IoT-Based Blockages Detection in Stormwater Drains

Flooding is an issue that affects many cities during periods of heavy rain, especially in developing countries. This issue often happens due to the lack of timely maintenance and cleaning of rainwater drains. This work presents a proposal to detect blockages in rainwater drains to determine where maintenance and cleaning need to be done promptly. An architecture that includes sensor nodes, a Gateway, and a cloud application was defined. The sensor nodes, which detect potential blockages in the drains, send data and status signals to the Gateway using LoRaWAN. The Gateway then passes the data to a cloud platform that records the data and issues an alert when a blockage is detected in a drain. The sensor node prototype is based on a Heltec LoRa Wifi board and has two sensors: an HC-SR04 ultrasonic sensor to measure distance and a DHT22 sensor to measure humidity and temperature. The cloud application was developed on the Arduino Cloud platform. A decision tree is proposed to detect blockages based on the readings from these sensors, particularly the distance sensor, considering four possible states: clear, possibly blocked, potentially blocked, and blocked. The decision tree is implemented in each node. Periodically, the node collects data from the sensors and transmits it to the cloud, and if a potential blockage is detected, it sends a message that triggers an alert on the platform. Preliminary tests of the prototype show accurate and timely results in detecting potential blockages, allowing for better use of resources allocated for maintaining drainage systems.