IoT-BASED REMOTE SURVEILLANCE FOR ANIMAL TRACKING NEAR RAILWAY TRACKS ARDUINO
DOI:
https://doi.org/10.63458/ijerst.v3i4.133Keywords:
Allocation, Artificial Intelligence, Deep Learning, Metaheuristic AlgorithmsAbstract
Railway tracks traversing through natural habitats bring forth a critical concern: the potential for collisions between trains and wildlife. This challenge necessitates innovative solutions to safeguard both the animal populations and the safety of railway operations. In response, this research introduces an ingenious approach—an IP camera based remote surveillance system tailored for animal tracking in close proximity to railway tracks. By harnessing cutting-edge technology, this system offers the promise of reducing animal fatalities and preventing hazardous train incidents. Central to this proposed solution is the utilization of an Adriano microcontroller intricately linked to a trio of sensors: an ultrasonic sensor, a Micro-Electro-Mechanical Systems (MEMS) sensor, and a Passive Infrared (PIR) sensor. This triumvirate of sensors collaborates seamlessly to discern the presence of animals within the vicinity of railway tracks. The ultrasonic sensor, adept at calculating distances by emitting and receiving sound waves, serves as the system's first line of defence in identifying potential collisions. The MEMS sensor, designed to detect even the minutest movements, further refines the system's by distinguishing between animals and stationary objects. Augmenting this ensemble, the PIR sensor operates as a thermal detector, responding to heat signatures and amplifying the system's capacity to identify.
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Copyright (c) 2026 G. Naga Chaitnya Kumar Reddy, Tharun Kumar Reddy, D Surendra
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