Design and Implementation of Autonomous Firefighting Rover

The firefighting rover is built to work in dangerous fire situations where it's too risky for firefighters to be directly involved. It uses a four-wheel design to move over rough terrains and handle high temperatures, making it suitable for places like forests, mountains, uneven roads, and caves. The rover is equipped with a Raspberry Pi and other components to detect fires using image recognition. It has a water tank and hose system to spray water on the fire, with a motor to pump the water and move the rover. A gas sensor helps detect toxic gasses in the area, and everything is controlled by an Arduino Uno. The rover is enclosed in a strong, simple design. The system is trained with 3,000 examples of fire, gas, and smoke, allowing it to be about 90% accurate in detecting hazards, with results recorded for reference.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/isense63713.2024.10872198
Primary Topic
Marine and Coastal Research
Type
article
Field-Weighted Citation Impact
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article

Design and Implementation of Autonomous Firefighting Rover

D. Ram Nivas, M. Kathirvelu, T. Sajitha, S. Sowmithra
Marine and Coastal Research
article

Design and Implementation of Autonomous Firefighting Rover

D. Ram Nivas, M. Kathirvelu, T. Sajitha, S. Sowmithra
article en

Abstract

The firefighting rover is built to work in dangerous fire situations where it's too risky for firefighters to be directly involved. It uses a four-wheel design to move over rough terrains and handle high temperatures, making it suitable for places like forests, mountains, uneven roads, and caves. The rover is equipped with a Raspberry Pi and other components to detect fires using image recognition. It has a water tank and hose system to spray water on the fire, with a motor to pump the water and move the rover. A gas sensor helps detect toxic gasses in the area, and everything is controlled by an Arduino Uno. The rover is enclosed in a strong, simple design. The system is trained with 3,000 examples of fire, gas, and smoke, allowing it to be about 90% accurate in detecting hazards, with results recorded for reference.

KPR Institute of Engineering and Technology (IN)
Openalex Percentile: Top 64%
Marine and Coastal Research
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