





Finished! Looks like this project is out of data at the moment!
We're working hard to collect more bird call data for you!
In the mean time why not test your skills on our sister project Frog Find
Summary: Conservation managers can't protect what they don’t know about, but our current ways of tracking biodiversity are random and small-scale. Australia has committed to create a national biodiversity monitoring programme. This has not yet occurred despite the urgent need to monitor common and threatened species, as highlighted by the challenges of determining the biodiversity impacts of the Black Summer fires of 2019/20. With new advancements in automation, smaller devices, and better power sources, the world needs to quickly expand biodiversity monitoring to be organized, thorough, and continuous on a large scale. We propose the BIOMON project to achieve this by using individual sensor devices equipped with machine learning models to identify biodiversity through sound and/or photos. Devices would be set up in networks that send the results back to researchers, who analyze the data and make it available to the public for free. These networks could cover entire continents to measure changes in biodiversity. No one has achieved this yet, and there are still big challenges like training the algorithms, having enough cellular network coverage, balancing sensor power and memory, and deciding where to place the sensors. There's a lot of work to do, but in the 21st century, we can't achieve big goals unless we start working toward them. Hayward et al., 2022. Australian Zoologist