AI-Driven Robotics for Sustainable Solutions in Disaster Management - Lakshay Malik (International Journal of Advanced Robotics and Automation Technology, 2025)
Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper explores the use of AI-driven robotics in disaster management, focusing on sustainable solutions that enhance the efficiency and effectiveness of disaster response and recovery operations. AI-powered robots can be deployed for a wide range of tasks, including search and rescue operations, damage assessment, and environmental monitoring. These robots leverage AI algorithms to navigate hazardous environments autonomously, analyze vast amounts of data in real-time, and assist emergency responders without putting human lives at risk. Furthermore, the ability to process and interpret data from multiple sensors allows these robots to provide valuable insights for decision-making in critical situations. This article delves into various AI-driven robotic systems currently in use or under development, such as autonomous drones, ground robots, and swarm robotics, examining their roles in disaster response. Case studies from real-world disaster scenarios illustrate the impact of these technologies in saving lives, optimizing resource allocation, and reducing response times. Additionally, the paper addresses the potential for scalability and sustainability of AI robotics in disaster management, highlighting the need for collaboration between governments, industries, and research institutions to ensure these technologies are accessible and affordable. Ultimately, this paper argues that AI-driven robotics have a pivotal role in advancing sustainable disaster management practices, fostering resilience in vulnerable communities, and reducing the long-term effects of catastrophic events.
Keywords: Deep Learning; Machine Learning; artificial intelligence; disaster management; human–robot interaction