Self-adaptive monitoring method of sand dredger self-adaptive monitoring system based on deep learning

Abstract

The invention discloses a self-adaptive monitoring method of a sand dredger self-adaptive monitoring system based on deep learning. The sand dredger self-adaptive monitoring system comprises a front-end monitoring terminal, a reasoning recognition device and a server management device. The front-end monitoring terminal comprises an embedded microprocessor, a water bank monitoring camera, a Beidou positioning module and an energy condition monitoring module; the reasoning recognition device comprises an embedded PC, and a wireless image transmission communication module, a deep learning acceleration card, a 4G wireless communication module, an Ethernet module and an SD card data storage module which are electrically connected with the embedded PC; the server management device comprises a sand dredger management Web platform, a sand dredger identification server, a monitoring state analysis server and a storage server, wherein the sand dredger identification server, the monitoring state analysis server and the storage server are electrically connected with the sand dredger management Web platform. According to the invention, automatic identification when the river and lake sand dredger enters and exits a sand excavation area and identification, evidence obtaining and early warning functions of illegal river and lake sand dredgers can be realized.

Description

technical field [0001] The invention relates to the technical field of an adaptive monitoring system for river and lake governance, in particular to an adaptive monitoring method for an adaptive monitoring system for a sand dredging ship based on deep learning. Background technique [0002] With the acceleration of urban construction, the demand for sand mining in rivers and lakes has increased dramatically, and disorderly and illegal sand mining has occurred frequently, seriously damaging the environment of rivers and lakes and threatening flood control safety. An important technical means for ecological environment protection and construction. The current river and lake sand mining information management platform mainly focuses on sand mining information registration, query, statistics, analysis, and report generation, with poor timeliness, low inspection efficiency, and difficulty in obtaining evidence and law enforcement. It is difficult to effectively control the patro...

AI Technical Summary

Problems solved by technology

The current river and lake sand mining information management platform mainly focuses on sand mining information registration, query, statistics, analysis, and report generation, with poor timeliness, low inspection efficiency, and difficulty in obtaining evidence and law enforcement. Inspection, it is difficult to get effective control, unable to adapt to the monitoring, identification, tracking, evidence collection, early warning and other intelligent supervision requirements of sand mining chaos

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