Networking communication method and system for intelligent street lamps

Abstract

The invention discloses a networking communication method and system for intelligent street lamps, and relates to the technical field of intelligent street lamps, and the networking communication system comprises an edge calculation module, a region calculation module and a fault recording module. The total communication module is connected with n area calculation modules, and each area calculation module is connected with an edge calculation subsystem composed of a plurality of edge calculation modules; according to the invention, monitoring data capture is realized through a camera, a standby battery and a data transmission line in the edge calculation module; preliminary data processing and secondary data processing are realized through an edge center and an edge calculation unit; adjusting operation is executed based on the data processing result through the intelligent street lamp and the standby battery; according to the invention, the interconnection and intercommunication problems among the street lamps are optimized through the solution of the optimal route, the remote control and troubleshooting capabilities of equipment are improved through data summarization and analysis, and the data acquisition, information transmission and intelligent control capabilities of an intelligent street lamp communication network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart street lamps, and specifically to a networking communication method and system for smart street lamps. Background Art

[0002] Smart street lights are an important part of smart city construction. Based on road lighting poles, they integrate multiple functions such as public security, traffic signals, communications, and traffic signs, realizing the integration of multiple poles, reducing road poles, and releasing public space resources. Smart street lights not only have the lighting functions of ordinary street lights, but also can achieve energy saving and reduce maintenance costs through precise switching, on-demand lighting, real-time dimming and other technologies. The cameras installed on the light poles can monitor traffic flow and road conditions in real time, use remote control technology and manage and monitor street lights in real time through the Internet, realize switching, brightness adjustment, lighting range control and other functions, and can detect pedestrians. It exists and performs intelligent control. When there are no pedestrians passing by, it enters standby mode to save energy, and automatically turns on to provide lighting when pedestrians pass by. Smart street lights are widely used in smart cities, communities, scenic spots, parks, digital villages, municipalities, highways, characteristic towns and other occasions, providing intelligent solutions for various application scenarios. In the future, with the continuous development of technologies such as 5G, artificial intelligence and the Internet of Things, smart street lights will achieve more intelligent and automated control and management, bringing more convenience and comfort to urban management and residents' lives. At the same time, with the continuous advancement of smart city construction, smart street lights will become an indispensable part of urban infrastructure. However, the existing smart street light technology still faces some challenges in its development process. For example, the interconnection and interoperability between street lights needs to be optimized, the ability of remote control and troubleshooting of equipment needs to be improved, and the ability of data collection, information transmission and intelligent control needs to be improved. Summary of the invention

[0003] In order to overcome the problems existing in the background technology that the interconnection and intercommunication between street lamps need to be optimized, the ability of remote control and troubleshooting of equipment needs to be improved, and the ability of data collection, information transmission and intelligent control needs to be improved, the embodiments of the present invention provide a networking communication method and system for smart street lamps.

[0004] The purpose of the present invention can be achieved by the following technical solution: A networking communication system for smart street lamps, including an edge computing module, a regional computing module and a fault recording module. The overall communication module is connected to n regional computing modules, and each regional computing module is connected to several edge computing modules.

[0005] Each edge computing module in the edge computing subsystem includes an edge computing unit, an edge hub, a camera, a smart street light, and a backup battery. Each edge computing unit is connected to several edge hubs, each edge hub is connected to a camera, a smart street light, and a backup battery. The data of each edge hub is collected through the edge computing unit, and bidirectional data transmission can be performed between each edge hub.

[0006] As a preferred embodiment of the present invention, the camera in the edge computing module records the road traffic video at a preset time interval t, and obtains the number of pedestrians Xk and the number of vehicles Yk appearing in the road traffic video within the preset time based on motion analysis technology.

[0007] The difference between the number of pedestrians at each preset time and the number of pedestrians at the previous preset time is calculated to obtain the change in the number of pedestrians Xk, calculate the difference between the number of vehicles and the number of vehicles at the previous preset time every preset time to get the change in the number of vehicles Yk. When the number of pedestrians changes Xk and the change in the number of vehicles When the values ​​of Yk are all 0, the camera generates a static signal and sends it to the edge center; when there is a change in the number of pedestrians Xk or the change in the number of vehicles When the value of Yk is not 0, the camera generates an analysis signal and sends it to the edge center. Based on the image analysis technology, the camera obtains the image brightness Tk in the road traffic camera within the preset time, constructs an ellipse with the sum of the number of vehicles Yk and the number of pedestrians Xk as the major axis and the number of pedestrians Xk as the minor axis, and extracts the area of ​​the ellipse as the traffic volume parameter Sk, where k is the edge center number, k=1, 2,..., p, and p is the total number of cameras in the edge computing module. Record the time t, edge center number k, traffic volume parameter Sk and image brightness T and form a camera data vector (t, k, Sk, Tk). The smart street lamp in the edge computing module obtains the input power Pk of the smart street lamp at every preset time t, records the time t, edge center number k and input power P and forms a street lamp data vector (t, k, Pk). The backup battery in the edge computing module obtains the percentage c of the remaining power of the backup battery at every preset time t, and records the time t, edge center number k and the percentage c of the remaining power of the backup battery to form a battery data vector (t, k, c).

[0008] As a preferred embodiment of the present invention, the edge center constructs a distribution model of natural light intensity: , where t is time; f(t) is the natural light intensity; A is the preset influencing factor; is the preset scale factor, is the preset position factor. Draw the function graph of f(t). Obtain the light intensity f(t) in the distribution model of natural light intensity at every preset t. By formula Get the lighting demand index ,in , and is the preset influencing factor. The edge center is calculated by the formula Calculating the Electricity Demand Index ,in It is the rated input power of the smart street light.

[0009] As a preferred embodiment of the present invention, the transmission network topology of the edge hub and the edge computing unit, each edge hub is connected to the edge computing unit through a transmission line, and two adjacent edge hubs are connected through a transmission line. The three edge hubs are numbered 1, 2, and 3 respectively; the edge computing unit is numbered 0. The transmission line passing through the edge hub is recorded as the baseline; the transmission line not connected to the edge hub is recorded as the sub-line, and each baseline and sub-line is marked with the starting point and end point of the transmission line. At preset time intervals, each baseline and sub-line obtains its own bandwidth utilization percentage a is the starting number of the transmission line, and b is the end number of the transmission line. The edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines. The line with the lowest sum of bandwidth utilization percentage among the optional lines is calculated and recorded as the optimal line.

[0010] When the edge center receives the analysis signal, it starts the data transmission line and transmits the lighting demand index to the preset time. and power demand index The optimal line is sent to the edge computing unit and other edge hubs; when the edge hub receives the static signal, it stops looking for the optimal line data transmission line and stops sending the lighting demand index to the edge computing unit and other edge hubs. and power demand index .

[0011] As a preferred embodiment of the present invention, the edge computing unit receives the lighting demand index After the calculation and analysis, when the lighting demand index Greater than the preset lighting demand index threshold When the lighting demand index is Greater than lighting demand index threshold 2 , sends an amplification signal to edge hub k, and sends a high demand signal to all edge hubs. Less than the preset lighting demand index threshold When , a light-off signal is sent to edge hub k through the optimal line, and a low-demand signal is sent to all edge hubs through the optimal line.

[0012] As a preferred embodiment of the present invention, when the edge hub receives a light-on signal, the smart street light is turned on with a preset power of 1. When the edge hub receives a light-off signal, the smart street light is turned off. When the edge hub receives an amplified signal, the smart street light is turned on with a preset power of 2, which is greater than the preset power of 1. When the edge hub receives a high demand signal, the preset impact factor is increased. and Multiply by the preset weight factor ; When the edge hub receives a low demand signal, it will preset the impact factor and Divide by the preset weight factor .

[0013] As a preferred embodiment of the present invention, when the edge computing unit detects a power outage, the power demand index received is Perform calculation analysis. When the power demand index is less than the preset power demand index threshold When the power demand index is greater than or equal to the preset power demand index threshold, the power supply signal is sent to the edge hub k through the optimal line. When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. Powering smart street lights controlled by edge hubs.

[0014] As a preferred embodiment of the present invention, the regional computing module records the lighting demand index of all edge computing modules at a preset time t. and power demand index Each edge computing module has a number i; i = 1, 2, ..., m; each regional computing module has a number j; j = 1, 2, ..., n; n is the total number of regional computing modules, and the regional computing module will calculate the time t, edge computing module number i, regional computing module number j, edge hub number k, lighting demand index and power demand index The data vector (t, i, j, k, , ). The data vectors with the same regional computing module number i, edge computing module number j and edge hub number k are recorded as a monitoring group. Extract the time t and lighting demand index in each monitoring group and power demand index , generate two sets of data points (t, ) and (t, ). With time t as the horizontal axis and lighting demand index as the Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the lighting demand index changing over time. Extract the points larger than the straight line in the image of the lighting demand index changing over time. = The area of ​​the part is recorded as the lighting anomaly index E1, where is the preset lighting demand index threshold 2. When the lighting anomaly index E1 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate the lighting anomaly vector (E1, i, j, k,). Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the power demand index changing over time. Extract the points larger than the straight line in the image of the power demand index changing over time. = The area of ​​the part is recorded as the power supply abnormality parameter E2, where is the preset power demand index threshold. When the power supply abnormality parameter E2 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate a power supply abnormality vector (E2, i, j, k,).

[0015] The fault recording module records all lighting abnormality vectors (E1, i, j, k,) and power supply abnormality vectors (E2, i, j, k,), and records all lighting abnormality vectors as a lighting abnormality group; records all power supply abnormality vectors as a power supply abnormality group, and displays all vectors in the lighting abnormality group and the power supply abnormality group on the display terminal according to the grouping.

[0016] As a preferred embodiment of the present invention, a networking communication method for a smart street lamp includes the following steps: Step 1: Get monitoring data: The camera in the edge computing module records the road traffic video at a preset time interval t, and obtains the number of pedestrians Xk and the number of vehicles Yk appearing in the road traffic video within the preset time based on motion analysis technology. The camera obtains the image brightness Tk in the road traffic video within the preset time based on image analysis technology; the backup battery in the edge computing module obtains the percentage c of the remaining power of the backup battery at a preset time interval t; the edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines; every preset time, each baseline and sub-line that maintains data transmission between the edge hub and the edge computing unit obtains its own bandwidth utilization percentage ; Step 2: Preliminary data analysis: The edge computing module calculates the difference between the number of pedestrians and the number of pedestrians at the previous preset time every preset time to obtain the change in the number of pedestrians. Xk, calculate the difference between the number of vehicles and the number of vehicles at the previous preset time every preset time to get the change in the number of vehicles Yk; when the number of pedestrians changes Xk and the change in the number of vehicles When the values ​​of Yk are all 0, the camera generates a static signal and sends it to the edge center; when there is a change in the number of pedestrians Xk or the change in the number of vehicles When the value of Yk is not 0, the camera generates an analysis signal and sends it to the edge center; an ellipse is constructed with the sum of the number of vehicles Yk and the number of pedestrians Xk as the major axis and the number of pedestrians Xk as the minor axis, and the area of ​​the ellipse is extracted and recorded as the traffic volume parameter Sk, where k is the edge center number, k=1, 2,..., p, and p is the total number of cameras in the edge computing module; the time t, edge center number k, traffic volume parameter Sk and image brightness T are recorded to form a camera data vector (t, k, Sk, Tk); the smart street lamp in the edge computing module obtains the input power Pk of the smart street lamp at every preset time t, records the time t, edge center number k and input power P to form a street lamp data vector (t, k, Pk); the time t, edge center number k and the percentage of power remaining in the backup battery c are recorded to form a battery data vector (t, k, c); the edge center constructs a distribution model of natural light intensity: , where t is time; f(t) is the natural light intensity; A is the preset influencing factor; is the preset scale factor, is the preset position factor; draw the function graph of f(t); obtain the light intensity f(t) in the natural light intensity distribution model at every preset t; through the formula Get the lighting demand index ,in , and is the preset influencing factor; the edge center is calculated by the formula Calculating the Electricity Demand Index ,in is the rated input power of the smart street light; Step 3: Find the optimal route: In the transmission network of edge hubs and edge computing units, each edge hub is connected to the edge computing unit through a transmission line, and two adjacent edge hubs are connected through a transmission line; the three edge hubs are numbered 1, 2, and 3 respectively; the edge computing unit is numbered 0; the transmission line through the edge hub is recorded as the baseline; the edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines, and the formula is used Calculate the line with the lowest sum of bandwidth utilization percentages among the selectable lines; Step 4: Data transmission: When the edge center receives the analysis signal, it starts the data transmission line and transmits the lighting demand index to the preset time. and power demand index Send it to the edge computing unit and other edge hubs through the optimal route; when the edge hub receives the static signal, it stops looking for the optimal route and stops sending the lighting demand index to the edge computing unit and other edge hubs and power demand index ; Step 5: Secondary data analysis and execution of lighting demand index: The edge computing unit receives the lighting demand index After the calculation and analysis, when the lighting demand index Greater than the preset lighting demand index threshold When the lighting demand index is Greater than lighting demand index threshold 2 , sends an amplification signal to edge hub k, and sends a high demand signal to all edge hubs; when the lighting demand index Less than the preset lighting demand index threshold When the edge hub receives the light-on signal, it turns on the smart street light with the preset power of 1; when the edge hub receives the light-off signal, it turns off the smart street light; when the edge hub receives the amplified signal, it turns on the smart street light with the preset power of 2, which is greater than the preset power of 1; when the edge hub receives the high-demand signal, it turns on the preset impact factor of 1. and Multiply by the preset weight factor ; When the edge hub receives a low demand signal, it will preset the impact factor and Divide by the preset weight factor ; Step 6: Secondary data analysis and execution of power demand index: When the edge computing unit detects a power outage, it receives the power demand index Perform calculation analysis. When the power demand index is less than the preset power demand index threshold When the power demand index is greater than or equal to the preset power demand index threshold, the power supply signal is sent to the edge hub k through the optimal line; when the power demand index is greater than or equal to the preset power demand index threshold When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k; when the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. Power supply for smart street lights controlled by edge hubs; Step 7: Data summary and fault analysis: The regional computing module records the lighting demand index of all edge computing modules at a preset time t. and power demand index ; Each edge computing module has a number i; i = 1, 2, ..., m; Each regional computing module has a number j; j = 1, 2, ..., n; n is the total number of regional computing modules, and the regional computing module will take time t, edge computing module number i, regional computing module number j, edge hub number k, lighting demand index and power demand index The data vector (t, i, j, k, , ); record the data vectors with the same regional computing module number i, edge computing module number j and edge hub number k as a monitoring group; extract the time t and lighting demand index in each monitoring group and power demand index , generate two sets of data points (t, ) and (t, ); with time t as the horizontal axis and lighting demand index as the Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the lighting demand index changing over time; extract the points larger than the straight line in the image of the lighting demand index changing over time = The area of ​​the part is recorded as the lighting anomaly index E1, where is the preset lighting demand index threshold 2; when the lighting anomaly index E1 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate the lighting anomaly vector (E1, i, j, k,); with time t as the horizontal axis and power supply demand index Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the power demand index changing with time; extract the points larger than the straight line in the image of the power demand index changing with time = The area of ​​the part is recorded as the power supply abnormality parameter E2, where is the preset power supply demand index threshold; when the power supply anomaly parameter E2 is greater than the preset threshold, the regional computing module number i, the edge computing module number j and the edge hub number k of the monitoring group are extracted to generate a power supply anomaly vector (E2, i, j, k,); the fault recording module records all lighting anomaly vectors (E1, i, j, k,) and power supply anomaly vectors (E2, i, j, k,), and records all lighting anomaly vectors as a lighting anomaly group; all power supply anomaly vectors are recorded as a power supply anomaly group, and all vectors in the lighting anomaly group and the power supply anomaly group are displayed on the display terminal according to the group.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention optimizes the interconnection and intercommunication problems between street lamps by solving the optimal route, ensuring that data transmission can be completed through other transmission paths when the bandwidth burden of a single transmission path is high, so that the entire communication network can better adapt to external disturbances and internal changes, improve the reliability of data transmission of the entire system, optimize the topological structure of the smart street lamp communication network, and improve the robustness of the entire system; 2. The present invention improves the remote control and troubleshooting capabilities of smart street lamp equipment through data aggregation and fault analysis, accurately analyzes the cause of the fault, accurately locates the faulty equipment number, and implements real-time monitoring of fault risks; 3. The present invention uses a camera to analyze changes in road conditions, maintains the lighting power of the smart street lamp unchanged when the number of pedestrians and vehicles remains unchanged, prevents the captured monitoring data from entering the transmission path of the edge hub and edge computing unit, reduces unnecessary data transmission burden, and ensures that there are enough path options during data transmission; prevents the captured monitoring data from entering unnecessary calculation processes when the number of pedestrians and vehicles remains unchanged, reduces the waste of computing power of the edge computing module, and ensures that the entire system has sufficient computing power redundancy when road conditions change; 4. The present invention adjusts the influencing factors involved in the calculation of the lighting demand index. When a single smart street lamp detects that the road conditions are increasing rapidly, the sensitivity of other smart street lamps to the number of pedestrians, the number of vehicles and the brightness changes is amplified, thereby improving the correlation of multiple smart street lamps in the same area; making all smart street lamps a whole with common perception and response, thereby improving the synchronization of smart street lamp power management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0019] Figure 1 is a system block diagram of the present invention; Figure 2 This is a schematic diagram of the topological structure of the edge computing module of the present invention; Figure 3 It is a schematic diagram of the distribution model function of the natural light intensity of the present invention; Figure 4 This is a schematic diagram of the distributed communication network topology of the edge computing module of the present invention; Figure 5 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] See also Figure 1 As shown, a networking communication system for smart street lamps includes an edge computing module, a regional computing module and a fault recording module. The overall communication module is connected to n regional computing modules, and each regional computing module is connected to several edge computing modules.

[0022] See also Figure 2 As shown, each edge computing module in the edge computing subsystem includes an edge computing unit, an edge hub, a camera, a smart street light, and a backup battery. Each edge computing unit is connected to several edge hubs, each edge hub is connected to a camera, a smart street light, and a backup battery. The data of each edge hub is collected through the edge computing unit, and bidirectional data transmission can be performed between each edge hub.

[0023] The camera in the edge computing module records the road traffic video at a preset time interval t, and obtains the number of pedestrians Xk and vehicles Yk appearing in the road traffic video within the preset time based on motion analysis technology.

[0024] The difference between the number of pedestrians at each preset time and the number of pedestrians at the previous preset time is calculated to obtain the change in the number of pedestrians Xk, calculate the difference between the number of vehicles and the number of vehicles at the previous preset time every preset time to get the change in the number of vehicles Yk. When the number of pedestrians changes Xk and the change in the number of vehicles When the values ​​of Yk are all 0, the camera generates a static signal and sends it to the edge center; when there is a change in the number of pedestrians Xk or the change in the number of vehicles When the value of Yk is not 0, the camera generates an analysis signal and sends it to the edge center. Based on the image analysis technology, the camera obtains the image brightness Tk in the road traffic camera within the preset time, constructs an ellipse with the sum of the number of vehicles Yk and the number of pedestrians Xk as the major axis and the number of pedestrians Xk as the minor axis, and extracts the area of ​​the ellipse as the traffic volume parameter Sk, where k is the edge center number, k=1, 2,..., p, and p is the total number of cameras in the edge computing module. Record the time t, edge center number k, traffic volume parameter Sk and image brightness T and form a camera data vector (t, k, Sk, Tk). The smart street lamp in the edge computing module obtains the input power Pk of the smart street lamp at every preset time t, records the time t, edge center number k and input power P and forms a street lamp data vector (t, k, Pk). The backup battery in the edge computing module obtains the percentage c of the remaining power of the backup battery at every preset time t, and records the time t, edge center number k and the percentage c of the remaining power of the backup battery to form a battery data vector (t, k, c).

[0025] See also Figure 3 As shown, the edge center constructs a distribution model of natural light intensity: , where t is time; f(t) is the natural light intensity; A is the preset influencing factor; is the preset scale factor, is the preset position factor. Draw the function graph of f(t). Obtain the light intensity f(t) in the distribution model of natural light intensity at every preset t. By formula Get the lighting demand index ,in , and is the preset influencing factor. The edge center is calculated by the formula Calculating the Electricity Demand Index ,in It is the rated input power of the smart street light.

[0026] See also Figure 4As shown in the figure, the transmission network topology of the edge hub and edge computing unit, each edge hub is connected to the edge computing unit through a transmission line, and two adjacent edge hubs are connected through a transmission line. The three edge hubs are numbered 1, 2, and 3 respectively; the edge computing unit is numbered 0. The transmission line passing through the edge hub is recorded as the baseline; the transmission line not connected to the edge hub is recorded as the sub-line, and each baseline and sub-line is marked with the starting point and end point of the transmission line. At preset time intervals, each baseline and sub-line obtains its own bandwidth utilization percentage a is the starting number of the transmission line, and b is the end number of the transmission line. The edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines. Calculate the line with the lowest sum of bandwidth utilization percentages among the optional lines. For example, with edge hub 1 as the starting point and edge computing unit 0 as the end point, there are five optional lines, namely: Line 1: baseline 0-1; Line 2: secondary line 1-2→baseline 2-0; Line 3: secondary line 1-2→secondary line 2-3→baseline 3-0; Line 4: secondary line 1-3→baseline 3-0; Line 5: secondary line 1-3→secondary line 3-2→baseline 2-0. The bandwidth utilization percentage of each transmission line is They are: =80%; =20%; =20%; =10%; =20%; =20%.

[0027] The sum of the bandwidth utilization percentages of each route is calculated as follows: Route 1: 80%; Route 2: 30%; Route 3: 50%; Route 4: 40%; Route 5: 60%. The optimal route is Route 2.

[0028] When the edge center receives the analysis signal, it starts the data transmission line and transmits the lighting demand index to the preset time. and power demand index Send it to the edge computing unit and other edge hubs through the optimal route; when the edge hub receives the static signal, it stops looking for the optimal route and stops sending the lighting demand index to the edge computing unit and other edge hubs and power demand index .

[0029] The edge computing unit receives the lighting demand index After the calculation and analysis, when the lighting demand index Greater than the preset lighting demand index threshold When the lighting demand index is Greater than lighting demand index threshold 2 , sends an amplification signal to edge hub k, and sends a high demand signal to all edge hubs. Less than the preset lighting demand index threshold When , a light-off signal is sent to edge hub k through the optimal line, and a low-demand signal is sent to all edge hubs through the optimal line.

[0030] When the edge hub receives a light-on signal, the smart street light is turned on with a preset power of 1. When the edge hub receives a light-off signal, the smart street light is turned off. When the edge hub receives an amplified signal, the smart street light is turned on with a preset power of 2, which is greater than the preset power of 1. When the edge hub receives a high demand signal, the preset impact factor is increased. and Multiply by the preset weight factor ; When the edge hub receives a low demand signal, it will preset the impact factor and Divide by the preset weight factor . Default impact factor and Lighting Demand Index The calculation formula The coefficients in Control the impact of the number of pedestrians and vehicles on the lighting demand index in road traffic cameras, Control the impact of image brightness in road traffic photography on the lighting demand index. and The increase means an increase in the lighting demand index of all smart street lamps controlled by the edge computing unit, thereby increasing the sensitivity of smart street lamp power to the number of pedestrians, vehicles and brightness.

[0031] When the edge computing unit detects a power outage, it receives the power demand index Perform calculation analysis. When the power demand index is less than the preset power demand index threshold When the power demand index is greater than or equal to the preset power demand index threshold, the power supply signal is sent to the edge hub k through the optimal line. When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. Powering smart street lights controlled by edge hubs.

[0032] The regional computing module records the lighting demand index of all edge computing modules at a preset time t. and power demand index Each edge computing module has a number i; i = 1, 2, ..., m; each regional computing module has a number j; j = 1, 2, ..., n; n is the total number of regional computing modules, and the regional computing module will calculate the time t, edge computing module number i, regional computing module number j, edge hub number k, lighting demand index and power demand index The data vector (t, i, j, k, , ). The data vectors with the same regional computing module number i, edge computing module number j and edge hub number k are recorded as a monitoring group. Extract the time t and lighting demand index in each monitoring group and power demand index , generate two sets of data points (t, ) and (t, ). With time t as the horizontal axis and lighting demand index as the Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the lighting demand index changing over time. Extract the points larger than the straight line in the image of the lighting demand index changing over time. = The area of ​​the part is recorded as the lighting anomaly index E1, where is the preset lighting demand index threshold 2. When the lighting anomaly index E1 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate the lighting anomaly vector (E1, i, j, k,). Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the power demand index changing over time. Extract the points larger than the straight line in the image of the power demand index changing over time. = The area of ​​the part is recorded as the power supply abnormality parameter E2, where is the preset power demand index threshold. When the power supply abnormality parameter E2 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate a power supply abnormality vector (E2, i, j, k,).

[0033] The fault recording module records all lighting abnormality vectors (E1, i, j, k,) and power supply abnormality vectors (E2, i, j, k,), and records all lighting abnormality vectors as a lighting abnormality group; records all power supply abnormality vectors as a power supply abnormality group, and displays all vectors in the lighting abnormality group and the power supply abnormality group on the display terminal according to the grouping.

[0034] See also Figure 5 As shown, a networking communication method for smart street lamps includes the following steps: Step 1: Get monitoring data: The camera in the edge computing module records the road traffic video at a preset time interval t, and obtains the number of pedestrians Xk and the number of vehicles Yk appearing in the road traffic video within the preset time based on motion analysis technology. The camera obtains the image brightness Tk in the road traffic video within the preset time based on image analysis technology; the backup battery in the edge computing module obtains the percentage c of the remaining power of the backup battery at a preset time interval t; the edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines; every preset time, each baseline and sub-line that maintains data transmission between the edge hub and the edge computing unit obtains its own bandwidth utilization percentage ; Step 2: Preliminary data analysis: The edge computing module calculates the difference between the number of pedestrians and the number of pedestrians at the previous preset time every preset time to obtain the change in the number of pedestrians. Xk, calculate the difference between the number of vehicles and the number of vehicles at the previous preset time every preset time to get the change in the number of vehicles Yk; when the number of pedestrians changes Xk and the change in the number of vehicles When the values ​​of Yk are all 0, the camera generates a static signal and sends it to the edge center; when there is a change in the number of pedestrians Xk or the change in the number of vehicles When the value of Yk is not 0, the camera generates an analysis signal and sends it to the edge center; an ellipse is constructed with the sum of the number of vehicles Yk and the number of pedestrians Xk as the major axis and the number of pedestrians Xk as the minor axis, and the area of ​​the ellipse is extracted and recorded as the traffic volume parameter Sk, where k is the edge center number, k=1, 2,..., p, and p is the total number of cameras in the edge computing module; the time t, edge center number k, traffic volume parameter Sk and image brightness T are recorded to form a camera data vector (t, k, Sk, Tk); the smart street lamp in the edge computing module obtains the input power Pk of the smart street lamp at every preset time t, records the time t, edge center number k and input power P to form a street lamp data vector (t, k, Pk); the time t, edge center number k and the percentage of power remaining in the backup battery c are recorded to form a battery data vector (t, k, c); the edge center constructs a distribution model of natural light intensity: , where t is time; f(t) is the natural light intensity; A is the preset influencing factor; is the preset scale factor, is the preset position factor; draw the function graph of f(t); obtain the light intensity f(t) in the natural light intensity distribution model at every preset t; through the formula Get the lighting demand index ,in , and is the preset influencing factor; the edge center is calculated by the formula Calculating the Electricity Demand Index ,in is the rated input power of the smart street light; Step 3: Find the optimal route: In the transmission network of edge hubs and edge computing units, each edge hub is connected to the edge computing unit through a transmission line, and two adjacent edge hubs are connected through a transmission line; the three edge hubs are numbered 1, 2, and 3 respectively; the edge computing unit is numbered 0; the transmission line through the edge hub is recorded as the baseline; the edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines, and the formula is used Calculate the line with the lowest sum of bandwidth utilization percentages among the selectable lines; Step 4: Data transmission: When the edge center receives the analysis signal, it starts the data transmission line and transmits the lighting demand index to the preset time. and power demand index The optimal line is sent to the edge computing unit and other edge hubs; when the edge hub receives the static signal, it stops looking for the optimal line data transmission line and stops sending the lighting demand index to the edge computing unit and other edge hubs. and power demand index ; Step 5: Secondary data analysis of lighting demand index: The edge computing unit receives the lighting demand index After the calculation and analysis, when the lighting demand index Greater than the preset lighting demand index threshold When the lighting demand index is Greater than lighting demand index threshold 2 , sends an amplification signal to edge hub k, and sends a high demand signal to all edge hubs; when the lighting demand index Less than the preset lighting demand index threshold When the edge hub receives the light-on signal, it turns on the smart street light with the preset power of 1; when the edge hub receives the light-off signal, it turns off the smart street light; when the edge hub receives the amplified signal, it turns on the smart street light with the preset power of 2, which is greater than the preset power of 1; when the edge hub receives the high-demand signal, it turns on the preset impact factor of 1. and Multiply by the preset weight factor ; When the edge hub receives a low demand signal, it will preset the impact factor and Divide by the preset weight factor ; Step 6: Secondary data analysis and execution of power demand index: When the edge computing unit detects a power outage, it receives the power demand index Perform calculation analysis. When the power demand index is less than the preset power demand index threshold When the power demand index is greater than or equal to the preset power demand index threshold, the power supply signal is sent to the edge hub k through the optimal line; when the power demand index is greater than or equal to the preset power demand index threshold When the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k; when the edge hub k receives the self-powered power signal, it turns on the backup battery controlled by the edge hub k to power the smart street lamp controlled by the edge hub k. Power supply for smart street lights controlled by edge hubs; Step 7: Data summary, fault analysis and execution: The regional computing module records the lighting demand index of all edge computing modules at a preset time t. and power demand index ; Each edge computing module has a number i; i = 1, 2, ..., m; Each regional computing module has a number j; j = 1, 2, ..., n; n is the total number of regional computing modules, and the regional computing module will take time t, edge computing module number i, regional computing module number j, edge hub number k, lighting demand index and power demand index The data vector (t, i, j, k, , ); record the data vectors with the same regional computing module number i, edge computing module number j and edge hub number k as a monitoring group; extract the time t and lighting demand index in each monitoring group and power demand index , generate two sets of data points (t, ) and (t, ); with time t as the horizontal axis and lighting demand index as the Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the lighting demand index changing over time; extract the points larger than the straight line in the image of the lighting demand index changing over time = The area of ​​the part is recorded as the lighting anomaly index E1, where is the preset lighting demand index threshold 2; when the lighting anomaly index E1 is greater than the preset threshold, the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group are extracted to generate the lighting anomaly vector (E1, i, j, k,); with time t as the horizontal axis and power supply demand index Establish a two-dimensional rectangular coordinate system for the vertical axis and set all points (t, ) fill in the coordinate system, and then use a smooth curve to fit all the points to generate an image of the power demand index changing with time; extract the points larger than the straight line in the image of the power demand index changing with time = The area of ​​the part is recorded as the power supply abnormality parameter E2, where is the preset power supply demand index threshold; when the power supply anomaly parameter E2 is greater than the preset threshold, the regional computing module number i, the edge computing module number j and the edge hub number k of the monitoring group are extracted to generate a power supply anomaly vector (E2, i, j, k,); the fault recording module records all lighting anomaly vectors (E1, i, j, k,) and power supply anomaly vectors (E2, i, j, k,), and records all lighting anomaly vectors as a lighting anomaly group; all power supply anomaly vectors are recorded as a power supply anomaly group, and all vectors in the lighting anomaly group and the power supply anomaly group are displayed on the display terminal according to the group.

[0035] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms "a", "an", and "the" are intended to include plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations; The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A networking communication system for smart street lamps, including several edge computing modules, characterized in that: Each edge computing module includes an edge computing unit, an edge hub, a camera, a smart street light, and a backup battery; each edge computing unit is connected to several edge hubs, each edge hub is connected to a camera, a smart street light, and a backup battery, the data of each edge hub is collected through the edge computing unit, and bidirectional data transmission can be carried out between each edge hub; Data collection and preliminary data analysis are performed on the camera and the backup battery at preset intervals to obtain a lighting demand index and a power supply demand index; Calculate the difference between the number of pedestrians and the number of pedestrians at the last preset time at every preset time to obtain the change in the number of pedestrians, and calculate the difference between the number of vehicles and the number of vehicles at the last preset time at every preset time to obtain the change in the number of vehicles; determine whether to generate an analysis signal and a stationary signal according to the values ​​of the change in the number of pedestrians and the change in the number of vehicles; The traffic volume parameter Sk is obtained by calculating the number of vehicles and pedestrians, and the time, edge hub number, traffic volume parameter and image brightness are recorded to form a camera data vector; the smart street lamp in the edge computing module obtains the input power of the smart street lamp at preset time intervals, and records the time, edge hub number and input power to form a street lamp data vector; the time, edge hub number and the percentage of power remaining in the backup battery are recorded to form a battery data vector; Construct a distribution model of natural light intensity, and obtain the light intensity f(t) in the distribution model of natural light intensity every preset time t; obtain the lighting demand index through calculation, and there are several preset influencing factors in the calculation process. The influencing factors are positively correlated with the lighting demand index, and the values ​​of the influencing factors can be dynamically adjusted according to the secondary calculation analysis results of the lighting demand index; perform secondary calculation analysis on the lighting demand index; obtain the power supply demand index through calculation, and perform secondary calculation analysis on the power supply demand index; In the transmission network topology of edge hubs and edge computing units, each edge hub is connected to an edge computing unit through a transmission line, and two adjacent edge hubs are connected through a transmission line; each edge hub is numbered 1, 2, ..., k; k is the total number of edge hubs; the edge computing unit is numbered 0; the transmission line passing through the edge hub is recorded as a baseline; the transmission line not connected to the edge hub is recorded as a sub-line, and each baseline and sub-line is marked with the starting point and end point of the transmission line; At preset intervals, each baseline and secondary line obtains its own bandwidth utilization percentage; The edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines. The line with the lowest sum of bandwidth utilization percentage among the optional lines is obtained through formula calculation, which is recorded as the optimal line. When the edge hub receives the analysis signal, it starts the data transmission line and sends the lighting demand index and power demand index to the edge computing unit and other edge hubs through the optimal line at preset intervals; When the edge hub receives the static signal, it stops looking for the optimal data transmission line and stops sending the lighting demand index and power demand index to the edge computing unit and other edge hubs; the edge computing unit performs secondary operation analysis on the lighting demand index after receiving it; when a power outage is detected, a secondary operation analysis is performed on the received power demand index.

2. A networking communication system for smart street lamps according to claim 1, characterized in that: It also includes a regional calculation module and a fault recording module; The regional computing module records the lighting demand index and power demand index of all edge computing modules at preset intervals; each edge computing module has a number i and each regional computing module has a number j, generating a data vector (t, i, j, k, , ); record the data vectors with the same regional computing module number, edge computing module number and edge hub number as a monitoring group; generate two sets of data points in the same monitoring group (t, ) and (t, ); generate an image of the lighting demand index changing over time; extract the image of the lighting demand index changing over time that is larger than the straight line =The area of ​​the second part of the preset lighting demand index threshold value and recorded as the lighting abnormality index E1; When the lighting anomaly index is greater than the preset threshold, extract the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group to generate a lighting anomaly vector (E1, i, j, k); generate an image of the power demand index changing over time; extract the image of the power demand index changing over time that is greater than the straight line =The area of ​​the preset power demand index threshold part is recorded as the power supply abnormality parameter E2; when the power supply abnormality parameter is greater than the preset threshold, the regional computing module number, edge computing module number and edge hub number of the monitoring group are extracted to generate a power supply abnormality vector (E2, i, j, k); The fault recording module records all lighting abnormality vectors (E1, i, j, k) and power supply abnormality vectors (E2, i, j, k) and records all lighting abnormality vectors as a lighting abnormality group; records all power supply abnormality vectors as a power supply abnormality group, and displays all vectors in the lighting abnormality group and the power supply abnormality group on the display terminal according to the grouping.

3. A networking communication system for smart street lamps according to claim 1, characterized in that: The specific process of data collection is as follows: The road traffic video is recorded at preset time intervals, and the number of pedestrians and vehicles appearing in the road traffic video within the preset time is obtained based on motion analysis technology; the camera obtains the image brightness in the road traffic video within the preset time based on image analysis technology, and the backup battery in the edge computing module obtains the percentage of power remaining of the backup battery at preset time intervals.

4. A networking communication system for smart street lamps according to claim 1, characterized in that: The secondary operation analysis of the lighting demand index is as follows: When the lighting demand index is greater than the preset lighting demand index threshold value one, a light-on signal is sent to the edge hub to which the lighting demand index belongs through the preferred path; when the lighting demand index is greater than the lighting demand index threshold value two, an amplification signal is sent to the edge hub to which the lighting demand index belongs, and a high demand signal is sent to all edge hubs; when the lighting demand index is less than the preset lighting demand index threshold value one, a light-off signal is sent to the edge hub to which the lighting demand index belongs through the preferred path, and a low demand signal is sent to all edge hubs through the preferred path.

5. A networking communication system for smart street lamps according to claim 4, characterized in that: The secondary operation analysis of the power supply demand index is as follows: When the power demand index is less than the preset power demand index threshold, a self-power supply signal is sent to the edge hub k through the preferred path; when the power demand index is greater than or equal to the preset power demand index threshold, a different power supply signal is sent to all edge hubs through the preferred path.

6. A networking communication system for smart street lamps according to any one of claims 4 or 5, characterized in that: The control operations performed according to the secondary operation analysis results are as follows: When the edge hub receives a light-on signal, the smart street light is turned on with a preset power of one; when the edge hub receives a light-off signal, the smart street light is turned off; when the edge hub receives an amplified signal, the smart street light is turned on with a preset power of two, and the preset power of two is greater than the preset power of one; When the edge hub receives a high demand signal, it amplifies the preset impact factor and multiplies the preset impact factor by the preset weight factor; When the edge hub receives the low demand signal, it reduces the preset impact factor by dividing the preset impact factor by the preset weight factor; When the edge hub receives a power supply signal from the power source, the backup battery controlled by the edge hub is turned on to power the smart street light controlled by the edge hub; When the edge center receives a power supply signal from an alien power source, the backup battery controlled by the edge center is turned on to power the smart street light controlled by the edge center with the highest power demand index.

7. A networking communication method for smart street lamps, characterized in that: The specific steps are: Step 1: Get monitoring data: The camera obtains the number of pedestrians, the number of vehicles and the image brightness at preset intervals; the backup battery obtains the percentage of remaining power of the backup battery at preset intervals; the edge computing module obtains all transmission paths starting from itself and ending at the edge computing unit, which are recorded as optional lines; each data transmission line between the edge hub and the edge computing unit obtains its own bandwidth utilization percentage; Step 2: Preliminary data analysis: The change in the number of pedestrians and the change in the number of vehicles are obtained through calculation; whether a stationary signal and an analysis signal are generated is determined by the values ​​of the change in the number of pedestrians and the change in the number of vehicles; the traffic volume parameters are obtained through calculations on the number of vehicles and the number of pedestrians; a camera data vector (t, k, Sk, Tk), a street light data vector (t, k, Pk) and a battery data vector (t, k, c) are generated; a distribution model of natural light intensity is constructed, and the light intensity is obtained in the distribution model of natural light intensity at every preset t interval; a lighting demand index is obtained through calculation, and there are several preset influencing factors in the calculation process; a power supply demand index is obtained through calculation; Step 3: Find the optimal route: The edge computing module obtains all transmission paths starting from itself and ending at edge computing unit 0, which are recorded as optional lines. The line with the lowest sum of bandwidth utilization percentage among the optional lines is calculated and recorded as the optimal line. Step 4: Data transmission: When the edge hub receives the analysis signal, it starts the data transmission line and sends the lighting demand index and power demand index to the edge computing unit and other edge hubs through the optimal line at preset intervals; When the edge hub receives the stationary signal, it stops searching for the optimal route and stops sending the lighting demand index and the power demand index to the edge computing unit and other edge hubs; Step 5: Secondary data analysis and execution of lighting demand index: When the lighting demand index is greater than the preset lighting demand index threshold value one, a light-on signal is sent to the edge hub to which the lighting demand index belongs through the optimal line; when the lighting demand index is greater than the lighting demand index threshold value two, an amplification signal is sent to the edge hub to which the lighting demand index belongs, and a high demand signal is sent to all edge hubs; when the lighting demand index is less than the preset lighting demand index threshold value one, a light-off signal is sent to the edge hub to which the lighting demand index belongs through the optimal line, and a low demand signal is sent to all edge hubs through the optimal line; when the edge hub receives the light-on signal, the smart street light is turned on with the preset power one; when the edge hub receives the light-off signal, the smart street light is turned off; when the edge hub receives the amplification signal, the smart street light is turned on with the preset power two, and the preset power two is greater than the preset power one; when the edge hub receives the high demand signal, the preset impact factor is amplified and multiplied by the preset weight factor; when the edge hub receives the low demand signal, the preset impact factor is reduced and divided by the preset weight factor; Step 6: Secondary data analysis and execution of power demand index: When the edge computing unit detects a power outage, it performs calculations and analysis on the received power demand index. When the power demand index is less than the preset power demand index threshold, it sends a self-power supply signal to the edge hub to which the power demand index belongs through the optimal line; when the power demand index is greater than or equal to the preset power demand index threshold, it sends a different power supply signal to all edge hubs through the optimal line; when the edge hub receives the self-power supply signal, it turns on the backup battery controlled by the edge hub to power the smart street lights controlled by the edge hub; when the edge hub receives the different power supply signal, it turns on the backup battery controlled by the edge hub to power the smart street lights controlled by the edge hub with the highest power demand index; Step 7: Data summary and fault analysis: The regional computing module records the lighting demand index and power demand index of all edge computing modules at preset time intervals; each edge computing module has a number i and each regional computing module has a number j. The regional computing module records the time t, edge computing module number i, regional computing module number j, edge hub number k, lighting demand index, and power supply demand index. and power demand index The data vector (t, i, j, k, , ); record the data vectors with the same regional computing module number, edge computing module number and edge hub number as a monitoring group; generate two sets of data points in the same monitoring group (t, ) and (t, ); generate an image of the lighting demand index changing over time; extract the image of the lighting demand index changing over time that is larger than the straight line =The area of ​​the second part of the preset lighting demand index threshold value and recorded as the lighting abnormality index E1; When the lighting anomaly index is greater than the preset threshold, extract the regional computing module number i, edge computing module number j and edge hub number k of the monitoring group to generate a lighting anomaly vector (E1, i, j, k); generate an image of the power demand index changing over time; extract the image of the power demand index changing over time that is greater than the straight line =The area of ​​the preset power demand index threshold part is recorded as the power supply abnormality parameter E2; when the power supply abnormality parameter is greater than the preset threshold, the regional computing module number, edge computing module number and edge hub number of the monitoring group are extracted to generate a power supply abnormality vector (E2, i, j, k); The fault recording module records all lighting abnormality vectors (E1, i, j, k) and power supply abnormality vectors (E2, i, j, k) and records all lighting abnormality vectors as a lighting abnormality group; records all power supply abnormality vectors as a power supply abnormality group, and displays all vectors in the lighting abnormality group and the power supply abnormality group on the display terminal according to the grouping.

Images