DEVELOPMENT OF ARTIFICIAL INTELLIGENCE-BASED ROBOTS FOR RESCUE TASKS AT DISASTER LOCATIONS - Achmad Nashrul Waahib; Iwan Ady Prabowo; Kusnadi Kusnadi; Antoni Pribadi; Syafiq Amir (Journal of Moeslim Research Technik, 2025)
The increasing frequency of natural disasters highlights the urgent need for efficient rescue operations. Traditional methods often face limitations in accessing hazardous areas, making the development of intelligent robotic systems essential for enhancing rescue efforts. This research focuses on creating an AI-based robot specifically designed for search and rescue tasks in disaster-stricken locations. The primary aim of this study is to develop a robotic system that utilizes artificial intelligence to navigate complex environments, identify survivors, and deliver essential supplies. The research seeks to evaluate the robot's effectiveness in real-world scenarios and its potential to improve response times during emergencies. A systematic approach was employed, combining hardware design and software development. The robot was equipped with advanced sensors, machine learning algorithms, and autonomous navigation capabilities. Field tests were conducted in simulated disaster environments to assess the robot's performance in detecting obstacles, locating victims, and executing rescue tasks. The AI-based robot demonstrated a 90% success rate in locating simulated survivors and effectively navigating through obstacles. Response times were significantly reduced compared to traditional methods, showcasing the robot's potential to enhance rescue operations in real emergencies. This research successfully developed an AI-driven robotic system for search and rescue tasks, demonstrating its effectiveness in improving operational efficiency.