BATECHOMON: INDIA’S FIRST AUTOMATED BAT MONITORING SYSTEM

UPSC Relevance

GS-3: Environment & Ecology – Biodiversity Monitoring

GS-3: Science & Tech – AI in Ecological Research

GS-2: Governance – Science in Conservation Policy

Key Highlights

System Overview

Name: BatEchoMon (Bat Echolocation Monitoring)

Developers: Kadambari Deshpande and Vedant Barje

Institution: Long-Term Urban Ecological Observatory, IIHS, Bengaluru

Tech: Raspberry Pi, ultrasonic detector, neural network model

Functionality

• Activates at sunset to detect and record bat calls in real time.
• Uses neural networks to identify species, isolating calls from ambient noise.
• Currently identifies 6–7 common Indian bat species.

Significance

1. Ecological Impact
2. Addresses gaps in bat ecology and acoustic monitoring.
3. Shifts from manual to automated call analysis.
4. Informs conservation by mapping bat distribution and behavior.
5. Technological Advantage

• Portable, modular design suited for long-term use in diverse habitats.
• Challenges and Future Scope
• Limited to 6–7 species due to small dataset.
• Requires expanded reference libraries and testing across environments.
• Plans to scale species library and deploy across Indian ecosystems.

Innovative Edge

1. Marks India’s advance in AI-driven biodiversity monitoring.
2. Supports data-driven wildlife policies.
3. Could inspire acoustic monitoring for other species.