Automated detection of illicit discharges in storm drains using a distributed network of low-cost IoT sensors

A novel, sensor-driven approach that automates the detection of transient illicit discharges in storm drains was piloted across ten storm drain outfalls in southern California. The sensor network continuously monitors key hydrologic and water quality variables. An automated algorithm utilizing a differential exponentially weighted moving average model was deployed to identify trends that indicate a potential illicit discharge. When a potential discharge is detected, an email alarm notifies stormwater managers in near-real-time. The manager may view the data immediately via a custom visualization dashboard and/or follow up in-person at the offending site. Rapid responses enabled by automated detection greatly improve the likelihood that intermittent illicit discharges will be detected, traced and eliminated. Results from the pilot program show that the open-source, 3D printed, internet-of-things (IoT)-enabled sensors utilized herein offer a financially viable product, facilitating widespread network coverage for automated illicit discharge detection in resource-limited programs.