RescuTrack: An Edge Computing-Enabled Vitals Monitoring System for First Responders

Natural disasters such as earthquakes, avalanches or events such as explosions and fire accidents frequently occur. Drone technology is a promising solution for disaster management where the mainstream communication infrastructure is unavailable or damaged. A swarm of drones serve as an Adhoc network to support rescue management activities. This project aims to design and develop an IoT-enabled Wireless Body Area Network (WBAN) to monitor the health status of Search and Rescue (SAR) teams in real-time in the event of floods and wildfires. The proposed WBAN architecture consists of the SAR team equipped with wearable body sensors, which collect health and environmental data for location determination and vital signs transmission. The Body Data Coordinator relays this data to the nearest gateway, equipped with an open-source, industry-grade middleware platform to allow data processing at the Edge and transmission to the Ground Control Station and further to the Cloud endpoint for further processing. There is a risk to personal health due to the arduous duties of first responders, which can cause high blood pressure among the SAR personnel and lead to acute cardiovascular events. There is a need to predict the risk of hypertension in first responders. This paper also discusses a time series-based forecasting algorithm to predict the BP Trends of the first resnonders involved in SAR activities.