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Dr. Pankaj H. Chandankhede is a faculty member in the Department of Electronics and Telecommunication Engineering at G H Raisoni College of Engineering, Nagpur, India. His research focuses on embedded systems, IoT, wireless communication, and disaster management technologies.
The rising prevalence and severity of natural and anthropogenic disasters underscore the necessity for intelligent systems that facilitate swift, precise, and data-informed decision-making. Artificial Intelligence (AI)-driven Decision Support Systems (DSS) amalgamate machine learning, deep learning, Internet of Things (IoT), remote sensing, Geographic Information Systems (GIS), cloud computing, big data analytics, drones, and digital twin technologies to enhance disaster preparedness, risk evaluation, emergency response, and post-disaster recovery. These systems evaluate real-time environmental, geographical, and operational data to forecast disasters, optimise resource distribution, improve situational awareness, and coordinate emergency operations. AI-driven Decision Support Systems empower governments, emergency management agencies, healthcare professionals, and humanitarian organisations to make prompt and educated decisions, therefore reducing loss of life, infrastructure damage, and economic repercussions. This chapter examines the principles, designs, applications, problems, and future trajectories of AI-driven decision support systems in disaster management and emergency response, highlighting their significance in fostering resilient and catastrophe-prepared communities.