A remote online monitoring and control management system for smart street lighting

Abstract

The present invention provides a remote online monitoring, control and management system for intelligent lighting of street lamps, comprising: an initial generation module for determining an initial lighting plan based on illumination data and traffic data of a target street lamp location; a monitoring and control module for monitoring real-time traffic data within the illumination range of the target street lamp, and controlling the actual illumination data of the target street lamp in real time based on the real-time traffic data and the initial lighting plan; a power supply management module for performing power supply scheduling management on a backup power supply based on the actual illumination data of the target street lamp in a single day and the output power of a solar battery, and obtaining a power supply scheduling management result; a module for generating an initial lighting plan based on historical illumination data and historical traffic data of the street lamp location, and controlling the illumination data of the street lamp based on the initial lighting plan based on the traffic data obtained in real time, thereby realizing the functions of online monitoring, control and power supply management of the street lamp based on illumination data and traffic flow data.

Description

Technical Field

[0001] The present invention relates to the field of smart lighting technology, and in particular to a remote online monitoring, control and management system for smart street lighting. Background Art

[0002] At present, smart street lights are one of the mainstream directions of future urban infrastructure construction. Existing smart street lights have achieved remote communication monitoring by adding 5G communication modules and various sensor modules to the street lights, which greatly enriches the functions and intelligence of the street lights.

[0003] However, although existing smart street lights have achieved remote monitoring and control, they are mostly controlled through remote manual input of data. They are unable to perform real-time intelligent analysis based on local traffic conditions, natural lighting conditions, and installation conditions to determine more scientific and reasonable lighting values ​​and power supply plans, which in turn leads to increased energy consumption and light overflow.

[0004] Therefore, the present invention proposes a remote online monitoring, control and management system for intelligent street lighting. Summary of the Invention

[0005] The present invention provides a remote online monitoring, control and management system for intelligent lighting of street lamps, which is used to generate an initial lighting plan based on historical lighting data and historical traffic data of the location of the street lamps, and to control the lighting data of the street lamps on the basis of the initial lighting plan based on the real-time traffic data. This realizes the functions of online monitoring and control of street lamps and power supply management based on lighting data and traffic flow data of the location of the street lamps, saves electricity and reduces the phenomenon of light overflow.

[0006] The present invention provides a remote online monitoring, control and management system for smart street lighting, comprising:

[0007] An initial generation module is used to determine an initial lighting plan based on the lighting data and traffic data of the target street lamp location;

[0008] A monitoring and control module is used to monitor real-time traffic data within the illumination range of the target street lamp and to control the actual lighting data of the target street lamp in real time based on the real-time traffic data and the initial lighting plan;

[0009] The power supply management module is used to perform power supply scheduling management on the backup power supply based on the actual lighting data of the target street lamp in a single day and the output power of the solar battery, and obtain the power supply scheduling management results.

[0010] Preferably, the initial generation module includes:

[0011] A first acquisition unit is configured to obtain a plurality of single-day illumination data of a location of a target street lamp within an analysis period as illumination data;

[0012] The second acquisition unit is configured to acquire a plurality of single-day traffic flow data of the location of the target street lamp based on a plurality of single-day traffic monitoring videos of the location of the target street lamp within an analysis period as traffic flow data;

[0013] The plan generation unit is used to generate an initial lighting plan for the target street lamp based on the lighting data and traffic data.

[0014] Preferably, the plan generating unit includes:

[0015] an illumination calculation subunit, configured to determine average daily illumination change data based on a plurality of daily illumination data in the illumination data, calculate a first brightness value at a corresponding moment based on the illumination value at a corresponding moment in the average daily illumination change data and a first conversion method, determine average daily flow change data based on a plurality of daily flow data in the flow data, calculate a second brightness value at a corresponding moment based on the flow value at a corresponding moment in the average daily flow change data and a second conversion method;

[0016] The plan generating subunit is configured to calculate a planned brightness value at a corresponding moment based on the first brightness value and the second brightness value, and to generate an initial lighting plan for the target street lamp based on the planned brightness values ​​at all moments in a single day.

[0017] Preferably, the monitoring and control module includes:

[0018] Traffic analysis unit, used to jointly analyze the real-time traffic monitoring videos within the illumination range of all target street lamps based on the installation locations of all target street lamps to obtain real-time traffic data;

[0019] The lighting control unit is used to control the actual lighting data of each target street lamp in real time based on real-time traffic data and the initial lighting plan.

[0020] Preferably, the traffic analysis unit includes:

[0021] The video splicing subunit is used to splice the real-time traffic monitoring videos within the illumination range of all target street lamps based on their installation locations to obtain a complete monitoring video;

[0022] The trajectory marking subunit is used to mark the real-time dynamic trajectory of each monitored object in the complete monitoring video in a preset road model based on the corresponding relationship between the real-time dynamic trajectory and the position, so as to obtain a real-time traffic model;

[0023] The range division subunit is used to divide the illumination area corresponding to the illumination range of each target street lamp in the real-time traffic trajectory model, and use the comprehensive flow characterization value of the illumination area of ​​all target street lamps as real-time traffic data.

[0024] Preferably, the range division subunit includes:

[0025] The standard determination end is used to divide the illumination area corresponding to the illumination range of each target street lamp in the real-time traffic trajectory model, determine the maximum road width perpendicular to the traffic direction within the illumination area, determine the total number of partial dynamic trajectories included in the illumination area, and use the ratio of the maximum road width to the partial dynamic trajectories as the standard interval width;

[0026] An interval calculation end calculates an average interval width of each partial dynamic track and each corresponding adjacent partial dynamic track within the irradiation range based on the coordinate values ​​of the outline pixel points of each partial dynamic track;

[0027] The traffic calculation end is used to use the comprehensive traffic characterization value of the illumination area of ​​all target street lamps calculated based on the average interval width as real-time traffic data.

[0028] Preferably, the flow calculation end includes:

[0029] The trajectory division sub-terminal is used to aggregate the dynamic trajectories whose average interval width does not exceed the standard interval width to obtain a high-density trajectory set, and aggregate the dynamic trajectories whose average interval width exceeds the standard interval width to obtain a low-density trajectory set;

[0030] The density calculation sub-terminal is used to divide the corresponding illumination area into a high-density area and a low-density area based on the high-density trajectory set and the low-density trajectory set, and use the ratio of the maximum road width perpendicular to the traffic direction in the high-density area to the total number of partial dynamic trajectories contained in the high-density area as the trajectory density of the high-density area, and use the ratio of the maximum road width perpendicular to the traffic direction in the low-density area to the total number of partial dynamic trajectories contained in the low-density area as the trajectory density of the low-density area, and use the comprehensive traffic characterization value of the illumination area of ​​all target street lamps calculated based on the trajectory density of the high-density area and the low-density area as the real-time traffic data.

[0031] Preferably, the density calculation sub-terminal uses the comprehensive flow characterization value of the illumination area of ​​all target street lamps calculated based on the trajectory density of the high-density area and the low-density area as the real-time traffic data, including:

[0032] Based on the first coordinate representation and the corresponding trajectory density of the high-density area within the illumination range and the second coordinate representation and the corresponding trajectory density of the low-density area within the illumination range, the first traffic flow characterization value of the corresponding illumination area is determined, and the second traffic flow characterization value of the corresponding illumination area is calculated based on the first traffic flow characterization value of the illumination area adjacent to the corresponding illumination area. The comprehensive traffic flow characterization value of the corresponding illumination area is calculated based on the first traffic flow characterization value and the second traffic flow characterization value of the corresponding illumination area, and the comprehensive traffic flow characterization value of the illumination area of ​​all target street lamps is used as real-time traffic data.

[0033] Preferably, the lighting control unit includes:

[0034] an illumination determination subunit, configured to determine a target brightness value of a corresponding target street lamp at a corresponding moment based on the comprehensive flow characterization value of the illumination area of ​​all target street lamps in the real-time traffic data, and to determine an actual brightness value of the corresponding target street lamp at the corresponding moment based on the target brightness value at the corresponding moment and the planned brightness value of the corresponding target street lamp at the corresponding moment in the initial lighting plan;

[0035] The lighting control subunit is used to control the actual lighting data of the corresponding target street lamp in real time based on the actual brightness value.

[0036] Preferably, the power supply management module includes:

[0037] An input determination unit, configured to determine an input power curve of a target street lamp in a single day based on actual lighting data of the target street lamp in a single day;

[0038] an output determination unit, configured to predict an output power curve of the backup power supply based on input power curves and output power of the solar battery within a plurality of single days;

[0039] The power supply management unit is used to manage the power supply of the backup power supply based on the output power curve.

[0040] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0041] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 This is a schematic diagram of a remote online monitoring, control and management system for smart street lighting according to an embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of an initial generation module in an embodiment of the present invention;

[0045] Figure 3 Schematic diagram of a plan generation unit in an embodiment of the present invention;

[0046] Figure 4 This is a schematic diagram of a monitoring and control module in an embodiment of the present invention;

[0047] Figure 5 This is a schematic diagram of a traffic analysis unit in an embodiment of the present invention;

[0048] Figure 6 A schematic diagram of a range division subunit in an embodiment of the present invention;

[0049] Figure 7 This is a schematic diagram of a flow calculation terminal in an embodiment of the present invention;

[0050] Figure 8 This is a schematic diagram of a lighting control unit in an embodiment of the present invention;

[0051] Figure 9 Schematic diagram of a power supply management module in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0053] Example 1:

[0054] The present invention provides a remote online monitoring and control management system for smart street lamp lighting. Figure 1 ,include:

[0055] An initial generation module is used to determine an initial lighting plan based on the lighting data and traffic data of the target street lamp location;

[0056] A monitoring and control module is used to monitor real-time traffic data within the illumination range of the target street lamp and to control the actual lighting data of the target street lamp in real time based on the real-time traffic data and the initial lighting plan;

[0057] The power supply management module is used to perform power supply scheduling management on the backup power supply based on the actual lighting data of the target street lamp in a single day and the output power of the solar battery, and obtain the power supply scheduling management results.

[0058] In this embodiment, the lighting data includes multiple single-day lighting data at the location of the target street lamp within the analysis period. The analysis period is the period of lighting data that needs to be collected when determining the initial lighting plan. The single-day lighting data is the lighting value change data at the location of the target street lamp within a single day.

[0059] In this embodiment, the traffic data includes multiple daily traffic data at the location of the target street lamp within the analysis period. The analysis period is the period of traffic data that needs to be collected when determining the initial lighting data plan. The daily traffic data is the traffic value change data at the location of the target street lamp within a single day.

[0060] In this embodiment, the initial lighting plan is a plan including the brightness values ​​that should be set for the target street lamp at different times within a single day, which is determined based on the lighting data and traffic data of the location of the target street lamp.

[0061] In this embodiment, the illumination range is the range that the target street lamp can illuminate on the road.

[0062] In this embodiment, the real-time traffic data is data representing the traffic flow within the illumination range of the target street lamp.

[0063] In this embodiment, the actual lighting data is the brightness value actually emitted by the target street lamp.

[0064] In this embodiment, the solar battery is a battery device installed on the target street lamp for supplying power to the target street lamp.

[0065] In this embodiment, the backup power supply is a power supply used to supply power to the target street lamp together with the solar battery when the solar battery cannot meet the power demand of the target street lamp.

[0066] In this embodiment, the backup power supply is dispatched and managed based on the actual lighting data of the target street lamp in a single day and the output power of the solar battery, namely:

[0067] Based on the actual lighting data of the target street lamps in a single day and the output power of the solar battery, the output power change curve of the backup power supply in a single day is determined, and the output power of the backup power supply is scheduled and managed based on the output power change curve of the backup power supply in a single day (that is, the backup power supply may supply power to multiple target street lamps at the same time. Therefore, the output power that needs to be provided to the target street lamp at the corresponding moment is determined according to the output power change curve of the backup power supply, and then the power reserve value is added to the output power at the corresponding moment (that is, to avoid insufficient power supply to the target street lamp due to prediction deviation, the output power needs to be reserved), and the output power that the backup power supply needs to provide to the corresponding target street lamp at the corresponding moment is obtained).

[0068] In this embodiment, the power supply scheduling management result is a result obtained after power supply scheduling management of the backup power supply is performed based on the actual lighting data of the target street lamp in a single day and the output power of the solar battery.

[0069] The beneficial effects of the above technology are: generating an initial lighting plan based on the historical lighting data and historical traffic data of the location of the street lamp, and adjusting the lighting data of the street lamp based on the initial lighting plan based on the real-time traffic data, realizing the function of online monitoring and regulation of the street lamp and power supply management based on the lighting data and traffic flow data of the location of the street lamp, saving electricity and reducing the phenomenon of light overflow.

[0070] Example 2:

[0071] Based on Example 1, the initial generation module, refer to Figure 2 ,include:

[0072] A first acquisition unit is configured to obtain a plurality of single-day illumination data of a location of a target street lamp within an analysis period as illumination data;

[0073] The second acquisition unit is configured to acquire a plurality of single-day traffic flow data of the location of the target street lamp based on a plurality of single-day traffic monitoring videos of the location of the target street lamp within an analysis period as traffic flow data;

[0074] The plan generation unit is used to generate an initial lighting plan for the target street lamp based on the lighting data and traffic data.

[0075] In this embodiment, the single-day illumination data is the illumination value variation data at the location of the target street lamp within a single day.

[0076] In this embodiment, the analysis period is the period of collecting illumination data and traffic data required to determine the initial lighting plan.

[0077] In this embodiment, the daily traffic data is the traffic value change data at the location of the target street lamp within a single day.

[0078] In this embodiment, single-day sunlight data is obtained from local historical meteorological data.

[0079] In this embodiment, the traffic monitoring video for a single day is the historical traffic monitoring video obtained by the monitoring device set on the target street lamp.

[0080] In this embodiment, multiple single-day traffic flow data of the target street lamp location are obtained based on multiple single-day traffic monitoring videos of the target street lamp location within the analysis period, namely:

[0081] By analyzing the traffic monitoring video of a single day, the comprehensive flow characterization value within the illumination range of the target street lamp at different times on the corresponding single day is determined (that is, the value representing the traffic flow within the corresponding illumination range of the target street lamp at the corresponding time, and the larger the comprehensive flow characterization value, the greater the traffic flow). The comprehensive flow characterization value within the illumination range of the target street lamp at different times on the corresponding single day is used as the single-day traffic data of the location of the target street lamp;

[0082] The single-day traffic flow data determined by analyzing multiple single-day traffic monitoring videos within the analysis period will be used as the multiple single-day traffic flow data at the location of the target street lamp within the analysis period.

[0083] The beneficial effect of the above technology is that by obtaining the natural light change data and traffic change data of the target street lamp location within multiple single days within the analysis period, an initial lighting control plan for the target street lamp is generated.

[0084] Example 3:

[0085] On the basis of Example 2, the plan generation unit refers to Figure 3 ,include:

[0086] an illumination calculation subunit, configured to determine average daily illumination change data based on a plurality of daily illumination data in the illumination data, calculate a first brightness value at a corresponding moment based on the illumination value at a corresponding moment in the average daily illumination change data and a first conversion method, determine average daily flow change data based on a plurality of daily flow data in the flow data, calculate a second brightness value at a corresponding moment based on the flow value at a corresponding moment in the average daily flow change data and a second conversion method;

[0087] The plan generating subunit is configured to calculate a planned brightness value at a corresponding moment based on the first brightness value and the second brightness value, and to generate an initial lighting plan for the target street lamp based on the planned brightness values ​​at all moments in a single day.

[0088] In this embodiment, the average single-day illumination change data is determined based on multiple single-day illumination data in the illumination data, namely:

[0089] Generate a single-day illumination value change curve for each single-day illumination data in the illumination data, align all single-day illumination value change curves in time series and average them, and obtain the average single-day illumination value change curve as the average single-day illumination change data.

[0090] In this embodiment, the first conversion method is a conversion method between a preset natural light value and the output light value of the target street lamp. For example, the product of the inverse of the natural light value and the preset first conversion coefficient (that is, the multiple between the output light value of the target street lamp and the preset natural light value) is the light value that the target street lamp should output, determined based on the light data.

[0091] In this embodiment, the first brightness value is the output light value of the target street lamp at the corresponding moment calculated based on the light data and the light value of the target street lamp at the corresponding moment, which is determined based on the light data and calculated using the first conversion method.

[0092] In this embodiment, the average daily flow change data is determined based on multiple daily flow data in the flow data, that is:

[0093] Generate a single-day comprehensive flow characterization value change curve for each single-day flow data in the flow data, align all single-day comprehensive flow characterization value change curves in time series and average them, and obtain the average single-day comprehensive flow characterization value change curve as the average single-day flow change data.

[0094] In this embodiment, the second brightness value is the output illumination value of the target street lamp at the corresponding moment calculated based on the comprehensive flow characterization value at the corresponding moment in the average daily flow change data and the flow data, which is calculated using the first conversion method.

[0095] In this embodiment, the second conversion method is a conversion method between a preset comprehensive flow characterization value and the output illumination value of the target street lamp. For example, the product of the comprehensive flow characterization value and a preset second conversion coefficient (that is, a multiple of the output illumination value of the target street lamp and the preset comprehensive flow characterization value) is the illumination value that the target street lamp should output, determined based on the flow data.

[0096] In this embodiment, the planned brightness value at the corresponding moment is calculated based on the first brightness value and the second brightness value, that is:

[0097] The larger value between the first brightness value and the second brightness value is used as the planned brightness value at the corresponding moment.

[0098] The beneficial effects of the above technology are: determining the planned lighting value of the target street lamp at the corresponding time based on multiple single-day lighting data contained in the lighting data and multiple single-day flow data contained in the flow data, and then generating a lighting plan for the target street lamp based on the previous lighting data and flow data of the location of the target street lamp.

[0099] Example 4:

[0100] Based on Example 1, the monitoring and control module, refer to Figure 4 ,include:

[0101] Traffic analysis unit, used to jointly analyze the real-time traffic monitoring videos within the illumination range of all target street lamps based on the installation locations of all target street lamps to obtain real-time traffic data;

[0102] The lighting control unit is used to control the actual lighting data of each target street lamp in real time based on real-time traffic data and the initial lighting plan.

[0103] In this embodiment, the real-time traffic data is data representing the real-time traffic flow within the illumination range of the target street lamps obtained by jointly analyzing the real-time traffic monitoring videos within the illumination range corresponding to all target street lamps based on the installation locations of all target street lamps.

[0104] In this embodiment, the real-time traffic monitoring video is a video obtained based on the monitoring device set on the target street lamp and contains all real-time traffic conditions within the illumination range of the target street lamp.

[0105] The beneficial effect of the above technology is: by jointly analyzing the real-time traffic monitoring videos within the illumination range of all target street lights, the real-time traffic conditions within the illumination range of the target street lights can be obtained, and then the real-time regulation of the actual lighting data of the target street lights can be achieved.

[0106] Example 5:

[0107] Based on Example 4, the traffic analysis unit, referring to Figure 5 ,include:

[0108] The video splicing subunit is used to splice the real-time traffic monitoring videos within the illumination range of all target street lamps based on their installation locations to obtain a complete monitoring video;

[0109] The trajectory marking subunit is used to mark the real-time dynamic trajectory of each monitored object in the complete monitoring video in a preset road model based on the corresponding relationship between the real-time dynamic trajectory and the position, so as to obtain a real-time traffic model;

[0110] The range division subunit is used to divide the illumination area corresponding to the illumination range of each target street lamp in the real-time traffic trajectory model, and use the comprehensive flow characterization value of the illumination area of ​​all target street lamps as real-time traffic data.

[0111] In this embodiment, the complete monitoring video is a monitoring video including the illumination range of all target street lamps obtained by splicing the real-time traffic monitoring videos within the illumination range corresponding to all target street lamps based on the installation positions of all target street lamps.

[0112] In this embodiment, the monitored objects are objects that appear within the illumination range of all target streetlights in the complete monitoring video (which may be pedestrians, vehicles, or other objects moving on the road).

[0113] In this embodiment, the real-time dynamic trajectory is the trajectory of the corresponding monitored object in the complete monitoring video that is currently passing within the illumination range of all target street lamps.

[0114] In this embodiment, the position correspondence is the coordinate conversion relationship between the position coordinates of the pixel point in the pre-input real-time traffic monitoring video and the actual position coordinates on the road, that is, the other position coordinate (that is, the position coordinate of the pixel point in the monitoring video or the actual position coordinate on the road) can be determined through the position correspondence and one of the position coordinates of the pixel point in the monitoring video or the actual position coordinates on the road.

[0115] In this embodiment, the real-time traffic model is a model that represents the real-time dynamic trajectories of all monitored objects on the road where the target street lamp is located, based on the real-time dynamic trajectory and position correspondence of each monitored object in the complete monitoring video, and marking the real-time dynamic trajectory in a preset road model.

[0116] In this embodiment, the illumination area is the area corresponding to the illumination range of each target street lamp in the real-time traffic trajectory model.

[0117] In this embodiment, the comprehensive traffic flow characterization value of the target street lamp's illuminated area is a value characterizing the current traffic flow situation in the target street lamp's illuminated area. A larger comprehensive traffic flow characterization value indicates a larger traffic flow.

[0118] The beneficial effects of the above technology are: the real-time traffic monitoring videos of all target street lamps are spliced ​​together to obtain a complete monitoring video, and the real-time dynamic trajectory of the monitored object determined in the complete monitoring video and the comprehensive flow guarantee value of the illumination area determined in the real-time traffic model built by the preset road model are used as real-time traffic data to realize the analysis of the real-time traffic situation within the illumination range of the target street lamp.

[0119] Example 6:

[0120] Based on Example 5, the range is divided into sub-units, refer to Figure 6 ,include:

[0121] The standard determination end is used to divide the illumination area corresponding to the illumination range of each target street lamp in the real-time traffic trajectory model, determine the maximum road width perpendicular to the traffic direction within the illumination area, determine the total number of partial dynamic trajectories included in the illumination area, and use the ratio of the maximum road width to the partial dynamic trajectories as the standard interval width;

[0122] An interval calculation end calculates an average interval width of each partial dynamic track and each corresponding adjacent partial dynamic track within the irradiation range based on the coordinate values ​​of the outline pixel points of each partial dynamic track;

[0123] The traffic calculation end is used to use the comprehensive traffic characterization value of the illumination area of ​​all target street lamps calculated based on the average interval width as real-time traffic data.

[0124] In this embodiment, the traffic direction is the direction in which the monitored object on the road moves back and forth, such as east-west or north-south.

[0125] In this embodiment, the maximum road width refers to the maximum width in the direction perpendicular to the traffic direction within the illumination range.

[0126] In this embodiment, the average interval width of each partial dynamic track and each corresponding adjacent partial dynamic track within the irradiation range is calculated based on the coordinate values ​​of the outline pixel points of each partial dynamic track, including:

[0127]

[0128] Where L is the average interval width between each partial dynamic track and the corresponding adjacent partial dynamic track within the illumination range, i is the i-th contour pixel point in the partial dynamic track, n is the total number of contour pixels in the partial dynamic track, j is the j-th contour pixel point in the corresponding adjacent partial dynamic track, m is the total number of contour pixels in the corresponding adjacent partial dynamic track, and x is the distance between the two adjacent partial dynamic tracks. i is the horizontal coordinate value of the i-th contour pixel point in the partial dynamic trajectory, x j is the horizontal coordinate value of the jth contour pixel point in the corresponding adjacent partial dynamic trajectory, y i is the ordinate value of the i-th contour pixel point in the partial dynamic trajectory, y j is the ordinate value of the j-th contour pixel point in the corresponding adjacent partial dynamic trajectory.

[0129] The beneficial effect of the above technology is: by analyzing the interval width between the tracks in the illumination area of ​​the target street lamp, the real-time traffic situation in the illumination area of ​​the target street lamp can be analyzed.

[0130] Example 7:

[0131] Based on Example 6, the flow calculation end, refer to Figure 7 ,include:

[0132] The trajectory division sub-terminal is used to aggregate the dynamic trajectories whose average interval width does not exceed the standard interval width to obtain a high-density trajectory set, and aggregate the dynamic trajectories whose average interval width exceeds the standard interval width to obtain a low-density trajectory set;

[0133] The density calculation sub-terminal is used to divide the corresponding illumination area into a high-density area and a low-density area based on the high-density trajectory set and the low-density trajectory set, and use the ratio of the maximum road width perpendicular to the traffic direction in the high-density area to the total number of partial dynamic trajectories contained in the high-density area as the trajectory density of the high-density area, and use the ratio of the maximum road width perpendicular to the traffic direction in the low-density area to the total number of partial dynamic trajectories contained in the low-density area as the trajectory density of the low-density area, and use the comprehensive traffic characterization value of the illumination area of ​​all target street lamps calculated based on the trajectory density of the high-density area and the low-density area as the real-time traffic data.

[0134] In this embodiment, the high-density trajectory set is a set obtained by aggregating some dynamic trajectories whose average interval width does not exceed the standard interval width.

[0135] In this embodiment, the low-density trajectory set is a set obtained by aggregating some dynamic trajectories whose average interval width exceeds the standard interval width.

[0136] In this embodiment, the corresponding irradiation area is divided into a high-density area and a low-density area based on the high-density trajectory set and the low-density trajectory set, that is:

[0137] The area in the illumination area containing all partial dynamic trajectories in the high-density trajectory set is regarded as a high-density area, and the area in the illumination area containing all partial dynamic trajectories in the low-density trajectory set is regarded as a low-density area.

[0138] In this embodiment, the trajectory density is a value representing the density of some dynamic trajectories in a high-density area or a low-density area.

[0139] The beneficial effects of the above technology are: it is possible to classify some dynamic trajectories within the illumination area of ​​the target street lamp by the interval width between them, and divide the illumination area on this basis, and based on the trajectory density in the divided area, it is possible to accurately analyze the traffic conditions within the illumination area of ​​the target street lamp.

[0140] Example 8:

[0141] Based on Example 7, the density calculation sub-terminal uses the comprehensive flow representation value of the illumination area of ​​all target street lamps calculated based on the trajectory density of the high-density area and the low-density area as the real-time traffic data, including:

[0142] Based on the first coordinate representation and the corresponding trajectory density of the high-density area within the illumination range and the second coordinate representation and the corresponding trajectory density of the low-density area within the illumination range, the first traffic flow characterization value of the corresponding illumination area is determined, and the second traffic flow characterization value of the corresponding illumination area is calculated based on the first traffic flow characterization value of the illumination area adjacent to the corresponding illumination area. The comprehensive traffic flow characterization value of the corresponding illumination area is calculated based on the first traffic flow characterization value and the second traffic flow characterization value of the corresponding illumination area, and the comprehensive traffic flow characterization value of the illumination area of ​​all target street lamps is used as real-time traffic data.

[0143] In this embodiment, based on the first coordinate representation and corresponding trajectory density of the high-density area within the illumination range and the second coordinate representation and corresponding trajectory density of the low-density area within the illumination range, a first traffic flow representation value corresponding to the illumination area is determined, including:

[0144] Determine the coordinate values ​​of the outline pixel points of the high-density area based on the first coordinate representation, and determine the coordinate values ​​of the outline pixel points of the low-density area based on the second coordinate representation;

[0145] Based on the coordinate values ​​and corresponding trajectory density of the contour pixels in the high-density area and the coordinate values ​​and corresponding trajectory density of the contour pixels in the low-density area, and combined with the coordinate values ​​of the target street lamp in the complete monitoring video, the first traffic flow representation value of the corresponding illuminated area is calculated:

[0146]

[0147] Where Q is the first traffic flow representation value of the corresponding illumination area, ρ1 is the trajectory density of the high-density area, a is the a-th contour pixel point in the high-density area, p is the total number of contour pixels contained in the high-density area, and x a is the horizontal coordinate value of the ath contour pixel point in the high-density area, x0 is the horizontal coordinate value of the target street light in the complete monitoring video, and y a is the ordinate value of the ath contour pixel point in the high-density area, y0 is the ordinate value of the target street light in the complete monitoring video, L max is the maximum road width perpendicular to the traffic direction in the corresponding illumination area, b is the bth contour pixel point in the low-density area, q is the total number of contour pixels contained in the low-density area, and x b is the horizontal coordinate value of the bth contour pixel point in the low-density area, y b It is the vertical coordinate value of the bth contour pixel point in the low-density area.

[0148] In this embodiment, the second traffic flow characterization value of the corresponding illumination area is calculated based on the first traffic flow characterization value of the illumination area adjacent to the corresponding illumination area, that is:

[0149] The average value of the first traffic flow characterization values ​​of all the illumination areas adjacent to the corresponding illumination area is used as the second traffic flow characterization value of the corresponding illumination area.

[0150] In this embodiment, the comprehensive traffic flow characterization value of the corresponding illuminated area is calculated based on the first traffic flow characterization value and the second traffic flow characterization value of the corresponding illuminated area, that is:

[0151] Z=α1Q1+α2Q2

[0152] In the formula, Z is the comprehensive flow characterization value of the corresponding illumination area, α1 is the first weight corresponding to the first traffic flow characterization value when calculating the comprehensive flow characterization value (preset (determined by the user), Q1 is the first traffic flow characterization value of the corresponding illumination area, α2 is the second weight corresponding to the second traffic flow characterization value when calculating the comprehensive flow characterization value (preset (determined by the user), and Q2 is the second traffic flow characterization value of the corresponding illumination area.

[0153] The beneficial effects of the above technology are: based on the first coordinate representation and corresponding trajectory density of the high-density area within the illumination range and the second coordinate representation and corresponding trajectory density of the low-density area within the illumination range, it is possible to determine the value representing the traffic flow in the corresponding illumination area by taking into account the distance from the target street lamp of different density levels, and to determine the value accurately representing the traffic flow situation in the corresponding illumination area by taking into account the traffic flow situation in the illumination area of ​​adjacent target street lamps.

[0154] Example 9:

[0155] On the basis of Example 5, the lighting control unit, referring to Figure 8 ,include:

[0156] an illumination determination subunit, configured to determine a target brightness value of a corresponding target street lamp at a corresponding moment based on the comprehensive flow characterization value of the illumination area of ​​all target street lamps in the real-time traffic data, and to determine an actual brightness value of the corresponding target street lamp at the corresponding moment based on the target brightness value at the corresponding moment and the planned brightness value of the corresponding target street lamp at the corresponding moment in the initial lighting plan;

[0157] The lighting control subunit is used to control the actual lighting data of the corresponding target street lamp in real time based on the actual brightness value.

[0158] In this embodiment, the target brightness value of the corresponding target street lamp at the corresponding time is determined based on the comprehensive flow characterization value of the illumination area of ​​all target street lamps in the real-time traffic data.

[0159] In this embodiment, the target brightness value of the corresponding target street lamp at the corresponding time is determined based on the comprehensive flow characterization value of the illumination area of ​​all target street lamps in the real-time traffic data, that is:

[0160] The target brightness value at the corresponding moment is determined based on the comprehensive characterization value and the corresponding conversion method (for example, the product of the comprehensive characterization value and the corresponding conversion coefficient (that is, the coefficient for converting the comprehensive characterization value into the target brightness value) is used as the target brightness value at the corresponding moment).

[0161] In this embodiment, the target brightness value is the brightness value that the target street light should emit at a corresponding moment, determined based on real-time traffic data.

[0162] In this embodiment, based on the target brightness value at the corresponding moment and the planned brightness value of the corresponding target street lamp at the corresponding moment in the initial lighting plan, the actual brightness value of the corresponding target street lamp at the corresponding moment is determined, namely:

[0163] The sum of the larger value of the first brightness value determined based on the illumination data in the target brightness value and the planned brightness value and the second brightness value determined based on the traffic data in the planned brightness value is taken as the actual brightness value of the corresponding target street lamp at the corresponding moment.

[0164] In this embodiment, the actual brightness value is the brightness value actually emitted by the target street lamp.

[0165] In this embodiment, the actual lighting data of the corresponding target street lamp is regulated in real time based on the actual brightness value, that is, the actual output brightness value of the target street lamp is set to the actual brightness value obtained in real time.

[0166] The beneficial effects of the above technology are: realizing real-time correction of the planned brightness value corresponding to the current moment in the initial lighting plan based on the target brightness value determined by the comprehensive flow value within the illumination range of the target street lamp analyzed based on real-time traffic data, thereby further ensuring the control accuracy of the output brightness of the target street lamp, so that the brightness value emitted by the target street lamp can minimize the power consumption while meeting the brightness requirements of the road.

[0167] Example 10:

[0168] Based on Example 1, the power supply management module, refer to Figure 9 ,include:

[0169] An input determination unit, configured to determine an input power curve of a target street lamp in a single day based on actual lighting data of the target street lamp in a single day;

[0170] an output determination unit, configured to predict an output power curve of the backup power supply based on input power curves and output power of the solar battery within a plurality of single days;

[0171] The power supply management unit is used to manage the power supply of the backup power supply based on the output power curve.

[0172] In this embodiment, the input power curve is a curve representing the change over time of the power required by the target street lamp in a single day, which is calculated based on the actual lighting data of the target street lamp in a single day.

[0173] In this embodiment, based on the input power curves and the output power of the solar battery in multiple single days, the output power curve of the backup power supply is predicted, namely:

[0174] Based on the input power curves within multiple single days and the output power of the solar battery, the power required by the backup power supply to provide for the corresponding target street lamp at each moment in a single day is determined. Based on the sum of the power required by the backup power supply to provide for the corresponding target street lamp at each moment in a single day and the power reserve value (that is, the output power that needs to be reserved to avoid insufficient power supply to the target street lamp due to prediction deviation), the planned output power of the backup power supply at the corresponding moment is generated, and the output power curve is generated based on the planned output power at all moments in a single day.

[0175] In this embodiment, the backup power supply is managed based on the output power curve, namely:

[0176] The power output by the backup power supply for the corresponding target street lamp at the corresponding moment is set based on the planned output power of the backup power supply at the corresponding moment in the output power curve.

[0177] The beneficial effects of the above technology are: based on the actual lighting data of the target street lamp in a single day, the input power curve of the target street lamp in a single day is calculated, and then the planned output power of the backup power supply is calculated based on the output power of the solar battery, thereby realizing early prediction and management of the output power of the backup power supply, realizing power supply management of the target street lamp, and reducing power supply waste of the backup power supply.

[0178] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A remote online monitoring, control and management system for smart street lighting, characterized in that: include: An initial generation module is used to determine an initial lighting plan based on the lighting data and traffic data of the target street lamp location; The monitoring and control module is used to monitor the real-time traffic data within the illumination range of the target street lamp and control the actual lighting data of the target street lamp in real time based on the real-time traffic data and the initial lighting plan, including: The traffic analysis unit is used to jointly analyze the real-time traffic monitoring videos within the illumination range of all target streetlights based on their installation locations to obtain real-time traffic data, including: Based on the installation locations of all target streetlights, the real-time traffic monitoring videos within the illumination range of all target streetlights are spliced ​​together to obtain a complete monitoring video. Based on the real-time dynamic trajectory and position correspondence of each monitored object in the complete surveillance video, the real-time dynamic trajectory is marked in the preset road model to obtain a real-time traffic model; In the real-time traffic trajectory model, the illumination area corresponding to the illumination range of each target street lamp is divided, the maximum road width perpendicular to the traffic direction within the illumination area is determined, the total number of partial dynamic trajectories contained in the illumination area is determined, and the ratio of the maximum road width to the partial dynamic trajectories is used as the standard interval width; The average interval width of each partial dynamic track and each corresponding adjacent partial dynamic track within the irradiation range is calculated based on the coordinate values ​​of the outline pixel points of each partial dynamic track; The dynamic trajectories whose average interval width does not exceed the standard interval width are summarized to obtain a high-density trajectory set, and the dynamic trajectories whose average interval width exceeds the standard interval width are summarized to obtain a low-density trajectory set; Based on the high-density trajectory set and the low-density trajectory set, the corresponding illumination area is divided into a high-density area and a low-density area. The ratio of the maximum road width perpendicular to the traffic direction in the high-density area to the total number of dynamic trajectories contained in the high-density area is used as the trajectory density of the high-density area. The ratio of the maximum road width perpendicular to the traffic direction in the low-density area to the total number of dynamic trajectories contained in the low-density area is used as the trajectory density of the low-density area. Based on the first coordinate representation of the high-density area within the illumination range, the coordinate values ​​of the contour pixels of the high-density area are determined; based on the second coordinate representation of the low-density area within the illumination range, the coordinate values ​​of the contour pixels of the low-density area are determined; and based on the coordinate values ​​and corresponding trajectory density of the contour pixels of the high-density area and the coordinate values ​​and corresponding trajectory density of the contour pixels of the low-density area, and combined with the coordinate values ​​of the target street lamp in the complete monitoring video, the first traffic flow representation value of the corresponding illumination area is calculated: Where Q is the first traffic flow representation value of the corresponding illumination area, ρ1 is the trajectory density of the high-density area, a is the a-th contour pixel point in the high-density area, p is the total number of contour pixels contained in the high-density area, and x a is the horizontal coordinate value of the ath contour pixel point in the high-density area, x0 is the horizontal coordinate value of the target street light in the complete monitoring video, and y a is the ordinate value of the ath contour pixel point in the high-density area, y0 is the ordinate value of the target street light in the complete monitoring video, L max is the maximum road width perpendicular to the traffic direction in the corresponding illumination area, b is the bth contour pixel point in the low-density area, q is the total number of contour pixels contained in the low-density area, and x b is the horizontal coordinate value of the bth contour pixel point in the low-density area, y b is the ordinate value of the bth contour pixel point in the low-density area; Calculate a second traffic flow characterization value of the corresponding illuminated area based on the first traffic flow characterization value of the illuminated area adjacent to the corresponding illuminated area, calculate a comprehensive traffic flow characterization value of the corresponding illuminated area based on the first traffic flow characterization value and the second traffic flow characterization value of the corresponding illuminated area, and use the comprehensive traffic flow characterization values ​​of the illuminated areas of all target street lamps as real-time traffic data; A lighting control unit is used to control the actual lighting data of each target street lamp in real time based on real-time traffic data and the initial lighting plan; The power supply management module is used to perform power supply scheduling management on the backup power supply based on the actual lighting data of the target street lamp in a single day and the output power of the solar battery, and obtain the power supply scheduling management results.

2. A street lamp intelligent lighting remote online monitoring and control management system according to claim 1, characterized in that: Initial generation module, including: A first acquisition unit is configured to obtain a plurality of single-day illumination data of a location of a target street lamp within an analysis period as illumination data; The second acquisition unit is configured to acquire a plurality of single-day traffic flow data of the location of the target street lamp based on a plurality of single-day traffic monitoring videos of the location of the target street lamp within an analysis period as traffic flow data; The plan generation unit is used to generate an initial lighting plan for the target street lamp based on the lighting data and traffic data.

3. A street lamp intelligent lighting remote online monitoring and control management system according to claim 2, characterized in that: Plan generation unit, including: an illumination calculation subunit, configured to determine average daily illumination change data based on a plurality of daily illumination data in the illumination data, calculate a first brightness value at a corresponding moment based on the illumination value at a corresponding moment in the average daily illumination change data and a first conversion method, determine average daily flow change data based on a plurality of daily flow data in the flow data, calculate a second brightness value at a corresponding moment based on the flow value at a corresponding moment in the average daily flow change data and a second conversion method; The plan generating subunit is configured to calculate a planned brightness value at a corresponding moment based on the first brightness value and the second brightness value, and to generate an initial lighting plan for the target street lamp based on the planned brightness values ​​at all moments in a single day.

4. The remote online monitoring, control and management system for smart street lighting according to claim 1 is characterized in that: Lighting control unit, including: an illumination determination subunit, configured to determine a target brightness value of a corresponding target street lamp at a corresponding moment based on the comprehensive flow characterization value of the illumination area of ​​all target street lamps in the real-time traffic data, and to determine an actual brightness value of the corresponding target street lamp at the corresponding moment based on the target brightness value at the corresponding moment and the planned brightness value of the corresponding target street lamp at the corresponding moment in the initial lighting plan; The lighting control subunit is used to control the actual lighting data of the corresponding target street lamp in real time based on the actual brightness value.

5. The remote online monitoring, control and management system for smart street lighting according to claim 1 is characterized in that: Power management module, including: An input determination unit, configured to determine an input power curve of a target street lamp in a single day based on actual lighting data of the target street lamp in a single day; an output determination unit, configured to predict an output power curve of the backup power supply based on input power curves and output power of the solar battery within a plurality of single days; The power supply management unit is used to manage the power supply of the backup power supply based on the output power curve.

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