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All Journal Indonesian Journal of Engineering and Science (IJES) Journal of Fuzzy Systems and Control (JFSC)
Nguyen, Hoang-Thong
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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PID-CONTROLLED HUMAN DETECTION ROBOT WITH VISUAL PROCESSING ON ALPHABOT-2 Nguyen, Hoang-Thong; Vo, Quoc-Thang; Le, Minh-Thiet; Truong, Cong-Tuan; Tran, Duy-Dat; Pham, Cong-Hoang-Anh; Cao, Huu-Tai; Lam, Gia-Bao; Truong, Hoang-Anh; Tran, Le-Bao-Luan; Nguyen, Hoang-Quang-Minh; Nguyen, Le-Hoang-Viet; Le, Thi-Hong-Lam
Indonesian Journal of Engineering and Science Vol. 6 No. 2 (2025): Table of Contents
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v6i2.176

Abstract

This paper presents a human detection and alert robot system based on the AlphaBot2 platform and Raspberry Pi. The system employs a camera with a HOG-based human detection algorithm to locate the target within the frame and uses an ultrasonic sensor to measure the distance to the person. Based on the horizontal offset between the person and the frame centre, the PID controller adjusts the speeds of two DC motors to guide the robot smoothly and steadily toward the person. When the robot reaches a predefined distance from the detected human target, a buzzer is triggered. Through experiments, the effectiveness of the image processing and PID algorithm is evaluated, and optimal parameter values are identified for the system.
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 Cao, Huu-Tai Lam, Gia-Bao Le, Hoang-Lam Le, Minh-Thiet Le, Thi-Hong-Lam Nguyen, Hai-Thanh Nguyen, Hoang-Quang-Minh Nguyen, Le-Hoang-Viet Nguyen, Le-Minh-Kha Nguyen, Ngoc-Hung Nguyen, Quang-Khai Nguyen, Quoc-Thuan Nguyen, Thanh-Binh Nguyen, Thanh-Toan Nguyen, Thi-Ngoc-Thao Nguyen, Van-Hiep Pham, Cong-Hoang-Anh Phung, Son-Thanh Tran, Duy-Dat Tran, Le-Bao-Luan Tran, Phuoc-Dat Truong, Cong-Tuan Truong, Hoang-Anh Vo, Quoc-Thang