Advancing Animal Behavior Analysis Using Accelerometer Data

The chapter explores the utilization of raw accelerometer data to analyze animal behaviors, detailing the challenges of handling large datasets and manually annotating behaviors. It delves into the process of supervised learning with data loggers to predict animal behaviors, focusing on distinguishing behaviors of kangaroo rats and studying rattlesnakes' eating habits. The speakers discuss the deployment of data loggers across different geographic locations to gather detailed behavior data and hint at the potential use of AI for enhanced data analysis in future research.