One serious facet of the worsening human-elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions.
This work proposes leveraging recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera mounted on a train or near a known elephant crossing or hotspot. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested.
Project partners include NVIDIA, IEEE SIGHT, UTS, University of Peradeniya and the Sri Lanka Railway Services.