基于目标检测的北方河道非法采砂智能监管应用研究

Research on Intelligent Supervision and Application of Illegal Sand Mining in Northern RiverChannel Based on Target Detection

河道非法采砂对河道河势稳定、防洪安全、生态环境等产生不利影响。为提高河道非法采砂监管效率,采用基于深度学习-的Faster RCNN目标检测算法研发北方河道非法采砂智能监管系统,采用前后端分离B/S架构、超图WebGIS平台、PaddleDetection开发框架在系统中实现视频基础服务、算法模型管理、非法采砂识别、业务监管等功能。该系统接入高点位河湖视频监控设备回传画面,对禁采区的非法采砂行为自动检测,固定非法采砂证据,辅助水行政执法人员完成非法采砂闭环处置工作。以北方迁安市试点应用情况为例,证明了该系统具有可行性,可提高非法采砂监管水平和效率。

Illegal sand mining in river channel has adverse effects on river regime stability, flood control safety and ecological environment.In order to improve the supervision efficiency of illegal sand mining in rivers, an intelligent monitoring system for illegal sand mining in north⁃ern rivers was developed based on the Faster⁃RCNN object detection algorithm based on deep learning, and the video foundation was createdin the system by using B/ S architecture, WebGIS platform, and PaddleDetection development framework to separate front and back endsservices, algorithm model management, illegal sand mining identification, business supervision and other functions. The system was connect⁃ed to high⁃point river and lake video monitoring equipment to send back images, automatically monitored illegal sand mining in prohibitedmining areas, fixed evidence of illegal sand mining and assisted law enforcement personnel to complete closed⁃loop of illegal sand mining su⁃pervision. Taking the pilot application in Qian’an City as an example, it proves that the system is feasible and improves the supervision leveland efficiency of illegal sand mining.