A beehive monitoring system based on the Helium Developer Kit and a RasPi with Seed’s 2-Mics ReSpeaker PiHat for audio acquisition and basic audio analysis with classification of queenless vs. with queen. Telemetry is done via the Helium network (it’s based on LoRaWAN).

[image source: https://www.hackster.io/354300/longhive-12d952]

Project description

Source Code

Audio analysis

Audio analysis was realized a bit cumbersome: First convert audio to a graphical representation, in this case a spectrogram, then analyse this graphics with deep learning, in this project a pre-trained Tensorflow Lite Interpreter.

[image source: https://www.hackster.io/354300/longhive-12d952]


Beside weight and temperature they measured CO2 and air quality . Unfortunately they used the worst weight sensor you can get, the unreliable bathroom sensors:

LongHive won 2 500 $ and some stuff (hardware, data plan) from the sponsore Helium on contest from hackster.io. Congratz!