CN-121984959-A - Remote AI centralized control system of integrative street lamp of scene

CN121984959ACN 121984959 ACN121984959 ACN 121984959ACN-121984959-A

Abstract

The embodiment of the invention provides a remote AI centralized control system and a remote AI centralized control method for a wind-solar integrated street lamp, and relates to the technical field of intelligent power grids and Internet of things technologies. The method comprises the steps of executing edge-side real-time data analysis and state prejudgment to generate a state data packet, uploading the state data packet to a cloud platform, executing comprehensive analysis and management and control decisions based on the state data packet by the cloud platform to generate an equipment-side intervention instruction, and executing the equipment-side intervention instruction. The invention solves the problem of low intelligent degree of the control of the street lamp, and further achieves the effect of improving the intelligent degree of the control of the street lamp.

Inventors

YAN SHAOBIN
YAN FEIFEI
HU XINGWEI

Assignees

上海博昂电气有限公司

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (10)

1. A remote AI centralized control method of a wind-solar integrated street lamp is characterized by comprising the following steps: Performing edge-side real-time data analysis and state pre-judgment to generate a state data packet, wherein the performing edge-side real-time data analysis and state pre-judgment comprises collecting real-time data of key parameters from at least one equipment sensor at a preset frequency, calculating a time change rate of the key parameters, determining a current equipment state grade based on the real-time data of the key parameters and the time change rate, and generating the state data packet based on the current equipment state grade; Uploading the state data packet to a cloud platform; The cloud platform executes comprehensive analysis and management and control decisions based on the state data packet to generate equipment-side intervention instructions; And executing the equipment side intervention instruction.
2. The method of claim 1, wherein the determining a current device state level based on the real-time data of the key parameter and the time rate of change comprises: comparing the real-time data of the key parameters and the time change rate with a preset parameter threshold value and a preset change rate threshold value respectively; and determining the state grade of the current equipment from a preset state grade set according to the comparison result, wherein the state grade set comprises a normal state, a concerned state, an early warning state and an emergency state.
3. The method of claim 1, wherein prior to uploading the status data packet to the cloud platform, the method further comprises: based on the link quality prejudgement result, executing active communication mode selection to determine the optimal communication link; And uploading the state data packet to the cloud platform through the optimal communication link.
4. The method of claim 3, wherein performing active communication mode selection based on the link quality pre-determined result comprises: monitoring link quality indexes of a first communication link and a second communication link in real time; And when the first communication link is used as a current communication link and the link quality index of the first communication link is lower than a preset unstable threshold value and the link quality index of the second communication link is higher than a preset stable threshold value, determining the optimal communication link as the second communication link.
5. The method of claim 1, wherein the cloud platform performing comprehensive analysis and management decisions based on the status data packets comprises: analyzing the state data packet to obtain a device state grade; And when the equipment state grade is a preset alarm grade, generating alarm information, wherein the alarm information comprises equipment identification and fault type.
6. A remote AI centralized control system of integrative street lamp of scene, its characterized in that includes: an edge computing and data collecting unit configured to perform the edge real-time data analysis and status pre-determination as claimed in claim 1 to generate a status data packet; The communication unit is used for uploading the state data packet to a cloud platform, and the cloud AI management and control platform is used for receiving the state data packet and executing comprehensive analysis and management and control decision based on the state data packet so as to generate an equipment-side intervention instruction; And the instruction execution unit is used for receiving and executing the equipment-side intervention instruction.
7. The system of claim 6, wherein the determining the current device state level based on the real-time data of the key parameter and the time rate of change comprises: comparing the real-time data of the key parameters and the time change rate with a preset parameter threshold value and a preset change rate threshold value respectively; and determining the state grade of the current equipment from a preset state grade set according to the comparison result, wherein the state grade set comprises a normal state, a concerned state, an early warning state and an emergency state.
8. The system of claim 6, wherein the system further comprises: before uploading the status data packet to the cloud platform, performing active communication mode selection based on a link quality prejudgment result to determine an optimal communication link; And uploading the state data packet to the cloud platform through the optimal communication link.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program, wherein the computer program is arranged to execute the method of any of the claims 1 to 5 when run.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of the claims 1 to 5.

Description

Remote AI centralized control system of integrative street lamp of scene Technical Field The embodiment of the invention relates to the field of smart grids and Internet of things, in particular to a remote AI centralized management and control system and method for wind-solar integrated street lamps. Background The wind-solar integrated street lamp is widely applied to urban and road illumination as a green illumination facility for supplying power by utilizing wind energy and solar energy. However, as the deployment scale thereof expands, conventional management modes expose a number of drawbacks. The existing wind-solar integrated street lamp generally lacks an effective remote centralized management and control means, and the equipment running state of the street lamp, such as the working condition of a fan, the electric quantity of an energy storage battery, the actual power of a lighting module and the like, often requires maintenance personnel to carry out regular manual on-site inspection, so that the efficiency is low, potential equipment faults cannot be found in time, the fault finding period is long, and the maintenance response is lagged. Furthermore, existing systems often do not have the ability to remotely issue fine control instructions. When the emergency weather conditions (such as windy weather) are faced, a forced protection instruction cannot be issued to the fan remotely, and when the illumination brightness is required to be dynamically adjusted according to the changes of people flow and traffic flow to save energy, remote power adjustment cannot be performed. The intelligent degree of the management mode is low, the flexibility is poor, and high manual maintenance cost and energy waste are caused. Therefore, how to construct an intelligent management and control system capable of realizing real-time monitoring of equipment state, active fault alarm and remote accurate control, so as to solve the problems of low intelligent degree, low management efficiency and poor communication adaptability of the conventional road lamp control, and the intelligent management and control system becomes a technical problem to be solved in the art. Disclosure of Invention The embodiment of the invention provides a remote AI centralized control system and a remote AI centralized control method for a wind-solar integrated street lamp, which at least solve the problem of low intelligent degree of lamp tube control in the related technology. According to one embodiment of the invention, a remote AI centralized control method of a wind-solar integrated street lamp is provided, comprising the following steps: Performing edge-side real-time data analysis and state pre-judgment to generate a state data packet, wherein the performing edge-side real-time data analysis and state pre-judgment comprises collecting real-time data of key parameters from at least one equipment sensor at a preset frequency, calculating a time change rate of the key parameters, determining a current equipment state grade based on the real-time data of the key parameters and the time change rate, and generating the state data packet based on the current equipment state grade; Uploading the state data packet to a cloud platform; The cloud platform executes comprehensive analysis and management and control decisions based on the state data packet to generate equipment-side intervention instructions; And executing the equipment side intervention instruction. In an exemplary embodiment, said determining a current device state level based on said real-time data of said key parameter and said time rate of change comprises: comparing the real-time data of the key parameters and the time change rate with a preset parameter threshold value and a preset change rate threshold value respectively; and determining the state grade of the current equipment from a preset state grade set according to the comparison result, wherein the state grade set comprises a normal state, a concerned state, an early warning state and an emergency state. In an exemplary embodiment, before uploading the status data packet to the cloud platform, the method further comprises: based on the link quality prejudgement result, executing active communication mode selection to determine the optimal communication link; And uploading the state data packet to the cloud platform through the optimal communication link. In an exemplary embodiment, the performing active communication mode selection based on the link quality pre-determination result includes: monitoring link quality indexes of a first communication link and a second communication link in real time; And when the first communication link is used as a current communication link and the link quality index of the first communication link is lower than a preset unstable threshold value and the link quality index of the second communication link is higher than a preset stable threshold value, determining the optimal communi