Design and Implementation of an IoT-Enabled Autonomous Fire-Fighting Robot Using Vision-Based Fire Detection
Keywords:
Mobile Robot, Fire-Fighting, Image Processing, Mobile Application, SLAM, IoTAbstract
This paper presents the design and implementation of an IoT-enabled autonomous fire-fighting mobile robot for early hazard detection, remote monitoring, and emergency response. The proposed system integrates real-time deep learning–based fire detection using a YOLO model with fire and gas sensor–based monitoring for IoT-based alert transmission and SLAM-based environmental visualization to form a multifunctional robotic platform capable of performing a sequence of tasks from detection and warning to initial fire response. The robot is capable of autonomous movement with obstacle avoidance, while a 2D SLAM-based mapping module is employed to provide environmental visualization for monitoring and decision support. A mobile application enables remote supervision and control, and real-time alerts are delivered through an IoT platform to enhance situational awareness. Experimental results show that the proposed system achieves a fire detection and response success rate of approximately 70%, with reliable fire recognition and fast response time under indoor testing conditions. The developed robot demonstrates strong potential as a practical solution for improving safety and supporting early-stage fire response in residential and industrial environments.
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Copyright (c) 2025 Hoang-Thong Nguyen, Quoc-Thuan Nguyen, Phuoc-Dat Tran, Quang-Khai Nguyen, Thi-Hong-Lam Le, Le-Minh-Kha Nguyen, Van-Hiep Nguyen, Thanh-Binh Nguyen, Ngoc-Hung Nguyen, Thi-Ngoc-Thao Nguyen, Son-Thanh Phung, Hoang-Lam Le, Thanh-Toan Nguyen, Hai-Thanh Nguyen
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