Iot-Enhanced Soldier Health System With Predictive Analytics And Real-Time Emergency Notifications And Qgis- Based Geospatial Monitoring System

Soldiers' health and safety are of utmost importance in the defense industry, particularly in combat or isolated areas where prompt medical assistance may not always be accessible. In order to continually watch and forecast soldiers' health, this article describes the design and development of an Internet of Things (IoT)-based Soldier Health Monitoring System that combines cutting-edge sensors, machine learning, and real-time communication technologies. This system combines IoT with AI-powered health forecasts to provide rapid decision-making, continuous monitoring, and prompt emergency responses. The work is an essential tool for military health management since it greatly improves soldiers' operational safety and well-being when they are in the field. The interface includes standard QGIS tools and menus for map navigation, layer control, and attribute management. In the defense section of a health monitoring project, a shortest path algorithm optimizes data transmission routes between sensors and the monitoring system, ensuring minimal latency and secure communication. It also helps allocate resources efficiently, improving the overall system's performance and reliability. In the defense section of a health monitoring project, the K-Nearest Neighbors (KNN) algorithm can be used to classify or predict the health status of a patient based on similar data points from neighboring patients.