Research and exploration on unmanned inspection system for underground cable and pipeline

Underground cable ducts are widely used to protect and place wires and cables, but the environment where they are located is narrow and occluded, which increases the difficulty of manual inspection and makes maintenance work tedious. In response to this issue, this paper designs an unmanned inspection system for underground cable ducts based on machine vision and Internet of Things (IoT) technology. Firstly, the locally trained YOLOv2 target detection model is deployed in Kendryte K210 embedded platform; then based on the temperature and humidity sensor and WiFi module, the temperature and humidity data are uploaded to the AliCloud IoT platform in real time through the MQTT protocol, and real-time monitoring the internal condition of the pipeline. Test results show that the inspection system can effectively complete the unmanned inspection task of cable pipelines, simplify the inspection process, and provide convenience for the staff.