Design and Implementation of an IoT-Enabled Autonomous Fire-Fighting Robot Using Vision-Based Fire Detection - 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 (Peneliti Teknologi Teknik Indonesia, 2025)
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.