aihub.org
 

AI-assisted camera system to monitor seabird behaviour

by
06 November 2020



share this:
Seagulls flying | AIhub

Researchers from Osaka University have combined bio-logging cameras with a machine learning algorithm to help them to shed light on hidden aspects of the lives of seabird species, including gulls and shearwaters.

Bio-logging is a technique involving the mounting of small lightweight video cameras and/or other data-gathering devices onto the bodies of wild animals. These systems allow researchers to observe various aspects of animals’ lives, such as behaviours and social interactions, with minimal disturbance.

However, the considerable battery life required for these high-cost bio-logging systems has proved limiting so far. “Since bio-loggers attached to small animals have to be small and lightweight, they have short runtimes and it was therefore difficult to record interesting infrequent behaviours,” explains study corresponding author Takuya Maekawa.

By using AI-assisted bio-loggers, researchers can use low-cost sensors to automatically detect behaviours of interest in real time, allowing them to conditionally activate high-cost (i.e., resource-intensive) sensors to target those behaviours.

The researchers have put together this video to explain how their system works:

The researchers used a random forest classifier algorithm to determine when to switch on the high-cost sensors. Their model uses accelerometer-based features, which can be used to detect the body movements of the animals with only a small (e.g., 1 second) delay between when data collection begins and when behaviours can first be detected. Features from accelerometers were used to train the model to detect whether the birds were flying, stationary or foraging.

You can see three examples of the camera in action below:

Read the research in full

Machine learning enables improved runtime and precision for bio-loggers on seabirds
Joseph Korpela, Hirokazu Suzuki, Sakiko Matsumoto, Yuichi Mizutani, Masaki Samejima, Takuya Maekawa, Junichi Nakai & Ken Yoda




Lucy Smith , Managing Editor for AIhub.
Lucy Smith , Managing Editor for AIhub.




            AIhub is supported by:


Related posts :



Eleven new NSF artificial intelligence research institutes announced

USA National Science Foundation (NSF) partnerships expand National AI Research Institutes to 40 states.
30 July 2021, by

AIhub monthly digest: July 2021 – ICML, protein folding for all, and AI Song Contest winner announced

Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.
29 July 2021, by

Use of AI to fight COVID-19 risks harming “disadvantaged groups”, experts warn

Rapid deployment of AI to tackle coronavirus must still go through ethical checks and balances.
28 July 2021, by


















©2021 - Association for the Understanding of Artificial Intelligence














©2021 - Association for the Understanding of Artificial Intelligence- aihub.org