Drainage network sedimentation management methods, systems, and medium based on large internet of things models

A drainage network sedimentation management method based on a large Internet of Things (IoT) model, wherein the method is executed by an emergency supervision management platform, and the method comprises:

• acquiring flow data of a pipe section by an acquisition device deployed in a drainage network, and obtaining the flow data uploaded by the acquisition device;
• determining a flow cross-sectional area series of a plurality of adjacent pipe sections based on the flow data of the pipe section;
• determining an anomalous pipe section and an anomalous flow passage moment based on the flow cross-sectional area series of the plurality of adjacent pipe sections;
• determining a target detection area and a target detection time based on the anomalous pipe section and the anomalous flow passage moment;
• controlling, by an emergency supervision object platform, a robot to perform sonar detection on the target detection area at the target detection time, and acquiring sonar detection data, wherein the robot is equipped with a sonar sensor;
• generating an estimated sedimentation thickness and a sedimentation type of the target detection area based on the sonar detection data and pipe characteristics;
• determining a sedimentation risk based on the estimated sedimentation thickness, the sedimentation type, and the pipe characteristics;
• automatically generating a desilting path and desilting parameters based on the sedimentation risk;
• controlling, by the emergency supervision object platform, automated desilting equipment to travel along the desilting path to a desilting operation point, and performing a desilting operation based on the desilting parameters.

A computer-readable storage medium storing computer instructions, wherein when a computer reads the computer instructions in the storage medium, the computer executes a method for a drainage network sedimentation management based on a large Internet of Things (IoT) model, comprising:

• acquiring flow data of a pipe section by an acquisition device deployed in a drainage network, and obtaining the flow data uploaded by the acquisition device;
• determining a flow cross-sectional area series of a plurality of adjacent pipe sections based on the flow data of the pipe section;
• determining an anomalous pipe section and an anomalous flow passage moment based on the flow cross-sectional area series of the plurality of adjacent pipe sections;
• determining a target detection area and a target detection time based on the anomalous pipe section and the anomalous flow passage moment;
• controlling, by an emergency supervision object platform, a robot to perform sonar detection on the target detection area at the target detection time, and acquiring sonar detection data, wherein the robot is equipped with a sonar sensor;
• generating an estimated sedimentation thickness and a sedimentation type of the target detection area based on the sonar detection data and pipe characteristics;
• determining a sedimentation risk based on the estimated sedimentation thickness, the sedimentation type, and the pipe characteristics;
• automatically generating a desilting path and desilting parameters based on the sedimentation risk;
• controlling, by the emergency supervision object platform, automated desilting equipment to travel along the desilting path to a desilting operation point, and performing a desilting operation based on the desilting parameters.