Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Fuzzy Systems and Control (JFSC)
Nguyen, Thi-Ngoc-Thao
Unknown Affiliation
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Fuzzy Systems and Control (JFSC)

 1 
Design and Implementation of an IoT-Enabled Autonomous Fire-Fighting Robot Using Vision-Based Fire Detection Nguyen, Hoang-Thong; Nguyen, Quoc-Thuan; Tran, Phuoc-Dat; Nguyen, Quang-Khai; Le, Thi-Hong-Lam; Nguyen, Le-Minh-Kha; Nguyen, Van-Hiep; Nguyen, Thanh-Binh; Nguyen, Ngoc-Hung; Nguyen, Thi-Ngoc-Thao; Phung, Son-Thanh; Le, Hoang-Lam; Nguyen, Thanh-Toan; Nguyen, Hai-Thanh
Journal of Fuzzy Systems and Control Vol. 3 No. 3 (2025): Vol. 3 No. 3 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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.
Co-Authors Le, Hoang-Lam Le, Thi-Hong-Lam Nguyen, Hai-Thanh Nguyen, Hoang-Thong Nguyen, Le-Minh-Kha Nguyen, Ngoc-Hung Nguyen, Quang-Khai Nguyen, Quoc-Thuan Nguyen, Thanh-Binh Nguyen, Thanh-Toan Nguyen, Van-Hiep Phung, Son-Thanh Tran, Phuoc-Dat