Outdoor lighting equipment risk analysis system and method based on data prediction, lighting equipment and storage medium

Abstract

The invention discloses an outdoor lighting equipment risk analysis system and method based on data prediction, lighting equipment and a storage medium, and relates to the technical field of equipment risk analysis, and the method comprises the steps: collecting flow information data of a target area from a plurality of preset data sources, and forming a precondition for intelligent on-off of the outdoor lighting equipment; when the outdoor lighting equipment is intelligently turned on, determining a light pollution data range and an equipment lighting range; target body movement data and position data in the target area are collected in real time, and the priority relation between the light pollution data range and the equipment illumination range is determined; determining an outdoor lighting equipment risk analysis instruction; and intelligent control of the outdoor lighting equipment is realized. Illumination processing at night and at low flow is ensured, basic illumination requirements are guaranteed, meanwhile, potential safety hazards caused by light pollution are reduced, intelligent risk analysis of outdoor illumination equipment is formed, and the intelligent level of the outdoor illumination equipment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment risk analysis, and in particular to a risk analysis system and method for outdoor lighting equipment based on data prediction, lighting equipment and storage medium. Background Art

[0002] At present, with the rapid development of the Internet of Things and digital technology, setting corresponding digital chips for outdoor lighting equipment to achieve remote automatic control has gradually come into people's view. As one of the necessities for people or vehicles to travel at night, outdoor lighting equipment relieves visual pressure while also bringing certain light pollution problems.

[0003] Especially for outdoor lighting street lamps at night, in order to ensure a larger lighting range, most of the outdoor lighting street lamps on the market are currently tilted at different angles, that is, they are not parallel to the horizontal line of the ground. In this case, due to the scattering of light, it will cause a certain range of light pollution problems, which will have a certain impact on vehicles passing through at night and pose a safety hazard. Therefore, how to reduce the safety hazards caused by light pollution while ensuring normal lighting is one of the main issues in the current intelligent risk analysis of outdoor lighting equipment. Summary of the invention

[0004] The purpose of the present invention is to provide a risk analysis system, method, lighting equipment and storage medium for outdoor lighting equipment based on data prediction, which are used to solve the problem of reducing the safety hazards caused by light pollution while ensuring normal lighting.

[0005] In a first aspect, the present application provides a risk analysis method for outdoor lighting equipment based on data prediction, the method comprising:

[0006] Collect traffic information data of the target area from multiple preset data sources to form the prerequisite for intelligent switching of outdoor lighting equipment;

[0007] Based on the preconditions of the intelligent on and off of outdoor lighting equipment, when the outdoor lighting equipment is intelligently turned on, the light pollution data range and the equipment lighting range are determined;

[0008] Collect the target movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range;

[0009] Determine risk analysis instructions for outdoor lighting equipment based on the priority relationship between the light pollution data range and the equipment lighting range;

[0010] Based on the risk analysis instructions of outdoor lighting equipment, intelligent control of outdoor lighting equipment is realized.

[0011] In combination with the first aspect, in an implementation of the first aspect of the present application, the traffic information data of the target area includes:

[0012] The sum of vehicle and pedestrian flow data in the target area;

[0013] Use multiple preset data sources to collect vehicle and pedestrian flow data in the target area, set a fixed time period, and continuously calculate the flow information data of the target area based on the fixed time period;

[0014] Set a flow information data threshold for the target area, and determine the duration of the flow information data of the target area being lower than the flow information data threshold for the target area as a precondition for the intelligent on / off of the outdoor lighting equipment;

[0015] System settings can adjust the duration , the duration of the traffic information data in the target area being lower than the traffic information data threshold of the target area reaches When the flow information data in the target area is higher than the flow information data threshold of the target area, it is determined that the outdoor lighting equipment is intelligently turned on.

[0016] In combination with the first aspect, in an implementation of the first aspect of the present application, determining the light pollution data range and the device lighting range includes:

[0017] Obtaining location information of outdoor lighting equipment, and when the outdoor lighting equipment is turned on, using brightness measurement equipment to determine lighting ranges of several groups of equipment, and taking an average value based on the lighting ranges of the several groups of equipment as the final determined lighting range of the equipment;

[0018] The light pollution data range includes same-direction light pollution and reverse light pollution;

[0019] The same-direction light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the same side as the outdoor lighting equipment; the reverse light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the opposite side of the outdoor lighting equipment;

[0020] The target objects include motor vehicles, non-motor vehicles and pedestrians; wherein the non-motor vehicles and pedestrians do not have a light pollution data range;

[0021] When the outdoor lighting equipment is turned on, a brightness measurement device is used to obtain several groups of pollution angles of the same-direction light pollution and the reverse light pollution, and the pollution angles of the same-direction light pollution and the reverse light pollution are determined based on the average values ​​of the several groups of pollution angles;

[0022] The pollution angle refers to the angle between the first straight line and the vertical plane where the outdoor lighting device is located, and the first straight line refers to the straight line formed by the edge light point of the outdoor lighting device and the eye of the target object.

[0023] In combination with the first aspect, in an implementation of the first aspect of the present application, the priority relationship between the light pollution data range and the device lighting range includes:

[0024] The first priority relationship means that the light pollution data range is higher than the equipment lighting range, which means that the target object has priority to enter the light pollution data range;

[0025] The second priority relationship means that the light pollution data range is equal to the device lighting range, which means that multiple targets enter the light pollution data range and the device lighting range at the same time.

[0026] In combination with the first aspect, in an implementation of the first aspect of the present application, determining the priority relationship between the light pollution data range and the device lighting range includes:

[0027] Distance thresholds are set for each target object, including motor vehicle threshold, non-motor vehicle threshold and pedestrian threshold. When the distance between each target object and the light pollution data range or the equipment lighting range is equal to the distance threshold, the travel data and position data of each target object are collected.

[0028] The travel data is based on the moving speed of the previous time period as a standard, and the specific time value of the previous time period is set by the system;

[0029] Based on the travel data and position data of each target, the time point when each target reaches its light pollution data range and equipment lighting range for the same outdoor lighting equipment is calculated by using data prediction method;

[0030] If a certain target body reaches the light pollution data range before other target bodies, the first risk analysis instruction output is determined;

[0031] If one or more target objects reach the light pollution data range and another target object reaches the device lighting range at the same time, determining the second risk analysis instruction output;

[0032] If a certain target object reaches the light pollution data range while other target objects are located at a distance from the certain target object that is less than the motor vehicle length of the certain target object, the third risk analysis instruction output is determined.

[0033] In combination with the first aspect, in an implementation of the first aspect of the present application, determining the first risk analysis instruction output includes:

[0034] Reduce the brightness of outdoor lighting equipment and set the system to low brightness to reduce the impact of light pollution data range;

[0035] Determining the second risk analysis instruction output includes:

[0036] Turn off a number of light bulbs of outdoor lighting equipment close to a certain target object to form a new light pollution data range, and determine that there are no other motor vehicles in the formed new light pollution data range.

[0037] In combination with the first aspect, in an implementation of the first aspect of the present application, determining the third risk analysis instruction output includes:

[0038] Output a second risk analysis instruction, mark other targets whose position distance from a certain target is less than the motor vehicle length of the certain target, and delete the data information of the marked target; wherein, the position distance refers to the overlapping distance of the motor vehicle body; wherein, if the horizontal distance of other targets to the outdoor lighting equipment is higher than that of a certain target, the other targets will not be marked.

[0039] In a second aspect, the present application provides an outdoor lighting equipment risk analysis system based on data prediction, the outdoor lighting equipment risk analysis system comprising:

[0040] The pre-on / off management module is used to collect the flow information data of the target area from multiple preset data sources to form the pre-conditions for the intelligent on / off of outdoor lighting equipment;

[0041] The data processing module determines the light pollution data range and the equipment lighting range when the outdoor lighting equipment is intelligently turned on based on the preconditions of the intelligent on and off of the outdoor lighting equipment;

[0042] The real-scene analysis module is used to collect the target movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range;

[0043] The risk analysis module determines the risk analysis instructions for outdoor lighting equipment based on the priority relationship between the light pollution data range and the equipment lighting range;

[0044] The command control module realizes intelligent control of outdoor lighting equipment based on the risk analysis instructions of outdoor lighting equipment.

[0045] On the third aspect, please provide an outdoor lighting device based on data prediction, the outdoor lighting device includes: an outdoor lighting device base, a lamp pole, an outdoor lighting lamp head and a chip; the lamp pole is installed on the outdoor lighting device base, the outdoor lighting lamp head is connected to the lamp pole, the chip is embedded in the outdoor lighting lamp head, the chip includes a memory and at least one processor, and instructions are stored in the memory; the at least one processor calls the instructions in the memory to enable the outdoor lighting device to execute the outdoor lighting device risk analysis method based on data prediction.

[0046] In a fourth aspect, the present application further provides a computer-readable storage medium having instructions stored thereon, and when the instructions are executed by a processor, the method for risk analysis of outdoor lighting equipment based on data prediction is implemented.

[0047] Compared with the prior art, the beneficial effects of the present invention are: in the field of outdoor lighting equipment, the present invention proposes the central idea of ​​intelligent control of outdoor lighting equipment, uses data from multiple data sources for analysis and processing, ensures lighting processing at night and when traffic is low, and reduces the safety hazards caused by light pollution while ensuring basic lighting needs, forms intelligent risk analysis of outdoor lighting equipment, and improves the intelligence level of outdoor lighting equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A schematic diagram of a process of a risk analysis method for outdoor lighting equipment based on data prediction according to the present invention;

[0049] Figure 2 This is a schematic diagram of module connections of a risk analysis system for outdoor lighting equipment based on data prediction according to the present invention;

[0050] Figure 3 A schematic diagram of an outdoor lighting device based on data prediction according to the present invention;

[0051] In the figure, 1. outdoor lighting equipment base; 2. lamp pole; 3. outdoor lighting lamp head; 4. chip. DETAILED DESCRIPTION

[0052] The embodiments of the present application provide a digital twin display method, device, equipment and storage medium for a smart logo. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this 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 interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In an embodiment of the present application, an embodiment of a risk analysis method for outdoor lighting equipment based on data prediction includes:

[0054] Collect traffic information data of the target area from multiple preset data sources to form the prerequisite for intelligent switching of outdoor lighting equipment;

[0055] Specifically, first, determine which data sources can provide traffic information data about the target area, such as sensor networks, satellite data, IoT devices, etc. These data sources should be able to collect the location parameters of the target object in real time or regularly. Next, establish a stable and efficient data collection system, use communication protocols and data transmission technology to store and transmit the traffic information data collected in the target area, to ensure the integrity, real-time and callability of the data.

[0056] The traffic information data of the target area includes:

[0057] The sum of vehicle and pedestrian flow data in the target area;

[0058] Use multiple preset data sources to collect vehicle and pedestrian flow data in the target area, set a fixed time period, and continuously calculate the flow information data of the target area based on the fixed time period;

[0059] Specifically, the fixed time period can be set to 1 minute, 5 minutes, etc., and the data information formed by the above data sources, by using the communication protocol and data transmission technology, the flow data within the fixed time period can be calculated. For example, taking 1 minute as an example, the data will form a group of vehicle flow and pedestrian flow data sum of the target area every 1 minute, and the flow information data threshold of the target area is set by the system, and the duration of the flow information data of the target area being lower than the flow information data threshold of the target area is determined as the precondition for the intelligent on and off of the outdoor lighting equipment;

[0060] Specifically, the sum of the vehicle flow and pedestrian flow data of the target area within each minute is determined and compared with the flow information data threshold of the target area. If the flow information data of the target area is lower than the flow information data threshold of the target area, it is recorded as 1 minute. If the flow information data of the target area in the next minute is also lower than the flow information data threshold of the target area, the duration is 1+1=2 minutes. Conversely, if the flow information data of the target area in the next minute is not lower than the flow information data threshold of the target area, the duration is reset to zero. The above steps can specifically provide accurate preconditions for the present application, based on the premise that the traffic flow is relatively sparse at night. If it is in the peak traffic period, the impact of vehicle lights under the peak traffic flow and the impact of the peak traffic flow itself are much higher than the impact of outdoor lighting equipment. Therefore, the present application is more accurate in setting the preconditions, which is used to reduce the safety risks of car owners driving at high speeds when the traffic flow is relatively sparse at night.

[0061] System settings can adjust the duration , the duration of the traffic information data in the target area being lower than the traffic information data threshold of the target area reaches When the flow information data in the target area is higher than the flow information data threshold of the target area, it is determined that the outdoor lighting equipment is intelligently turned on.

[0062] Based on the preconditions of the intelligent on and off of outdoor lighting equipment, when the outdoor lighting equipment is intelligently turned on, the light pollution data range and the equipment lighting range are determined;

[0063] Determining the light pollution data range and the equipment lighting range includes:

[0064] Obtaining location information of outdoor lighting equipment, and when the outdoor lighting equipment is turned on, using brightness measurement equipment to determine lighting ranges of several groups of equipment, and taking an average value based on the lighting ranges of the several groups of equipment as the final determined lighting range of the equipment;

[0065] The light pollution data range includes same-direction light pollution and reverse light pollution;

[0066] The same-direction light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the same side as the outdoor lighting equipment; the reverse light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the opposite side of the outdoor lighting equipment;

[0067] Specifically, in this application, outdoor lighting equipment takes street lamps as an example. As the most common outdoor lighting equipment, the light pollution caused by street lamps cannot be ignored. Street lamps are often set at one end of the road. For most roads, there are two-way lanes. When vehicles in the same lane are driving towards the street lamps, the light pollution points formed on one side of the street lamps are the same-direction light pollution. For the opposite lanes, when vehicles in the opposite lanes are driving towards the street lamps, the light pollution points formed on the other side of the street lamps are the reverse light pollution.

[0068] The target bodies include motor vehicles, non-motor vehicles and pedestrians; wherein, the non-motor vehicles and pedestrians do not have a light pollution data range; wherein, the non-motor vehicles and pedestrians only consider the problem of lighting range.

[0069] When the outdoor lighting equipment is turned on, a brightness measurement device is used to obtain several groups of pollution angles of the same-direction light pollution and the reverse light pollution, and the pollution angles of the same-direction light pollution and the reverse light pollution are determined based on the average values ​​of the several groups of pollution angles;

[0070] The pollution angle refers to the angle between the first straight line and the vertical plane where the outdoor lighting device is located, and the first straight line refers to the straight line formed by the edge light point of the outdoor lighting device and the target object's eyes;

[0071] Specifically, the pollution angle is essentially a standard measurement method, not limited to being formed with any plane. In this application, it is specifically defined as the angle with the vertical plane where the outdoor lighting equipment is located. During the measurement process, it is only necessary to ensure that each measurement is made with the same plane. In this application, the vertical plane where the outdoor lighting equipment is located is taken as an example, that is, the base of the lighting equipment is taken as the base point, and the plane where the entire lamp pole is located is the vertical plane where the outdoor lighting equipment is located. After confirming the pollution angle, the light pollution range is calculated each time according to the vertical plane where the outdoor lighting equipment is located and the pollution angle. In the subsequent adjustment process, new light pollution areas can be quickly identified;

[0072] Collect the target movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range;

[0073] The priority relationship between the light pollution data range and the device lighting range includes:

[0074] The first priority relationship means that the light pollution data range is higher than the equipment lighting range, which means that the target object has priority to enter the light pollution data range;

[0075] The second priority relationship means that the light pollution data range is equal to the device lighting range, which means that multiple targets enter the light pollution data range and the device lighting range at the same time.

[0076] Specifically, this application aims to reduce light pollution while ensuring lighting needs. Therefore, the priority processing is mainly to reduce light pollution when lighting is not needed, and automatically adjust when lighting is needed, so as to make the two compatible;

[0077] The priority relationship between the light pollution data range and the device lighting range is determined as follows:

[0078] Distance thresholds are set for each target object, including motor vehicle threshold, non-motor vehicle threshold and pedestrian threshold. When the distance between each target object and the light pollution data range or the equipment lighting range is equal to the distance threshold, the travel data and position data of each target object are collected.

[0079] The travel data is based on the moving speed of the previous time period as a standard, and the specific time value of the previous time period is set by the system;

[0080] Specifically, the system can set a time, such as 1 minute, and measure the moving speed within 1 minute as the basis for data prediction, so as to determine the time for each target object to move to the corresponding light pollution data range or equipment lighting range, so as to perform priority processing;

[0081] Based on the travel data and position data of each target object, the time point when each target object reaches its light pollution data range and the device lighting range for the same outdoor lighting device is calculated;

[0082] If a certain target body reaches the light pollution data range before other target bodies, the first risk analysis instruction output is determined;

[0083] If one or more target objects reach the light pollution data range and another target object reaches the device lighting range at the same time, determining the second risk analysis instruction output;

[0084] If a certain target object reaches the light pollution data range while other target objects are located at a distance from the certain target object that is less than the motor vehicle length of the certain target object, the third risk analysis instruction output is determined.

[0085] Determining the first risk analysis instruction output includes:

[0086] Reduce the brightness of outdoor lighting equipment and set the system to low brightness to reduce the impact of light pollution data range;

[0087] Determining the second risk analysis instruction output includes:

[0088] Turn off a number of light bulbs of outdoor lighting equipment close to a certain target object to form a new light pollution data range, and determine that there are no other motor vehicles in the formed new light pollution data range.

[0089] Determining the third risk analysis instruction output includes:

[0090] Output a second risk analysis instruction, mark other targets whose position distance from a certain target is less than the motor vehicle length of the certain target, and delete the data information of the marked target; wherein, the position distance refers to the overlapping distance of the motor vehicle body; wherein, if the horizontal distance of other targets to the outdoor lighting equipment is higher than that of a certain target, the other targets will not be marked.

[0091] Specifically, the third risk analysis instruction is mainly to reduce the processing power consumption of outdoor lighting equipment. In actual scenarios, due to the obstruction of light, when vehicles overlap, the overlapping vehicles will not be affected by light pollution. In this case, the system does not need to perform calculations again. In this embodiment, three lanes are used as an example for explanation. Taking the opposite lane as an example, if the vehicle in the middle lane reaches the light pollution data range first, the vehicles in the other two lanes overlap with the vehicle in the middle lane, and the overlapping distance is less than the distance of the motor vehicle in the middle lane itself, then the vehicles in the outer lane (i.e., the lane farthest from the outdoor lighting equipment) will be blocked by the vehicles in the middle lane and will not be affected by light pollution, while the vehicles in the inner lane (i.e., the lane closest to the outdoor lighting equipment) will not be blocked by the vehicles in the middle lane, but will still be affected by light pollution. Therefore, the present application introduces a new technical feature, namely, the horizontal distance of other target bodies to the outdoor lighting equipment for measurement. The horizontal distance is based on the road as the entire plane, the straight line where the base of the outdoor lighting equipment is located is the horizontal line, and the straight-line distance of the vehicle to the horizontal line is recorded as the horizontal distance, which is essentially to measure the overlapping impact between each motor vehicle.

[0092] Based on the risk analysis instructions of outdoor lighting equipment, intelligent control of outdoor lighting equipment is realized.

[0093] The above describes a risk analysis system for outdoor lighting equipment based on data prediction in an embodiment of the present application. The following describes a risk analysis system for outdoor lighting equipment based on data prediction in an embodiment of the present application. Figure 2 In an embodiment of the present application, an embodiment of a risk analysis system for outdoor lighting equipment based on data prediction includes:

[0094] The pre-on / off management module 101 is used to collect flow information data of the target area from multiple preset data sources to form the pre-conditions for intelligent on / off of outdoor lighting equipment;

[0095] The data processing module 102 determines the light pollution data range and the equipment lighting range when the outdoor lighting equipment is intelligently turned on based on the preconditions of the outdoor lighting equipment being intelligently turned on and off;

[0096] The real scene analysis module 103 is used to collect the target body movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range;

[0097] The risk analysis module 104 determines the risk analysis instruction of the outdoor lighting equipment based on the priority relationship between the light pollution data range and the equipment lighting range;

[0098] The instruction control module 105 implements intelligent control of the outdoor lighting equipment based on the risk analysis instructions of the outdoor lighting equipment.

[0099] At the same time, the present application also provides an outdoor lighting device based on data prediction, and the outdoor lighting device based on data prediction includes: an outdoor lighting device base 1, a lamp pole 2, an outdoor lighting lamp head 3 and a chip 4; the lamp pole 2 is installed on the outdoor lighting device base 1, the outdoor lighting lamp head 3 is connected to the lamp pole 2, and the chip 4 is embedded in the outdoor lighting lamp head 3, and the chip 4 includes a memory and at least one processor, and instructions are stored in the memory; the at least one processor calls the instructions in the memory so that the outdoor lighting device based on data prediction executes the outdoor lighting device risk analysis method based on data prediction.

[0100] like Figure 3 As shown, the outdoor lighting lamp head 3 adopts an array of lamp beads. In the determination of the second risk analysis instruction output, it is mentioned that several bulbs of the outdoor lighting equipment close to a certain target body are turned off to form a new light pollution data range, which may specifically include:

[0101] By turning off a row of array lamp beads close to a certain target direction, the light pollution data range formed will be closer to the front than the original light pollution data range. After the vehicle passes the original light pollution data range, the turned-off lamp beads will be turned on again, and the light pollution data range will be restored to its original position, thereby reducing the impact of light pollution during the driving process of the vehicle.

[0102] The present application also additionally provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, the method for risk analysis of outdoor lighting equipment based on data prediction is implemented.

[0103] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A risk analysis method for outdoor lighting equipment based on data prediction, characterized in that: The method includes: Collect traffic information data of the target area from multiple preset data sources to form the prerequisite for intelligent switching of outdoor lighting equipment; Based on the preconditions of the intelligent on and off of outdoor lighting equipment, when the outdoor lighting equipment is intelligently turned on, the light pollution data range and the equipment lighting range are determined; Collect the target movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range; Determine risk analysis instructions for outdoor lighting equipment based on the priority relationship between the light pollution data range and the equipment lighting range; Based on the risk analysis instructions of outdoor lighting equipment, intelligent control of outdoor lighting equipment is realized.

2. The method for risk analysis of outdoor lighting equipment based on data prediction according to claim 1, characterized in that: The traffic information data of the target area includes: The sum of vehicle and pedestrian flow data in the target area; Use multiple preset data sources to collect vehicle and pedestrian flow data in the target area, set a fixed time period, and continuously calculate the flow information data of the target area based on the fixed time period; Set a flow information data threshold for the target area, and determine the duration of the flow information data of the target area being lower than the flow information data threshold for the target area as a precondition for the intelligent on / off of the outdoor lighting equipment; System settings can adjust the duration , the duration of the traffic information data in the target area being lower than the traffic information data threshold of the target area reaches When the flow information data in the target area is higher than the flow information data threshold of the target area, it is determined that the outdoor lighting equipment is intelligently turned on.

3. The risk analysis method for outdoor lighting equipment based on data prediction according to claim 1, characterized in that: Determining the light pollution data range and the equipment lighting range includes: Obtaining location information of outdoor lighting equipment, and when the outdoor lighting equipment is turned on, using brightness measurement equipment to determine lighting ranges of several groups of equipment, and taking an average value based on the lighting ranges of the several groups of equipment as the final determined lighting range of the equipment; The light pollution data range includes same-direction light pollution and reverse light pollution; The same-direction light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the same side as the outdoor lighting equipment; the reverse light pollution refers to the pollution of the light of the outdoor lighting equipment to the target on the opposite side of the outdoor lighting equipment; The target objects include motor vehicles, non-motor vehicles and pedestrians; wherein the non-motor vehicles and pedestrians do not have a light pollution data range; When the outdoor lighting equipment is turned on, a brightness measurement device is used to obtain several groups of pollution angles of the same-direction light pollution and the reverse light pollution, and the pollution angles of the same-direction light pollution and the reverse light pollution are determined based on the average values ​​of the several groups of pollution angles; The pollution angle refers to the angle between the first straight line and the vertical plane where the outdoor lighting device is located, and the first straight line refers to the straight line formed by the edge light point of the outdoor lighting device and the eye of the target object.

4. The method for risk analysis of outdoor lighting equipment based on data prediction according to claim 1, characterized in that: The priority relationship between the light pollution data range and the device lighting range includes: The first priority relationship means that the light pollution data range is higher than the equipment lighting range, which means that the target object has priority to enter the light pollution data range; The second priority relationship means that the light pollution data range is equal to the device lighting range, which means that multiple targets enter the light pollution data range and the device lighting range at the same time.

5. The method for risk analysis of outdoor lighting equipment based on data prediction according to claim 4, characterized in that: The priority relationship between the light pollution data range and the device lighting range is determined as follows: Distance thresholds are set for each target object, including motor vehicle threshold, non-motor vehicle threshold and pedestrian threshold. When the distance between each target object and the light pollution data range or the equipment lighting range is equal to the distance threshold, the travel data and position data of each target object are collected. The travel data is based on the moving speed of the previous time period as a standard, and the specific time value of the previous time period is set by the system; Based on the travel data and position data of each target, the time point when each target reaches its light pollution data range and equipment lighting range for the same outdoor lighting equipment is calculated by using data prediction method; If a certain target body reaches the light pollution data range before other target bodies, the first risk analysis instruction output is determined; If one or more target objects reach the light pollution data range and another target object reaches the device lighting range at the same time, determining the second risk analysis instruction output; If a certain target object reaches the light pollution data range while other target objects are located at a distance from the certain target object that is less than the motor vehicle length of the certain target object, the third risk analysis instruction output is determined.

6. The method for risk analysis of outdoor lighting equipment based on data prediction according to claim 5, characterized in that: Determining the first risk analysis instruction output includes: Reduce the brightness of outdoor lighting equipment and set the system to low brightness to reduce the impact of light pollution data range; Determining the second risk analysis instruction output includes: Turn off a number of light bulbs of outdoor lighting equipment close to a certain target object to form a new light pollution data range, and determine that there are no other motor vehicles in the formed new light pollution data range.

7. The method for risk analysis of outdoor lighting equipment based on data prediction according to claim 5, characterized in that: Determining the third risk analysis instruction output includes: Output a second risk analysis instruction, mark other targets whose position distance from a certain target is less than the motor vehicle length of the certain target, and delete the data information of the marked target; wherein, the position distance refers to the overlapping distance of the motor vehicle body; wherein, if the horizontal distance of other targets to the outdoor lighting equipment is higher than that of a certain target, the other targets will not be marked.

8. A risk analysis system for outdoor lighting equipment based on data prediction, characterized in that: The outdoor lighting equipment risk analysis system comprises: The pre-on / off management module is used to collect the flow information data of the target area from multiple preset data sources to form the pre-conditions for the intelligent on / off of outdoor lighting equipment; The data processing module determines the light pollution data range and the equipment lighting range when the outdoor lighting equipment is intelligently turned on based on the preconditions of the intelligent on and off of the outdoor lighting equipment; The real-scene analysis module is used to collect the target movement data and position data in the target area in real time, and determine the priority relationship between the light pollution data range and the equipment lighting range; The risk analysis module determines the risk analysis instructions for outdoor lighting equipment based on the priority relationship between the light pollution data range and the equipment lighting range; The command control module realizes intelligent control of outdoor lighting equipment based on the risk analysis instructions of outdoor lighting equipment.

9. An outdoor lighting device based on data prediction, characterized in that: The outdoor lighting equipment includes: an outdoor lighting equipment base, a lamp pole, an outdoor lighting lamp head and a chip; the lamp pole is installed on the outdoor lighting equipment base, the outdoor lighting lamp head is connected to the lamp pole, and the chip is embedded in the outdoor lighting lamp head. The chip includes a memory and at least one processor, and instructions are stored in the memory; the at least one processor calls the instructions in the memory so that the outdoor lighting equipment executes a risk analysis method for outdoor lighting equipment based on data prediction as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, a risk analysis method for outdoor lighting equipment based on data prediction is implemented as described in any one of claims 1-7.

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