A low-cost device that listens to water pipes and finds hidden leaks.

Tunisia loses close to a third of its drinking water to leaks in old underground pipes, and a leak stays invisible until a pipe bursts or a bill jumps. EchoDrop is a small sensor that clips onto a pipe and listens. A leak makes a faint, steady sound inside the pipe that people can't hear. EchoDrop picks it up, tells a leak apart from normal water use, and sends an alert so it gets fixed before the water is gone.

I'm from Tunisia, where water is scarce and a lot of it is lost this way, so this is the problem I wanted to work on.

Three parts: a contact microphone on the pipe, an ESP32 that runs the detection, and an alert (a buzzer or a WiFi notification). The hard part is the software that decides "leak" or "normal" from the sound. It looks at three things: how continuous the sound is, how much its energy varies over time, and where its energy sits in frequency. A leak is steady and broadband; normal use is short and bursty.

echodrop_demo.py builds simulated pipe signals (a steady leak hiss, normal taps, and a steady appliance hum as a hard case), pulls out those features, and trains a small classifier. On this simulated set it reaches an F1 around 0.88. Most of the errors are the appliance hum mistaken for a leak, which is the real challenge and the next thing to solve.

Run it:

pip install numpy matplotlib
python3 echodrop_demo.py

It writes echodrop_signaux.png (what the sounds look like) and echodrop_detection.png (how the two separate, plus the confusion matrix).

These are simulated signals to show the method works, not field recordings. Real pipe audio will be noisier, and validating on it is the next step.

Early prototype. The detection runs on simulated audio, and the physical device isn't built yet. Next steps: record real leak and non-leak audio, build a first unit on an ESP32, and test it on a real pipe.

MIT. See LICENSE.