Advancing Urban Evacuation Management: A Real-Time, Adaptive Model Leveraging Cloud-Enabled Big Data and IoT Surveillance

Emergency evacuation management in urban areas is paramount due to rapid population growth and urbanization. This research introduces an innovative methodology leveraging the Internet of Things (IoT) and Big Data Technologies to fortify emergency management systems. This research proposes a system that integrates IoT sensors, an MQTT broker, a Kafka broker, HDFS, and Spark streaming, all housed in the cloud infrastructure, facilitating real-time monitoring and calculation of varying risk scores through each of the exit routes during an emergency and providing the evacuees with a user interface that alerts them with the most probable safety exits. Unlike conventional evacuation systems that focus solely on identifying the shortest exit route, or have a static approach to processing data, our solution minimizes potential risks during an emergency by monitoring factors such as pressure, temperature, humidity and flame intensity in real-time and predicts risk scores for danger-prone exits considering the number of exits and accessibility of each exit, thus notifying the user of the same through a web interface. To illustrate the practical applicability of our system, we present a case study centred around a sports stadium, offering a tangible example of the proposed solution’s effectiveness.