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Journal : Journal of Fuzzy Systems and Control (JFSC)

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 | DOI: 10.59247/jfsc.v3i3.354

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.
Intelligent Control for 2D-Crane System Huynh, Trung-Son; Dinh, Dang-Khoa; Tran, Trong-Bang; Dang, Huu-Loc; Le, Dinh-Nguyen-Phuc; Bui, Hung-Thinh; Le, Hoang-Lam; Nguyen, Thanh-Binh; Nguyen, Van-Hiep; Nguyen, Le-Nhat-Minh; Dang, Thien-Quoc; Nguyen, Ngoc-Hung; Nguyen, Thi-Ngoc-Thao; Pham, Huynh-Duc; Nguyen, Xuan-Tien; Nguyen, Van-Dong-Hai
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.350

Abstract

This paper presents an Intelligent Learning-based Control approach for a 2D Crane System, aiming to evaluate the learning capability of various intelligent techniques based on a baseline Fuzzy Logic Controller (FLC). The initial fuzzy controller is designed for position and sway control, while Genetic Algorithm (GA), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS) are employed in simulation to retrain and enhance its performance. Comparative results show that intelligent learning methods can significantly improve system response, reduce overshoot, and increase robustness compared to the original fuzzy controller. Moreover, an experimental setup using the baseline FLC is implemented to verify the practical effectiveness of the fuzzy control approach on a real 2D crane system. The findings highlight the potential of intelligent learning techniques for future real-time implementation.
Development of an Automated PCB Inspection, Error Statistics, and Classification System Phan, Truong-Nguyen; Tran, Thi-Ngoc-Tram; Ho, Thanh-Viet; Nguyen, Binh-Hau; Hoang, Minh-Tri; Tran, Hai-Nam; Nguyen, Nhat-Nam; Tran, Nguyen-Cong-Anh; Do, Le-Huu-Tri; Nguyen, Thi-Ngoc-Thao; Tran, Nam-Long; Nguyen, Duong-Thuan; Le, Van-Huy; Nguyen, Van-Tuan; Pham, Huynh-Anh-Tuan
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.353

Abstract

In the electronics manufacturing industry, Printed Circuit Boards are critical to electronic devices, and their quality directly affects product performance and reliability. Common assembly defects, such as missing components, misalignment, or wrong parts, must be detected promptly to reduce waste and maintain reputation. In Vietnam, PCB inspection is largely manual, limiting speed, accuracy, and consistency. The system integrates a YOLOv5-based machine vision module for detecting missing and misaligned components, a Siemens S7-1200 PLC for controlling an XY gantry and conveyor system, and a web interface for real-time monitoring. The primary contributions include: a fully integrated cyber-physical prototype suitable for educational and small-scale industrial use; a novel method for component misalignment detection using fiducial-based relative positioning; and seamless communication between vision, control, and HMI modules. Experimental results on two common PCB types, L298N and ULN2003, demonstrate a classification and error detection accuracy of up to 93%. The system achieves a throughput suitable for laboratory and small-batch production, with a positioning accuracy of ±0.5 mm. The system aims to achieve high accuracy, fast processing, and practical applicability in production lines.
An Enhanced PID-Based Motion Control Framework for Autonomous Line-Following Robot Tran, Nguyen-Thanh-Loc; Bui, Viet-Tien-Dung; Bui, Hong-Nho; Nguyen, Hoang-Nguyen; Nguyen, Thi-Ngoc-Thao; Nguyen, Thanh-Sang; Nguyen, Hung-Ky; Nguyen, Huynh-Duc-Anh; Phan, Thanh-Binh; Luong, Hoang-Sang; Nguyen, Le-Minh-Tan; Tran, Vo-Minh-Khoa; Nguyen, Tien-Dat; Pham, Huynh-Khanh-Nam; Nguyen, Duc-Dat; Nguyen, The-Nhan
Journal of Fuzzy Systems and Control Vol. 4 No. 1 (2026): Vol. 4 No. 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jfsc.v4i1.368

Abstract

PID controller is widely used in automatic control systems because it is simple, reliable, and easy to apply. It is especially suitable for mobile robots, such as line-following robots. The main contribution of this work is an experimental method to tune PID parameters. Instead of using complex algorithms, the parameters are adjusted and tested directly on a real robot. This makes the method easier to apply, especially for low-cost and educational systems. Experiments were conducted to evaluate how PID parameters (Kp, Ki, and Kd) affect the robot’s performance. The robot was tested on different paths, including straight lines, curves, and 90-degree turns. The results show that the optimal parameters are Kp = 65, Ki = 0.1, and Kd = 13. With these values, the robot moves smoothly, responds quickly, and follows the path accurately.
Co-Authors Bui, Hong-Nho Bui, Hung-Thinh Bui, Viet-Tien-Dung Dang, Huu-Loc Dang, Phuc-Khanh Dang, Thien-Quoc Dang, Tran-Gia-Bao Dieu, Nghia Dinh, Dang-Khoa Do, Le-Huu-Tri Do, Ngoc-Huy Ho, Thanh-Phuong Ho, Thanh-Viet Hoang, Minh-Giap Hoang, Minh-Tri Hong, Vi-Cuong Huynh, Anh-Tuan Huynh, Trung-Son Lam, Xuan-Minh-Nhat Le, Dinh-Duc-Vinh Le, Dinh-Nguyen-Phuc Le, Hoang-Lam Le, Hoang-Linh Le, Hoang-Nhat-Huy Le, Ngoc-Long Le, Quoc-Tuan Le, Thi-Hong-Lam Le, Thi-Thanh-Hoang Le, Tuan-Kiet Le, Van-Huy Le, Xuan-Cuong Lieu, Vinh-Hung Luong, Hoang-Sang Nguyen, Anh-Huy Nguyen, Anh-Tuan Nguyen, Binh-Hau Nguyen, Duc-Dat Nguyen, Duong-Thuan Nguyen, Ha-Thien-Phuc Nguyen, Hai-Thanh Nguyen, Hoang-Nguyen Nguyen, Hoang-Thong Nguyen, Hung-Ky Nguyen, Huynh-Duc-Anh Nguyen, Huynh-The-Hung Nguyen, Kieu-Vinh Nguyen, Le-Anh-Tuan Nguyen, Le-Minh-Kha Nguyen, Le-Minh-Quan Nguyen, Le-Minh-Tan Nguyen, Le-Nhat-Minh Nguyen, Minh-Khoa Nguyen, Minh-Tam Nguyen, Ngoc-Hung Nguyen, Nhat-Nam Nguyen, Phong-Luu Nguyen, Quang-Khai Nguyen, Quang-Thien Nguyen, Quoc-Bao Nguyen, Quoc-Thuan Nguyen, Thanh-Binh Nguyen, Thanh-Sang Nguyen, Thanh-Toan Nguyen, The-Nhan Nguyen, Tien-Dat Nguyen, Truong-Viet Nguyen, Van-Bac Nguyen, Van-Dong-Hai Nguyen, Van-Hai Nguyen, Van-Hiep Nguyen, Van-Tuan Nguyen, Xuan-Tien Pham, Gia-Loc Pham, Huynh-Anh-Tuan Pham, Huynh-Duc Pham, Huynh-Khanh-Nam Pham, Ngoc-Bao Pham, Truong-Phuong-Nam Phan, Thanh-Binh Phan, Truong-Nguyen Phu, Thi-Ngoc-Hieu Phung, Son-Thanh Tran, Hai-Nam Tran, Huu-Nhan Tran, Nam-Long Tran, Nguyen-Cong-Anh Tran, Nguyen-Thanh-Loc Tran, Phuoc-Dat Tran, Quang-Huy Tran, Thi-Ngoc-Tram Tran, Trong-Bang Tran, Van-Toan Tran, Vo-Minh-Khoa Truong, Nhat-Bang Truong, Tuan-Minh Vo, Binh-An Vu, Bao-Huy