During an emergency, getting the right help at the right time is very important. However, many existing emergencyreporting methods mainly depend on manual communication, which can cause delays in identifying the type and severity of an emergency and assigning suitable resources. This paper presents ResQAI, an intelligent emergency response application designed to improve the process of reporting, analyzing, and responding to emergency situations.ResQAI uses artificial intelligence to identify the emergency category from the user's description and predict its severity. Based on the emergency type, severity, location, and availability of resources, the system helps assign suitable resources and volunteers. The application also uses GPS to capture the emergency location and Firebase Cloud Messaging (FCM) to send notifications to the concerned users and organizations. A voice-based reporting option allows users to describe an emergency using speech, which is converted into text before submitting the report. To support situations where internet connectivity is unavailable, ResQAI stores emergency requests locally using SQLite and synchronizes them with the server when connectivity is restored. The proposed approach combines artificial intelligence, location services, mobile technology, and offline synchronization in a single emergency response platform. The system is intended to reduce manual effort, improve response coordination, and provide a more organized approach to emergency resource allocation.

Dr. B. Meena Preethi, Aswath.T, "ResQAI – Intelligent Emergency Resource Allocation and Crisis Response Using Artificial Intelligence" International Journal of Scientific Research and Engineering Development, V9(5): Page(1188-1200) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.