Open AccessShazam for bats: Internet of Things for continuous real‐time biodiversity monitoring
Author(s) -
Gallacher Sarah,
Wilson Duncan,
Fairbrass Alison,
Turmukhambetov Daniyar,
Firman Michael,
Kreitmayer Stefan,
Mac Aodha Oisin,
Brostow Gabriel,
Jones Kate
Publication year - 2021
Publication title -
iet smart cities
Language(s) - English
Resource type - Journals
ISSN - 2631-7680
DOI - 10.1049/smc2.12016
Subject(s) - human echolocation , biodiversity , field (mathematics) , computer science , environmental monitoring , internet of things , continuous monitoring , environmental resource management , enhanced data rates for gsm evolution , citizen science , data science , real time computing , computer security , ecology , artificial intelligence , environmental science , business , biology , botany , mathematics , finance , neuroscience , pure mathematics
Biodiversity surveys are often required for development projects in cities that could affect protected species such as bats. Bats are important biodiversity indicators of the wider health of the environment and activity surveys of bat species are used to report on the performance of mitigation actions. Typically, sensors are used in the field to listen to the ultrasonic echolocation calls of bats or the audio data is recorded for post‐processing to calculate the activity levels. Current methods rely on significant human input and therefore present an opportunity for continuous monitoring and in situ machine learning detection of bat calls in the field. Here, we show the results from a longitudinal study of 15 novel Internet connected bat sensors—Echo Boxes—in a large urban park. The study provided empirical evidence of how edge processing can reduce network traffic and storage demands by several orders of magnitude, making it possible to run continuous monitoring activities for many months including periods which traditionally would not be monitored. Our results demonstrate how the combination of artificial intelligence techniques and low‐cost sensor networks can be used to create novel insights for ecologists and conservation decision‐makers.