Development of Real Time Underground Monitoring System Using Unmanned Vechile

The cave environment plays a crucial role in research across geology, biology, ecology, hydrology, and cultural anthropology. This project aims to develop an unmanned vehicle using IoT and Raspberry Pi technologies to monitor cave conditions and transmit data via GPS. The vehicle will detect environmental parameters such as air quality, temperature, humidity, lighting, objects, and soil condition using integrated sensors and AI algorithms. Designed for safe navigation, the unmanned vehicle identifies hazards like air pollution, darkness and autonomously retreats to avoid damage. The unmanned vehicles have become more reliable and practical for cave exploration. This system will assist in identifying dangers like collapses, flooding, landslides, and low oxygen zones, enhancing safety in cave exploration. The vehicle is designed to operate in confined and harsh environments, ensuring reliable performance in challenging cave conditions. Robust sensors ensure precise detection of environmental parameters, even in low-light or obstructed areas. This innovative solution bridges the gap between manual cave exploration and modern technological advancements. Key Words: Sensor Fusion, Internet of things, Remote Sensing , Artificial Intelligence, Hazard Detection