Street lamp fault monitoring system based on AI edge calculation

Abstract

The invention relates to the field of smart cities, in particular to a street lamp fault monitoring system based on AI edge computing, which comprises a plurality of edge computing nodes deployed on a street lamp side and a cloud management platform in communication connection with all the edge computing nodes through an internet of things network. The edge computing node is used for collecting and analyzing state information of a target street lamp and reporting a fault; and the cloud management platform is used for receiving and processing the fault information and optimizing the system AI model. Through an interval deployment strategy and a multi-sensor fusion verification mechanism, the system ensures that monitoring coverage is free of omission while the hardware deployment number and cost are remarkably reduced, an edge AI processes images in real time, and cross validation is performed in combination with electrical data, so that the fault identification accuracy is improved. The method greatly improves the recognition accuracy and reliability of faults, such as'light-off 'and'flicker', of a single street lamp, and reduces the false alarm and missing alarm.

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