AI for better emergency response

Abstract

Artificial intelligence (AI) is becoming an essential tool for improving how societies respond to emergencies. By combining machine learning, deep learning, computer vision, and Internet of Things (IoT) technologies, AI systems can support faster decision-making, better risk assessment, and more effective disaster management. A review of over 400 studies shows that AI has been applied in many areas, including disaster prediction, healthcare emergencies, industrial safety, cybersecurity, and traffic control. These applications demonstrate that AI can increase accuracy in predicting hazards, automate detection of risks, and optimize the use of emergency resources. For example, predictive models have been used to create early warning systems for earthquakes, floods, and wildfires, helping communities prepare before disasters strike. In real-time response, AI-powered cameras and sensors improve incident detection, reducing delays and ensuring resources are deployed efficiently. In healthcare, AI supports triage, diagnostics, and ambulance dispatch, which improves patient survival rates. AI also strengthens workplace safety and cybersecurity by detecting threats and maintaining communication during crises. However, challenges such as data interoperability, regulatory issues, algorithmic bias, and ethical concerns remain. Overall, AI offers a powerful way to build safer, more resilient emergency response systems that can protect lives and reduce risks worldwide