Disaster emergency response framework for smart buildings

Building evacuation is critical in saving human lives in case of an emergency resulting from natural or human-made attacks and disasters. The efficiency of evacuation can be enhanced by integrating the internet of things, fog computing, cloud computing, and other communication technologies. In this study, we present an intelligent evacuation system that combines Internet of Things (IoT), fog layer, and cloud layer. First, this system applies IoT technologies to capture environmental information, and the location of occupants to track their movements. Second, the Fog layer is employed to detect emergency events using Support Vector Machine (SVM), perform real-time Spatio-temporal processing based on the data collected, and dimension reduction with the energy-saving mechanism. Third, the Cloud layer facilitates an evacuation algorithm to compute a fast and safe route using environmental and occupant information gleaned from the fog and generate an evacuation map to direct evacuees to the exit. Our model considers the current location of evacuees as well as environmental information gained from intelligent building sensors and personal mobile platforms to recommend the optimal evacuation route for each traced evacuee. The results of simulations show that our framework can efficiently and accurately guide evacuees to a safer location while significantly reducing direct fire exposure. Further, performance parameters are evaluated by comparing fog-cloud deployments and cloud only deployments for more clarity. This study acknowledges that the proposed paradigm is efficient in utilizing IoT devices, fog, and cloud services to build an energy-efficient, cost-effective, and scalable evacuation platform for smart building advancements.(C) 2022 Elsevier B.V. All rights reserved.

Automated summary

In this study, an intelligent evacuation system is proposed that integrates IoT, fog layer, and cloud layer to efficiently and accurately guide evacuees to safer locations while significantly reducing direct fire exposure.