 represents the weight of the comprehensive efficiency value of the traffic light, and λ represents other influencing factors of the comprehensive optimization index.

[0049] The early warning module is used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of the target time zone according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

[0050] The preset value of the comprehensive optimization index is marked as η Def , when η Def <η, it means that the comprehensive optimization index of the target time zone is greater than the preset value of the comprehensive optimization index, indicating that the quality of the target traffic light is good. Def >η, it means that the comprehensive optimization index of the target time zone is greater than the preset value of the comprehensive optimization index, indicating that the quality of the target traffic light is poor, and a warning signal is sent to the management terminal.

[0051] The present invention divides the target time area into various sub-time areas through the data acquisition time division module, and marks them in sequence, which is helpful for fine management of data in different time periods and provides a clear time frame for subsequent data analysis; the photovoltaic panel basic performance data, internal electronic data and light absorption data collected by the photovoltaic power generation data acquisition module provide a comprehensive data source for subsequent photovoltaic power generation efficiency analysis, ensuring accurate evaluation of photovoltaic power generation performance; the photovoltaic power generation data analysis module calculates the photovoltaic power generation comprehensive efficiency value of each sub-time area through photovoltaic panel basic performance data analysis, internal electronic data analysis and light absorption data analysis units, which is helpful for identifying the working efficiency of photovoltaic panels in different time periods and provides a scientific basis for optimizing photovoltaic power generation systems; the signal light recognition data, special situation data and intelligent control data collected by the signal light data acquisition module provide signal light performance evaluation. It provides comprehensive and detailed data support, which is helpful for real-time monitoring and diagnosis of the working status of traffic lights; through the analysis of traffic light data by the traffic light data analysis module, the comprehensive efficiency value of traffic lights in each sub-time zone is calculated, which provides a quantitative evaluation method for the working efficiency of traffic lights, which is helpful for timely discovery of possible problems with traffic lights and maintenance; through the comprehensive analysis module, the data transmitted by the photovoltaic power generation data analysis module and the traffic light data analysis module are imported into the comprehensive analysis model, and the comprehensive optimization index of the target time zone is calculated, which provides a comprehensive indicator for the performance evaluation and optimization of the entire intelligent traffic light system, and helps to improve the overall performance of the system; through the early warning module, a preset value of the comprehensive optimization index is established, and judgment is made based on the actual comprehensive optimization index, and an early warning signal is issued, which is helpful for timely discovery of possible problems in the intelligent traffic light system, and notifies management personnel to deal with them, so as to ensure the stable operation of the system.

[0052] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0053] 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. An intelligent traffic signal light monitoring system based on the Internet of Things, characterized in that: include: Data collection time division module: used to determine the data collection time of the target intelligent traffic light as the target time zone, divide the target time zone into various sub-time zones by equal time division, and mark them as 1, 2...n in sequence; Photovoltaic power generation data acquisition module: used to collect basic performance data of photovoltaic panels, internal electronic data of photovoltaic panels and light absorption data of photovoltaic panels in each sub-time zone, and transmit the collected data to the photovoltaic power generation data analysis module; Photovoltaic power generation data analysis module: including photovoltaic panel basic performance data analysis unit, photovoltaic panel internal electronic data analysis unit and photovoltaic panel light absorption data analysis unit, used for analyzing the data transmitted by the photovoltaic power generation data acquisition module and transmitting the analysis results to the comprehensive analysis module; Traffic light data collection module: used to collect traffic light identification data, traffic light special situation data and traffic light intelligent control data in each sub-time zone, and transmit the collected data to the traffic light data analysis module; Traffic light data analysis module: including a traffic light recognition data analysis unit, a traffic light special situation data analysis unit and a traffic light intelligent control data analysis unit, which are used to analyze the data transmitted by the traffic light data acquisition module and transmit the analysis results to the comprehensive analysis module; Comprehensive analysis model: used to establish a comprehensive analysis model, import the data transmitted by the traffic light data analysis module and the photovoltaic power generation data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of the target time area, and transmit it to the early warning module; Early warning module: used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of the target time area according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

2. According to claim 1, the intelligent traffic signal light monitoring system based on the Internet of Things is characterized by: The basic performance data of the photovoltaic panel include the dust particle density on the surface of the photovoltaic panel, the tilt angle of the photovoltaic panel, the thermal expansion coefficient of the photovoltaic panel material, and the electron migration rate inside the photovoltaic panel, which are marked as Fd, Ft, Fh, and Fm respectively. The internal electronic data of the photovoltaic panel include the quantum efficiency, non-radiative recombination rate, photogenerated carrier lifetime, and instantaneous power fluctuation amplitude of photovoltaic power generation, which are marked as Eq, Ev, El, and Ef respectively. The light absorption data of the photovoltaic panel include the light absorption ratio of the photovoltaic panel at the standard wavelength, the parasitic capacitance value of the photovoltaic panel, the leakage current size, and the response time of the maximum power point tracking, which are marked as La, Lp, Lc, and Lt respectively.

3. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The photovoltaic panel basic performance data analysis unit is used to establish a photovoltaic panel basic performance data analysis model, import the photovoltaic panel basic performance data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel basic performance data analysis model, and calculate the photovoltaic panel basic characteristic value of each sub-time zone, which is specifically expressed as: PF i represents the basic characteristic value of the photovoltaic panel in the i-th sub-time zone, Fd i represents the dust particle density on the photovoltaic panel surface in the i-th sub-time zone, Ft i represents the photovoltaic panel tilt angle in the i-th sub-time zone, Fh i represents the thermal expansion coefficient of the photovoltaic panel material in the i-th sub-time period, Fm i Represents the electron migration rate inside the photovoltaic panel in the i-th sub-time region.

4. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The photovoltaic panel internal electronic data analysis unit is used to establish a photovoltaic panel internal electronic data analysis model, import the photovoltaic panel internal electronic data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel internal electronic data analysis model, and calculate the photovoltaic electronic efficiency evaluation value of each sub-time zone, which is specifically expressed as: PE i represents the photovoltaic electronic efficiency evaluation value of the i-th sub-time zone, Eq i represents the quantum efficiency of the photovoltaic panel in the i-th sub-time zone, Ev i represents the non-radiative recombination rate in the ith sub-time region, El i represents the lifetime of photogenerated carriers in the ith sub-time region, Ef i represents the instantaneous power fluctuation amplitude of photovoltaic power generation in the i-th sub-time zone, Eq max Indicates the maximum quantum efficiency of the photovoltaic panel in the target time period, Ef max Indicates the maximum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone, Ef min Indicates the minimum instantaneous power fluctuation amplitude of photovoltaic power generation in the target time zone.

5. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The photovoltaic panel light absorption data analysis unit is used to establish a photovoltaic panel light absorption data analysis model, import the photovoltaic panel light absorption data transmitted by the photovoltaic power generation data acquisition module into the photovoltaic panel light absorption data analysis model, and calculate the photovoltaic panel light absorption efficiency value of each sub-time zone, which is specifically expressed as: PL i represents the light absorption efficiency value of the photovoltaic panel in the i-th sub-time zone, La i Indicates the light absorption ratio of the photovoltaic panel at the standard wavelength in the i-th sub-time zone, Lp i represents the parasitic capacitance value of the photovoltaic panel in the i-th sub-time zone, Lc i Indicates the leakage current size of the ith sub-time zone, Lt i represents the response time of the maximum power point tracking in the i-th time sub-region.

6. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The signal light recognition data includes the recognition accuracy of the signal light for different types of vehicles, the visibility distance of the signal light in foggy weather, the length of time the signal light is blocked by reflections from surrounding buildings, and the driver's reaction time to the color change of the signal light, which are marked as Ra, Rv, Ro, and Rt respectively. The signal light special situation data includes the synchronization error between the intelligent traffic light and the adjacent signal light, the number of times the signal light is blocked by birds in different time periods, the signal light's success rate in receiving special vehicle signals, and the number of effective warnings for pedestrians running red lights, which are marked as Se, Sb, Sc, and Sr respectively. The signal light intelligent control data includes the memory occupancy rate of the signal light intelligent control system, the download speed of the signal light program update, the interaction frequency of the signal light and the intelligent navigation system, and the temperature change of the signal light control chip, which are marked as Cm, Cv, Cf, and Ce respectively.

7. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The signal light recognition data analysis unit is used to establish a signal light recognition data analysis model, import the signal light recognition data transmitted by the signal light data acquisition module into the signal light recognition data analysis model, and calculate the signal light recognition efficiency evaluation value of each sub-time zone, which is specifically expressed as: DR i represents the traffic light recognition efficiency evaluation value of the i-th sub-time zone, Ra i Rv represents the recognition accuracy of the traffic lights in the ith sub-time zone for different vehicle models, i represents the visibility distance of the traffic light in foggy weather in the i-th sub-time zone, Ro i Rt represents the duration of time that the traffic light in the ith sub-time zone is blocked by the reflection of surrounding buildings. i Rv represents the driver's reaction time to the change of the signal light color in the i-th sub-time zone, max Indicates the maximum visibility distance of traffic lights in foggy weather in the target time area.

8. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The signal light special situation data analysis unit is used to establish a signal light special situation data analysis model, import the signal light special situation data transmitted by the signal light data acquisition module into the signal light special situation data analysis model, and calculate the signal light special scene evaluation value of each sub-time zone, which is specifically expressed as: DS i represents the special scene evaluation value of the traffic light in the i-th sub-time zone, Se i represents the synchronization error between the intelligent traffic light in the ith sub-time zone and the adjacent traffic lights, Sb i represents the number of times the traffic light is blocked by birds in different time periods of the i-th sub-time zone, Sc i Sr represents the success rate of receiving special vehicle signals by the traffic lights in the i-th sub-time zone, i Indicates the number of effective warnings for pedestrians running red lights in the i-th sub-time zone.

9. The intelligent traffic signal light monitoring system based on the Internet of Things according to claim 1 is characterized in that: The comprehensive analysis model is specifically expressed as: η represents the comprehensive optimization index of the target time zone, κ i represents the comprehensive efficiency value of photovoltaic power generation in the i-th sub-time zone, τ i represents the comprehensive efficiency value of the traffic light in the i-th sub-time zone, β1 represents the weight of the comprehensive efficiency value of photovoltaic power generation, β2 represents the weight of the comprehensive efficiency value of the traffic light, and λ represents other influencing factors of the comprehensive optimization index.

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