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India’s First Automated Bat Monitoring System: BatEchoMon, developed by IIHS Bengaluru, is India’s first real-time automated system for bat monitoring and detection.
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Saves Significant Time: BatEchoMon dramatically reduces data processing time for bat echolocation calls from months to hours, previously a major bottleneck.
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How it Works: BatEchoMon uses ultrasonic microphones (modified AudioMoth), a Raspberry Pi microprocessor, solar power, and Wi-Fi for data transmission.
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AI-Powered Analysis: It employs a convolutional neural network (CNN) to distinguish bat calls from other sounds and classify them by species based on call structure.
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Detailed Output: Generates spectrograms, audio files, and species-specific statistical data on bat calls, frequency, and timing.
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Impact on Research: BatEchoMon allows researchers to focus on bat ecology and ask more in-depth questions instead of being bogged down by data processing.
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Globally Significant: Experts suggest that BatEchoMon’s in-built recording and call classifying unit could be a milestone in global bat research.
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Cost-Effective: The core system is designed to be more affordable than advanced detectors and similar systems, making it more accessible.
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Current Limitations: The primary challenge is the limited reference libraries for the calls of many Indian bat species; currently identifies 6-7 common species.
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Future Goals: Expanding the system to identify more bat species and creating robust training datasets through collaboration.
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Application: Useful in urbanization/climate.
