Authors: Rishav Bairagya, Barshan Kundu, Arghya Biswas, Nikhilesh Sil
Abstract: Artificial intelligence (AI)-based emergency response systems provide emerging as key enablers of smart infrastructure safety, improved real-time decision-making, risk assessment, and catastrophe mitigation tactics across multiple domains. The combination of machine learning (ML), deep learning (DL), computer vision, IoT-enabled predictive analytics, and AI-powered robotics in optimising emergency response mechanisms is examined in this systematic literature review, which includes more than 100 eligible papers. In addition to offering a thorough evaluation of technological developments and adoption bar-riers, the study thoroughly investigates AI applications in disaster management, real-time incident detection, healthcare emergency response, industrial hazard prevention, cybersecurity frameworks, and intelligent traffic control. According to the findings, artificial intelligence (AI) has greatly increased automated hazard detection, predictive accuracy, and emergency resource optimisation. These improvements have sped up reaction times, reduced human error, and improved situational awareness in crisis management. Early warning systems for earth-quakes, floods, and wildfires have been made possible by AI-driven predictive analytics models, promoting proactive risk mitigation and catastrophe prepar-edness. Artificial intelligence (AI)-driven computer vision and sensor-based surveillance technologies have enhanced incident detection in real-time emergency response, cutting down on intervention delays and guaranteeing more effective use of emergency resources. Triage automation, geospatial analytics for ambulance dispatch, and AI-enhanced diagnostic technologies have simplified medical crisis management in the healthcare industry, increasing survival rates and cutting down on treatment delays. Furthermore, cybersecurity intelligence systems, robotic automation, and AI-integrated industrial safety frameworks have improved workplace hazard prevention and cyber threat identification. In an emergency, an AI-powered drone-based system facilitates communication between firefighters via light, sound, and a graphical user interface. AI-driven technology solves problems based on situational awareness (SA). Emergency response systems powered by AI improve the security of smart infrastructure. Real-time emergency response optimisation, automated hazard detection, and enhanced risk assessment are all made possible by AI technologies. Real-time fire scenarios are identified using an AI-powered smart firefighting system. During disasters, artificial intelligence (AI) can improve the efficiency of emergency response.AI's role as a crucial enabler of intelligent, data-driven emergency response frameworks, fire fighting, and emergency response will be further reinforced as AI technologies continue to advance and are incorporated into emergency management strategies. This will improve crisis preparedness, real-time intervention capabilities, and global disaster resilience. // This review offers a thorough synthesis of AI's revolutionary role in contemporary emergency management, including insights into technological advancements, constraints, and policy considerations.
