MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641058148 A) filed by Dr. Arulprakash M; S Vjna Y Kumar; and Karneedi Bogeswar on May 07, 2026, for Wildtrackai: Gpu-Accelerated Footprint-Based Wildlife Monitoring Using Computer Vision.
Inventors include Dr. Arulprakash M; S Vjna Y Kumar; and Karneedi Bogeswar.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Abstract WildTrackAI leverages advanced computer vision techniques to automate the classification of animal footprints, offering a novel solution for wildlife researchers and conservationists. Traditional methods of footprint analysis are often labor-intensive and subject to human error, which can lead to inaccuracies in species identification and behavioural studies. By employing 1 0 deep learning algorithms, WildTrackAI aims to enhance the efficiency and precision of footprint classification, enabling faster data collection and analysis in ecological studies. The ------ projectinvolves tfie aevelopmenC of a robust convolutional neural networlc(CNN)-modei-- ----- - trained on a diverse dataset of animal footprints, which includes various species across different terrains. This dataset is meticulously curated to ensure comprehensive representation and to 15 facilitate the model's ability to generalize across different environmental conditions. The model's architecture is designed to extract distinctive features from the footprints, allowing it to effectively differentiate between species and even individual animals. WildTrackAI's implementation will significantly contribute to ecological monitoring and wildlife management by providing timely and accurate data for conservation efforts. By streamlining the process of 20 footprint classification, this project not only aids researchers in their fieldwork but also promotes greater awareness and understanding of biodiversity and animal behaviour. The potential applications extend beyond research, offering tools for ecological education and citizen science initiatives, thereby fostering a deeper connection between communities and their local wildlife.
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