Fog-inspired framework for emergency rescue operations in post-disaster scenario

Time-critical applications, such as emergency systems, healthcare, or smart traffic monitoring, demand latency-aware and real-time decision-making. Excessive delays in rescue actions result in a significant death toll each year around the world. In such crucial situations, technologies like the Internet of Things (IoT) coupled with cloud and fog infrastructure might be extremely effective in post-disaster scenarios. This study investigates the opportunities and prospects, and of combining cloud computing services with fog computing to deliver emergency rescue assistance to victims. A hierarchical framework has been developed in this work that gathers and aggregates data from various IoT devices, undertakes preliminary data processing in fog nodes, and finds optimal paths when certain locations remain inaccessible due to disaster damage. When a victim’s health status is abnormal, an alert is issued to assist the victim, and the cloud server predicts the ambulance’s path so that it arrives with the minimal possibility of delay, preventing any deadly conditions. Also, evaluation of the model has demonstrated that by incorporating fog, significant average delay reduction can be achieved while ensuring better precision, recall value, and response time than the cloud-based systems.