Sound nuisance in the city is a big problem. Sensing and classifying sounds can provide the necessary information to take effective countermeasures in the city “jungle”. Next to this sound sensing can be very relevant in detecting poaching or loose elephants approaching a village in the real jungle. Together with Waag and Sensing Clues we collaborate on developing sound sensors.
For the more experienced Sensemakers it’s interesting to work on the sound classification sensor. You will use digital signal processing, and deep learning for the classification of sound on the sensor. We see AI moving towards the edge more and more. Together with SensingClues we improved the prototype, however, we still face some challenges:
- Energy consumption is still way to high, draining batteries way too fast and heating up the device. We want to be as free as possible in device placement, indicating a battery powered solution. So, we radically need to find ways to get power consumption and heat production down.
- Price. We want many devices, both in the city and the jungle. At the moment a quite expensive microphone is required, making classification at a greater distance possible.
- Robust design (casing, weather, tamper-proof).
- Various communication options, it the wild we likely need LoRaWan, perhaps even LoRaWan to low orbit satellite. In the cities LoRa (free of charge by TTN, NB-IoT, LTE/M, M2M and perhaps even bursted WiFi are viable options.
- Although a sound classification sensor for the jungle and for the city may differ somewhat in requirements, they can both be worked on. Actually, when the sensor can work in the jungle it certainly will be usable in the city.
So as Sensemakers it is our goal to work with Sensing Clues to further develop a better and cheaper version of their prototype, deploy it in different pilots, share the learnings and publish solutions for others to copy;