Intelligent lighting method and device for road, storage medium and electronic equipment

Abstract

The invention provides an intelligent lighting method and device for a road, a storage medium and electronic equipment, and the method comprises the steps: obtaining first environment influence data which at least comprises solar altitude data and current illumination data at a current moment; obtaining second environment influence data, wherein the second environment influence data at least comprises a weather condition influence factor and vehicle flow data obtained through model prediction; according to the first environment influence data and the second environment influence data, determining whether the lighting device is turned on or not; and under the condition that the lighting device is turned on, determining the current brightness of the lighting device at least according to the first environment influence data and the second environment influence data. According to the method, by integrating devices such as a GPS, an illumination sensor, a weather station and a vehicle detector, environment illumination, weather conditions and traffic flow data are collected and analyzed in real time, the switching time and brightness of street lamps are dynamically adjusted, and therefore energy conservation and emission reduction are achieved, and road safety is improved.

Description

Technical Field

[0001] The present application relates to the field of smart city infrastructure, and more specifically, to a smart road lighting method, a smart road lighting device, a computer-readable storage medium, and an electronic device. Background Art

[0002] With the acceleration of urbanization, urban lighting has become an important component of energy consumption. Traditional road lighting systems usually use a fixed schedule to control the switching of lights. This practice not only wastes energy, but also cannot adapt to complex external environmental changes, such as seasonal changes in day length, differences in pedestrian and vehicle density in different time periods, etc. In recent years, with the development of Internet of Things (IoT) technology, intelligent lighting systems that can automatically adjust according to the external environment have emerged. However, most existing systems only consider a single factor (such as the light intensity detected by a photoresistor), and fail to make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effects or inefficient energy utilization. Summary of the invention

[0003] The main purpose of the present application is to provide an intelligent road lighting method, an intelligent road lighting device, a computer-readable storage medium and an electronic device, so as to at least solve the problem that the lighting system in the prior art only considers a single factor and does not fully utilize multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy utilization efficiency.

[0004] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a smart road lighting method is provided, including: obtaining first environmental impact data, the first environmental impact data at least including solar altitude angle data and current lighting data at the current moment; obtaining second environmental impact data, the second environmental impact data at least including weather condition impact factors and vehicle flow data obtained according to model prediction; determining whether a lighting device is turned on according to the first environmental impact data and the second environmental impact data; when the lighting device is turned on, determining the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data.

[0005] Optionally, the current lighting data includes current lighting intensity, and determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data includes: determining a comprehensive impact factor based on at least the current lighting intensity and the weather condition impact factor; determining that the lighting device is turned on when the solar altitude angle data is less than or equal to a first altitude threshold and the comprehensive impact factor is greater than or equal to a first numerical value; determining that the lighting device is turned off when the solar altitude angle data is greater than a second altitude threshold and / or the comprehensive impact factor is less than a second numerical value, the first altitude threshold is less than the second altitude threshold, and the first numerical value is greater than the second numerical value.

[0006] Optionally, determining a comprehensive influencing factor based at least on the current light intensity and the weather condition influencing factor includes: obtaining a lighting influencing factor formula Among them, I f is the current illumination impact factor, I current is the current light intensity, I min is the preset minimum light intensity threshold; according to the lighting influence factor formula, the current light intensity and the minimum light intensity threshold, the current illumination influence factor is determined; and the comprehensive influence calculation formula C=W·I is obtained. f , where C is the comprehensive influencing factor and W is the weather condition influencing factor; the comprehensive influencing factor is determined according to the comprehensive influencing calculation formula, the weather condition influencing factor and the current illumination influencing factor.

[0007] Optionally, the current illumination data includes current illumination intensity, the vehicle flow data includes predicted current traffic flow, and determining the current brightness of the lighting device based at least on the first environmental impact data and the second environmental impact data includes: obtaining a brightness adjustment formula Wherein, L is the current brightness of the lighting device, L max is the maximum brightness of the lighting device, I current is the current light intensity, I min is the preset minimum light intensity threshold, F is the predicted current traffic flow, and F max is the maximum traffic flow of the road section where the lighting device is located at the target time in the historical data, W is the weather condition influencing factor, the target time is the time of the day in the historical data that is the same as the current time, α, β and γ are the first weight coefficient, the second weight coefficient and the third weight coefficient respectively, α+β+γ=1; the current brightness of the lighting device is determined according to the brightness adjustment formula.

[0008] Optionally, obtaining the first environmental impact data includes: calculating the solar declination according to the formula Determine the solar declination, where δ is the solar declination and n is the number of days in the year for the current day; according to the local hour angle calculation formula Determine the local hour angle, wherein H is the local hour angle, t is the local time, λ is the longitude of the lighting device, and e is the time difference correction value; determine the solar altitude angle according to the solar altitude angle calculation formula h=arcsin(sinδsinφ+cosδcosφcosH), wherein h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the lighting device, and H is the local hour angle; determine the first environmental impact data at least based on the solar altitude angle.

[0009] Optionally, obtaining the second environmental impact data includes: constructing a weather condition model and a traffic flow model; inputting the first historical data into the weather condition model, and predicting the weather condition impact factor, wherein the first historical data includes: the environmental weather at a historical moment and the historical weather condition impact factor corresponding to the environmental weather at the historical moment, obtained during a first historical time period; inputting the second historical data into the traffic flow model, and predicting the vehicle flow data, wherein the second historical data includes: the historical moment and the historical vehicle flow data corresponding to the historical moment, obtained during a second historical time period; determining the second environmental impact data based on the weather condition impact factor and the vehicle flow data.

[0010] Optionally, after determining the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data, the method further includes: determining the daily opening time of the lighting device as the actual working time; obtaining an energy saving formula E=P·(t fixed -t actual ), where E is the daily energy saving of the lighting device, P is the power of a single lighting device, t fixed is the working time of the lighting device under a fixed schedule, t actual is the actual working time of the lighting device; and according to the energy saving formula, the daily energy saving amount of the lighting device is determined.

[0011] According to another aspect of the present application, an intelligent road lighting device is provided, including: a first acquisition unit, used to acquire first environmental impact data, the first environmental impact data at least including solar altitude angle data and current lighting data at a current moment; a second acquisition unit, used to acquire second environmental impact data, the second environmental impact data at least including weather condition impact factors and vehicle flow data obtained according to model prediction; a first determination unit, used to determine whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; a second determination unit, used to determine the current brightness of the lighting device according to at least the first environmental impact data and the second environmental impact data when the lighting device is turned on.

[0012] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the intelligent road lighting methods.

[0013] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the intelligent lighting methods for the road.

[0014] By applying the technical solution of the present application, the intelligent lighting method of the above-mentioned road first obtains the first environmental impact data, which at least includes the solar altitude angle data and the current illumination data at the current moment; then obtains the second environmental impact data, which at least includes the weather condition influencing factors and vehicle flow data predicted by the model; then determines whether the lighting device is turned on based on the first environmental impact data and the second environmental impact data; finally, when the lighting device is turned on, determines the current brightness of the lighting device based on at least the first environmental impact data and the second environmental impact data. The method integrates GPS, light sensors, meteorological stations, vehicle detectors and other equipment to collect and analyze ambient light, weather conditions and traffic flow data in real time, dynamically adjust the switching time and brightness of street lamps, thereby achieving energy conservation and emission reduction and improving road safety, and solves the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a mobile terminal for executing a method for intelligent lighting of a road provided in an embodiment of the present application is shown;

[0017] Figure 2 A schematic diagram of a process of an intelligent road lighting method provided according to an embodiment of the present application is shown;

[0018] Figure 3 A structural block diagram of an intelligent road lighting device provided according to an embodiment of the present application is shown.

[0019] The above drawings include the following reference numerals:

[0020] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0021] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0022] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0025] Solar altitude angle: Solar altitude angle refers to the angle between the sun's rays and the horizon. It is an important parameter to measure the sun's position.

[0026] Light sensor: A light sensor is an electronic device that can detect the intensity of ambient light and usually outputs an electrical signal proportional to the light intensity.

[0027] Weather Condition Impact Factor: The weather condition impact factor is a numerical value that reflects the impact of current weather conditions on light and visibility. The default values ​​are 1 for sunny days, 0.7 for cloudy days, 0.5 for rainy days, and 0.3 for foggy days.

[0028] Dynamic brightness adjustment: Dynamic brightness adjustment refers to the process of automatically adjusting the brightness of street lights based on real-time environmental conditions (such as light intensity, traffic flow and weather conditions).

[0029] As introduced in the background technology, most of the prior art only considers a single factor (such as the light intensity detected by a photoresistor), and fails to fully utilize multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy utilization efficiency. In order to solve the problem that the lighting system in the prior art only considers a single factor, and fails to fully utilize multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy utilization efficiency, the embodiments of the present application provide a smart road lighting method, a smart road lighting device, a computer-readable storage medium and an electronic device.

[0030] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0031] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a mobile terminal of an intelligent road lighting method according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0032] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the intelligent lighting method of the road in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0033] In this embodiment, a smart lighting method for a road running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 2 FIG. 1 is a flow chart of an intelligent road lighting method according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:

[0035] Step S201, obtaining first environmental impact data, wherein the first environmental impact data at least includes solar altitude angle data and current illumination data at a current moment;

[0036] Specifically, the first environmental impact data is detected by multiple sensors, such as a light sensor, which is used to measure the light intensity of the current environment. The solar altitude angle data is used to represent the current time information, such as whether the current time is morning, noon or evening.

[0037] Wherein, obtaining the first environmental impact data includes the following steps:

[0038] Step S2011, according to the solar declination calculation formula Determine the solar declination, where δ is the solar declination mentioned above and n is the number of days in the year on the current day; where n is the number of days in the year on the current day, i.e. n is the number of days since January 1 of each year. For example, on January 1, n = 1. 23.44° is the inclination of the ecliptic;

[0039] Step S2012, calculate the local hour angle according to the formula Determine the local hour angle, where H is the local hour angle, t is the local time, λ is the longitude of the lighting device, and e is the time difference correction value; t is the local time in hours;

[0040] Step S2013, determining the solar altitude angle according to the solar altitude angle calculation formula h=arcsin(sinδsinφ+cosδcosφcosH), wherein h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the lighting device, and H is the local hour angle;

[0041] Step S2014: determining the first environmental impact data at least according to the solar altitude angle.

[0042] Specifically, the concept of solar altitude angle is introduced, and combined with weather conditions and current illumination, comprehensive judgment can be made to more accurately calculate the time to turn on and off the lights. Combined with geographical location and seasonal changes, the time to turn on and off the lights is calculated by the solar altitude angle to ensure that the changes in natural light are accurately reflected.

[0043] Step S202, obtaining second environmental impact data, wherein the second environmental impact data at least includes a weather condition impact factor and vehicle flow data obtained according to model prediction;

[0044] Specifically, the second environmental impact data is data predicted by the model, and the training data of each model is historical data collected by multiple sensors, such as traffic flow sensors and meteorological sensors. The traffic flow sensor is used to monitor the vehicle flow on the road in real time. The meteorological sensor is used to obtain the current weather conditions, including temperature, humidity, rainfall, etc.

[0045] Wherein, obtaining the second environmental impact data includes the following steps:

[0046] Step S2021, constructing a weather condition model and a traffic flow model;

[0047] Step S2022, inputting the first historical data into the weather condition model to predict the weather condition influencing factor, wherein the first historical data includes: the ambient weather at the historical moment and the historical weather condition influencing factor corresponding to the ambient weather at the historical moment acquired in the first historical time period;

[0048] Step S2023, inputting the second historical data into the above-mentioned traffic flow model to predict the above-mentioned vehicle flow data, wherein the above-mentioned second historical data includes: historical moments and historical vehicle flow data corresponding to the above-mentioned historical moments obtained in the second historical time period;

[0049] Step S2024: determining the second environmental impact data based on the weather condition impact factor and the vehicle flow data.

[0050] Specifically, the integrated light sensor, weather station and vehicle detector collects real-time data on ambient light, weather conditions and traffic flow, providing a basis for intelligent control. By analyzing historical traffic flow data, a traffic flow model is established to predict future traffic flow changes. By analyzing historical weather data, a weather condition model is established to predict future weather changes.

[0051] Since traffic flow and weather change rapidly in real time, if only the data collected by real-time sensors are used to control lighting devices, it will lead to control time lag problems. Therefore, a prediction model is used for prediction, and the predicted data is combined with the real-time collected data to comprehensively control the lighting devices, thereby improving the accuracy and real-time performance of the control.

[0052] Step S203, determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data;

[0053] Specifically, the lighting device can be a street lamp, which integrates light sensors, weather stations and vehicle detectors to collect ambient light, weather conditions and traffic flow data in real time, providing a basis for intelligent control.

[0054] The current illumination data includes the current illumination intensity. Determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data includes the following steps:

[0055] Step S301, determining a comprehensive influencing factor at least according to the current light intensity and the weather condition influencing factor;

[0056] Wherein, determining the comprehensive influencing factor at least according to the above-mentioned current light intensity and the above-mentioned weather condition influencing factor comprises the following steps:

[0057] Step S3011, obtaining the lighting impact factor formula Among them, I f is the current illumination impact factor, I current is the current light intensity, I min is the preset minimum light intensity threshold; the current illumination influence factor I f The value range is [0,1];

[0058] Step S3012, determining the current illumination influence factor according to the illumination influence factor formula, the current illumination intensity and the minimum illumination intensity threshold;

[0059] Step S3013, obtaining the comprehensive impact calculation formula C = W·I f , where C is the above comprehensive influencing factor, and W is the above weather condition influencing factor;

[0060] Step S3014, determining the comprehensive impact factor according to the comprehensive impact calculation formula, the weather condition impact factor and the current illumination impact factor.

[0061] Specifically, the influencing factors of weather conditions and current illumination are introduced to dynamically adjust the light on / off time to improve the adaptability and flexibility of the system. A weather condition influencing factor W is set with a value range of [0,1], 1 for sunny days, 0.7 for cloudy days, 0.5 for rainy days, and 0.3 for foggy days. That is, the value of the weather condition influencing factor corresponds to the actual weather conditions.

[0062] Step S302, when the solar altitude angle data is less than or equal to a first altitude threshold, and the comprehensive influencing factor is greater than or equal to a first value, determining that the lighting device is turned on;

[0063] Step S303, when the solar altitude angle data is greater than the second altitude threshold, and / or the comprehensive influencing factor is less than the second value, determine that the lighting device is turned off, the first altitude threshold is less than the second altitude threshold, and the first value is greater than the second value.

[0064] Specifically, the method for calculating the switching time of lights based on comprehensive analysis of multiple factors integrates data from light sensors, meteorological stations and vehicle detectors, combines the influencing factors of solar altitude angle and weather conditions, and dynamically calculates the switching time of street lights to ensure precise control under different environmental conditions.

[0065] The first height threshold can be set to -6°, the first value can be set to 0.5, the second height threshold can be set to 0°, and the second value can be set to 0.2. That is, when the sun altitude angle h is lower than a certain threshold (for example, -6° represents civil dusk / dawn), and the comprehensive impact factor C is greater than a certain threshold (for example, 0.5), the street light is turned on; when the sun altitude angle h is higher than a certain threshold (for example, 0° represents complete darkness), or the comprehensive impact factor C is less than a certain threshold (for example, 0.2), the street light is turned off.

[0066] Step S204: when the lighting device is turned on, determine the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data.

[0067] Specifically, based on light intensity, traffic flow and weather conditions, the brightness of street lights is dynamically adjusted through an optimization formula to achieve the dual goals of energy saving and safety.

[0068] The current illumination data includes the current illumination intensity, the vehicle flow data includes the predicted current traffic flow, and the current brightness of the lighting device is determined at least based on the first environmental impact data and the second environmental impact data, including the following steps:

[0069] Step S2041, obtaining a brightness adjustment formula Wherein, L is the current brightness of the above lighting device, L max is the maximum brightness of the above lighting device, I current is the current light intensity, I min is the preset minimum light intensity threshold, F is the predicted current traffic flow, and F max is the maximum traffic flow of the road section where the lighting device is located at the target time in the historical data, W is the weather condition influencing factor, the target time is the time of the day in the historical data that is the same as the current time, α, β and γ are the first weight coefficient, the second weight coefficient and the third weight coefficient, respectively, α+β+γ=1;

[0070] Step S2042: determining the current brightness of the lighting device according to the brightness adjustment formula.

[0071] Specifically, a dynamic brightness adjustment formula that takes into account light intensity, traffic flow and weather conditions can be introduced to more accurately adjust the brightness of street lamps. Among them, W is the weather condition influencing factor (1 for sunny days, 0.7 for cloudy days, 0.5 for rainy days, and 0.3 for foggy days). The weight coefficient can be optimized through machine learning based on historical data to ensure the best lighting effect and energy saving effect under different conditions.

[0072] Wherein, after determining the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data, the method further comprises the following steps:

[0073] Step S401, determining the daily on-time of the lighting device as the actual working time;

[0074] Step S402, obtaining the energy saving formula E=P·(t fixed -t actual ), where E is the daily energy saving of the lighting device, P is the power of a single lighting device, t fixed is the working time of the above lighting device under a fixed schedule, t actual The actual working time of the above lighting device;

[0075] Step S403: determining the daily energy saving amount of the lighting device according to the energy saving formula.

[0076] Specifically, the combined effects of light intensity, traffic flow and weather conditions are utilized to dynamically adjust the brightness of street lamps through an optimized mathematical formula to achieve the dual goals of energy saving and safety.

[0077] The intelligent lighting method for the above-mentioned road of the present application first obtains the first environmental impact data, which at least includes the solar altitude angle data and the current illumination data at the current moment; then obtains the second environmental impact data, which at least includes the weather condition influencing factors and vehicle flow data predicted by the model; then determines whether the lighting device is turned on based on the first environmental impact data and the second environmental impact data; finally, when the lighting device is turned on, determines the current brightness of the lighting device based on at least the first environmental impact data and the second environmental impact data. The method integrates GPS, light sensors, meteorological stations, vehicle detectors and other equipment to collect and analyze ambient light, weather conditions and traffic flow data in real time, dynamically adjust the switching time and brightness of street lamps, thereby achieving energy conservation and emission reduction and improving road safety, and solves the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy efficiency.

[0078] In some examples, the above method is applied to an intelligent road lighting control system based on multiple factors (including traffic flow, lighting, weather conditions, current time zone, etc.). The system monitors these factors in real time and uses dynamic algorithms to intelligently adjust the timing of turning on and off street lights and the brightness, thereby achieving the dual goals of energy saving and ensuring traffic safety.

[0079] The core of the system includes: traffic flow analysis module, light intensity measurement module, weather condition analysis module, time zone judgment module and intelligent control unit. Through comprehensive data analysis, the system can turn on or off street lights at the right time and dynamically adjust the lighting brightness according to real-time environmental conditions.

[0080] The data acquisition module includes: a traffic flow sensor for real-time monitoring of vehicle flow on the road; a light sensor for measuring the light intensity of the current environment; a meteorological sensor for obtaining the current weather conditions, including temperature, humidity, rainfall, etc.; a clock module for obtaining the current date and time information. The data processing module includes: a data storage unit for storing data collected by the sensor; a data analysis unit for processing and analyzing the collected data, including traffic flow analysis, light intensity analysis, weather condition analysis, etc.; an algorithm calculation unit for calculating the switching time of the street lamp according to the analysis results. The control execution module includes: a street lamp controller for controlling the switching of the street lamp according to the calculation results; and a communication module for exchanging data with the cloud server to achieve remote monitoring and management.

[0081] Among them, the traffic flow sensor monitors the vehicle flow on the road in real time and transmits the data to the data processing module. The light sensor measures the light intensity of the current environment and transmits the data to the data processing module. The meteorological sensor obtains the current weather conditions and transmits the data to the data processing module. The clock module obtains the current date and time information and transmits the data to the data processing module. The energy consumption sensor monitors the energy consumption of each street lamp and transmits the data to the data processing module. The data processing module also establishes a light intensity model by analyzing the historical light intensity data to predict future light intensity changes, and establishes an energy consumption model by analyzing the historical energy consumption data to predict future energy consumption changes.

[0082] The embodiment of the present application also provides an intelligent lighting device for a road. It should be noted that the intelligent lighting device for a road in the embodiment of the present application can be used to execute the intelligent lighting method for a road provided in the embodiment of the present application. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0083] The following is an introduction to the intelligent road lighting device provided in the embodiments of the present application.

[0084] Figure 3 Schematic diagram of an intelligent lighting device for a road according to an embodiment of the present application. Figure 3As shown, the device includes a first acquisition unit 10, a second acquisition unit 20, a first determination unit 30 and a second determination unit 40, the first acquisition unit 10 is used to acquire first environmental impact data, the first environmental impact data at least includes solar altitude angle data and current illumination data at the current moment; the second acquisition unit 20 is used to acquire second environmental impact data, the second environmental impact data at least includes weather condition impact factors and vehicle flow data obtained according to model prediction; the first determination unit 30 is used to determine whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; the second determination unit 40 is used to determine the current brightness of the lighting device when the lighting device is turned on, at least according to the first environmental impact data and the second environmental impact data.

[0085] The intelligent lighting device for the above-mentioned road of the present application comprises a first acquisition unit, a second acquisition unit, a first determination unit and a second determination unit, wherein the first acquisition unit is used to acquire first environmental impact data, the first environmental impact data at least including solar altitude angle data and current illumination data at the current moment; the second acquisition unit is used to acquire second environmental impact data, the second environmental impact data at least including weather condition impact factors and vehicle flow data predicted by the model; the first determination unit is used to determine whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; the second determination unit is used to determine the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data when the lighting device is turned on. The device collects and analyzes environmental illumination, weather conditions and traffic flow data in real time by integrating GPS, light sensors, meteorological stations and vehicle detectors, and dynamically adjusts the switching time and brightness of street lamps, thereby achieving energy conservation and emission reduction and improving road safety, and solving the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effect or low energy efficiency.

[0086] In some examples, the current illumination data includes the current illumination intensity, and the first determination unit includes a first determination module, a second determination module, and a third determination module. The first determination module is used to determine the comprehensive influence factor based on at least the current illumination intensity and the weather condition influence factor; the second determination module is used to determine that the lighting device is turned on when the solar altitude angle data is less than or equal to the first altitude threshold, and the comprehensive influence factor is greater than or equal to the first value; the third determination module is used to determine that the lighting device is turned off when the solar altitude angle data is greater than the second altitude threshold, and / or the comprehensive influence factor is less than the second value, the first altitude threshold is less than the second altitude threshold, and the first value is greater than the second value. Combined with the solar altitude angle and the weather condition influence factor, the switching time of the street lamp is dynamically calculated to ensure accurate control under different environmental conditions.

[0087] In some examples, the first determination module includes a first acquisition submodule, a first determination submodule, a second acquisition submodule and a second determination submodule, wherein the first acquisition submodule is used to acquire the lighting impact factor formula Among them, I f is the current illumination impact factor, I current is the current light intensity, I min is the preset minimum light intensity threshold; the first determination submodule is used to determine the current illumination influence factor according to the above lighting influence factor formula, the above current light intensity and the above minimum light intensity threshold; the second acquisition submodule is used to obtain the comprehensive influence calculation formula C = W·I f , where C is the comprehensive influencing factor, and W is the weather condition influencing factor; the second determination submodule is used to determine the comprehensive influencing factor according to the comprehensive influencing calculation formula, the weather condition influencing factor and the current illumination influencing factor. The influencing factors of weather conditions and current illumination are introduced to dynamically adjust the light switching time, thereby improving the adaptability and flexibility of the system.

[0088] In some examples, the current illumination data includes the current illumination intensity, the vehicle flow data includes the predicted current traffic flow, and the second determination unit includes a first acquisition module and a fourth determination module, the first acquisition module is used to acquire the brightness adjustment formula Wherein, L is the current brightness of the above lighting device, L max is the maximum brightness of the above lighting device, I current is the current light intensity, I min is the preset minimum light intensity threshold, F is the predicted current traffic flow, and F maxis the maximum traffic flow of the road section where the lighting device is located at the target time in the historical data, W is the weather condition influencing factor, the target time is the same time as the current time every day in the historical data, α, β and γ are the first weight coefficient, the second weight coefficient and the third weight coefficient respectively, α+β+γ=1; the fourth determination module is used to determine the current brightness of the lighting device according to the brightness adjustment formula. Introducing a dynamic brightness adjustment formula that comprehensively considers light intensity, traffic flow and weather conditions can more accurately adjust the brightness of street lights.

[0089] In some examples, the first acquisition unit includes a fifth determination module, a sixth determination module, a seventh determination module and an eighth determination module, wherein the fifth determination module is configured to calculate the solar declination according to the solar declination calculation formula Determine the solar declination, where δ is the solar declination, and n is the number of days in the current year; the sixth determination module is used to calculate the local hour angle according to the formula Determine the local hour angle, where H is the local hour angle, t is the local time, λ is the longitude of the lighting device, and e is the time difference correction value; the seventh determination module is used to determine the solar altitude angle according to the solar altitude angle calculation formula h=arcsin(sinδsinφ+cosδcosφcosH), where h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the lighting device, and H is the local hour angle; the eighth determination module is used to determine the first environmental impact data at least based on the solar altitude angle. Combined with the geographical location and seasonal changes, the light switching time is calculated by the solar altitude angle to ensure accurate reflection of natural light changes.

[0090] In some examples, the second acquisition unit includes a construction module, a first prediction module, a second prediction module and an eighth determination module, wherein the construction module is used to construct a weather condition model and a traffic flow model; the first prediction module is used to input the first historical data into the weather condition model to predict the weather condition influencing factor, wherein the first historical data includes the environmental weather at the historical moment and the historical weather condition influencing factor corresponding to the environmental weather at the historical moment acquired in the first historical time period; the second prediction module is used to input the second historical data into the traffic flow model to predict the vehicle flow data, wherein the second historical data includes the historical moment and the historical vehicle flow data corresponding to the historical moment acquired in the second historical time period; the eighth determination module is used to determine the second environmental impact data according to the weather condition influencing factor and the vehicle flow data. The integrated light sensor, weather station and vehicle detector collect the environmental light, weather condition and traffic flow data in real time, providing a basis for intelligent control.

[0091] In some examples, the device further includes a ninth determination module, a second acquisition module and a tenth determination module, wherein the ninth determination module is used to determine the daily opening time of the lighting device as the actual working time after determining the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data; the second acquisition module is used to obtain the energy saving formula E=P·(t fixed -t actual ), where E is the daily energy saving of the lighting device, P is the power of a single lighting device, t fixed is the working time of the above lighting device under a fixed schedule, t actual is the actual working time of the lighting device; the tenth determination module is used to determine the daily energy saving amount of the lighting device according to the energy saving formula. By using the comprehensive influence of light intensity, traffic flow and weather conditions, the brightness of the street lamp is dynamically adjusted through an optimized mathematical formula to achieve the dual goals of energy saving and safety.

[0092] The intelligent lighting device for the road includes a processor and a memory, the first acquisition unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions. The modules are all located in the same processor; or, the modules are located in different processors in any combination.

[0093] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to solve the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy efficiency.

[0094] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0095] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the intelligent lighting method for the road.

[0096] An embodiment of the present invention provides a processor, and the processor is used to run a program, wherein the intelligent lighting method for the road is executed when the program is run.

[0097] An embodiment of the present invention provides a device, the device including a processor, a memory, and a program stored in the memory and executable on the processor, and when the processor executes the program, at least the following steps are implemented:

[0098] Step S201, obtaining first environmental impact data, wherein the first environmental impact data at least includes solar altitude angle data and current illumination data at a current moment;

[0099] Step S202, obtaining second environmental impact data, wherein the second environmental impact data at least includes a weather condition impact factor and vehicle flow data obtained according to model prediction;

[0100] Step S203, determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data;

[0101] Step S204: when the lighting device is turned on, determine the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data.

[0102] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0103] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing at least the following method steps:

[0104] Step S201, obtaining first environmental impact data, wherein the first environmental impact data at least includes solar altitude angle data and current illumination data at a current moment;

[0105] Step S202, obtaining second environmental impact data, wherein the second environmental impact data at least includes a weather condition impact factor and vehicle flow data obtained according to model prediction;

[0106] Step S203, determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data;

[0107] Step S204: when the lighting device is turned on, determine the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data.

[0108] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0109] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0114] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0115] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0116] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0117] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0118] 1) The intelligent lighting method for the above-mentioned road of the present application first obtains the first environmental impact data, which at least includes the solar altitude angle data and the current illumination data at the current moment; then obtains the second environmental impact data, which at least includes the weather condition influencing factors and vehicle flow data predicted by the model; then determines whether the lighting device is turned on based on the first environmental impact data and the second environmental impact data; finally, when the lighting device is turned on, determines the current brightness of the lighting device based on at least the first environmental impact data and the second environmental impact data. The method integrates GPS, light sensors, meteorological stations, vehicle detectors and other equipment to collect and analyze ambient light, weather conditions and traffic flow data in real time, dynamically adjust the switching time and brightness of street lamps, thereby achieving energy conservation and emission reduction and improving road safety, and solves the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effects or low energy efficiency.

[0119] 2) The intelligent lighting device for the above-mentioned road of the present application comprises a first acquisition unit, a second acquisition unit, a first determination unit and a second determination unit, wherein the first acquisition unit is used to acquire first environmental impact data, the first environmental impact data at least including the solar altitude angle data and the current illumination data at the current moment; the second acquisition unit is used to acquire second environmental impact data, the second environmental impact data at least including the weather condition impact factor and the vehicle flow data predicted by the model; the first determination unit is used to determine whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; the second determination unit is used to determine the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data when the lighting device is turned on. The device collects and analyzes the ambient light, weather conditions and traffic flow data in real time by integrating GPS, light sensors, meteorological stations and vehicle detectors, and dynamically adjusts the switching time and brightness of the street lamps, thereby achieving energy conservation and emission reduction and improving road safety, and solving the problem that the lighting system in the prior art only considers a single factor and does not make full use of multiple sensor data for comprehensive analysis, resulting in poor lighting effect or low energy efficiency.

[0120] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for intelligent road lighting, characterized in that: include: Acquire first environmental impact data, where the first environmental impact data at least includes solar altitude angle data and current illumination data at a current moment; Acquire second environmental impact data, the second environmental impact data at least including a weather condition impact factor and vehicle flow data predicted by the model; determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; When the lighting device is turned on, the current brightness of the lighting device is determined at least according to the first environmental impact data and the second environmental impact data.

2. The method according to claim 1, characterized in that The current illumination data includes current illumination intensity, and determining whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data includes: Determining a comprehensive influencing factor based at least on the current light intensity and the weather condition influencing factor; When the solar altitude angle data is less than or equal to a first altitude threshold, and the comprehensive influencing factor is greater than or equal to a first value, determining that the lighting device is turned on; When the solar altitude angle data is greater than a second altitude threshold and / or the comprehensive influencing factor is less than a second value, it is determined that the lighting device is turned off, the first altitude threshold is less than the second altitude threshold, and the first value is greater than the second value.

3. The method according to claim 2, characterized in that Determining a comprehensive influencing factor based at least on the current light intensity and the weather condition influencing factor includes: Get the lighting impact factor formula Among them, I f is the current illumination impact factor, I current is the current light intensity, I min is the preset minimum light intensity threshold; Determine the current illumination influence factor according to the illumination influence factor formula, the current illumination intensity and the minimum illumination intensity threshold; Get the comprehensive impact calculation formula C = W·I f , where C is the comprehensive influencing factor and W is the weather condition influencing factor; The comprehensive impact factor is determined according to the comprehensive impact calculation formula, the weather condition impact factor and the current illumination impact factor.

4. The method according to claim 1, characterized in that: The current illumination data includes current illumination intensity, the vehicle flow data includes predicted current traffic flow, and the current brightness of the lighting device is determined at least based on the first environmental impact data and the second environmental impact data, including: Get the brightness adjustment formula Wherein, L is the current brightness of the lighting device, L max is the maximum brightness of the lighting device, I current is the current light intensity, I min is the preset minimum light intensity threshold, F is the predicted current traffic flow, and F max is the maximum traffic flow of the road section where the lighting device is located at the target time in the historical data, W is the weather condition influencing factor, the target time is the time of the day in the historical data that is the same as the current time, α, β and γ are the first weight coefficient, the second weight coefficient and the third weight coefficient, respectively, α+β+γ=1; The current brightness of the lighting device is determined according to the brightness adjustment formula.

5. The method according to claim 1, characterized in that Obtain the first environmental impact data, including: According to the solar declination calculation formula Determine the solar declination, where δ is the solar declination and n is the number of days in the year for the current day; Calculate the local hour angle using the formula Determine the local hour angle, where H is the local hour angle, t is the local time, λ is the longitude of the lighting device, and e is the time difference correction value; Determine the solar altitude angle according to the solar altitude angle calculation formula h=arcsin(sinδsinφ+cosδcosφcosH), wherein h is the solar altitude angle, δ is the solar declination, φ is the geographical latitude of the lighting device, and H is the local hour angle; The first environmental impact data is determined at least according to the solar altitude angle.

6. The method according to claim 1, characterized in that Obtain the second environmental impact data, including: Build weather condition models and traffic flow models; Inputting first historical data into the weather condition model to predict the weather condition influencing factor, wherein the first historical data includes: ambient weather at a historical moment and a historical weather condition influencing factor corresponding to the ambient weather at the historical moment, obtained within a first historical time period; Inputting the second historical data into the traffic flow model to predict the vehicle flow data, wherein the second historical data includes: historical moments and historical vehicle flow data corresponding to the historical moments acquired in a second historical time period; The second environmental impact data is determined according to the weather condition impact factor and the vehicle flow data.

7. The method according to claim 1, characterized in that After determining the current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data, the method further includes: Determining the daily on-time of the lighting device as the actual working time; Get the energy saving formula E = P (t fixed -t actual ), where E is the daily energy saving of the lighting device, P is the power of a single lighting device, t fixed is the working time of the lighting device under a fixed schedule, t actual is the actual working time of the lighting device; According to the energy saving formula, the daily energy saving amount of the lighting device is determined.

8. An intelligent road lighting device, characterized in that: include: A first acquisition unit is used to acquire first environmental impact data, wherein the first environmental impact data at least includes solar altitude angle data and current illumination data at a current moment; A second acquisition unit is used to acquire second environmental impact data, wherein the second environmental impact data at least includes a weather condition impact factor and vehicle flow data obtained according to model prediction; a first determining unit, configured to determine whether the lighting device is turned on according to the first environmental impact data and the second environmental impact data; A second determining unit is configured to determine, when the lighting device is turned on, a current brightness of the lighting device at least according to the first environmental impact data and the second environmental impact data.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the intelligent road lighting method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing the intelligent lighting method for the road as described in any one of claims 1 to 7.

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