Paper by Ayan Mukhopadhyay: “Emergency response management (ERM) is a challenge faced by communities across the globe. First responders must respond to various incidents, such as fires, traffic accidents, and medical emergencies. They must respond quickly to incidents to minimize the risk to human life. Consequently, considerable attention has been devoted to studying emergency incidents and response in the last several decades. In particular, data-driven models help reduce human and financial loss and improve design codes, traffic regulations, and safety measures. This tutorial paper explores four sub-problems within emergency response: incident prediction, incident detection, resource allocation, and resource dispatch. We aim to present mathematical formulations for these problems and broad frameworks for each problem. We also share open-source (synthetic) data from a large metropolitan area in the USA for future work on data-driven emergency response…(More)”.
How to contribute:
Did you come across – or create – a compelling project/report/book/app at the leading edge of innovation in governance?
Share it with us at info@thelivinglib.org so that we can add it to the Collection!
About the Curator
Get the latest news right in you inbox
Subscribe to curated findings and actionable knowledge from The Living Library, delivered to your inbox every Friday
Related articles
artificial intelligence, DATA, privacy
Co-creating Consent for Data Use — AI-Powered Ethics for Biomedical AI
Posted in September 10, 2025 by Stefaan Verhulst
artificial intelligence
AI openness
Posted in September 9, 2025 by Stefaan Verhulst
artificial intelligence
Political Automation: An Introduction to AI in Government and Its Impact on Citizens
Posted in September 8, 2025 by Stefaan Verhulst