IOT BASED BORDER SECURITY SYSTEM USING MACHINE LEARNING

Artificial Intelligence and Machine Learning

The troops' health tracking and monitoring system serves as the foundation for this project. The suggested system, which consists of tiny wearable physiological equipment sensors and transmission modules, can be worn on a soldier's jacket to track their location and health state using GPS. The information is then sent to the control room via IOT and ML. The idea of physical borders between countries is no longer relevant due to globalization and the mobility of global inhabitants. Physical borders that are based on artillery and heavily armed take a lot of labour, are prone to human error, and in some rough areas, may even affect the ecosystem. The goal of this study is to provide a novel "Smart Border" with an integrated Intruder Alert system as an alternative to physical barriers. Alert system that uses cutting-edge surveillance technology in place of armed and physical patrolling. Without the need for costly, human-and technologically-intensive physical barriers and heavily armed patrols, this technology could address border security concerns. The proposed system uses sensors, thermal imaging, and surveillance cameras to identify intruders, distinguish them from soldiers and patrol officers using machine learning, and notify officials in the event of an emergency.

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