A MOBILE BASED AMBULANCE EMERGENCY AND SECURITY ALERT SYSTEM USING KNN ALGORITHM
Abstract
This research focuses on the design and implementation of a mobile-based ambulance emergency and security alert system utilizing the K-Nearest Neighbor (KNN) algorithm. The system was developed using React Native, enabling cross-platform functionality for both Android and iOS devices. It allows users to send real-time emergency alerts, which are classified by the KNN model into categories such as medical emergencies, accidents, fire outbreaks, theft, and security threats. The system integrates geo-location services and mapping APIs to transmit distress signals to the nearest responders, thereby improving response times and coordination. Performance was evaluated using classification metrics, and the results demonstrate reliable emergency categorization, although some misclassifications occurred in complex scenarios. Despite limitations related to internet dependency and algorithmic simplicity, the system provides an efficient and scalable solution to emergency response challenges in Nigeria. This work contributes a practical application of machine learning and mobile technologies to enhance public safety and emergency healthcare delivery.
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