• Goal: To reduce human-elephant conflicts (HEC) and accidental deaths (e.g., train collisions) by providing early detection and alert systems.
• Core Technology: A IOT combined with machine learning models that recognize elephants.
• Unique Feature: A non-visual, camera-free detection approach that is resilient to poor visibility, weather, and low-light conditions.

To create an AI-powered, low-cost, and scalable solution that protects elephants and humans by enabling real-time, non-invasive wildlife monitoring.

• Develop and deploy Organic signatue-based elephant detection systems using IoT and machine learning.
• Provide real-time alerts to wildlife officials and villagers in conflict zones.
• Contribute to conservation research by collecting elephant odor datasets for future ecological studies.

Our supervisor and valuable domain experts are involved in the projects

• Supervisor: Mr. Saliya Wickramasinghe

-Prof. -Dr.

We are a group of 5 members in domains software engineering, embedded systems, UI/UX design, and wildlife research:

• Akila Wanninayake – Project Lead / Research / Backend & Architecture
• Bhanuka Chathuranga – Machine Learning & Data Processing
• Sampath Dissanayake – IoT & Device Firmware and Project Management
• Piyumi Paranavithanage – Testing, Deployment & Documentation
• Kaushika Weerakoon – UI/UX & Frontend / IOT and Integration

We welcome collaboration and input from:

• Wildlife conservationists
• Electronics engineers
• AI/ML researchers
• Software developers

If you have ideas or want to contribute, please reach out to us via GitHub Discussions or Contact.

• Research Proposal: docs/proposal.pdf
• Figma UI Design: Link to Figma
• Research Papers & References: docs/references

This is an academic and research project. © 2025 ELE-SCENT Team. All rights reserved.