Iot-Fog-Cloud-Assisted Novel Industrial Disaster Evacuation Framework

Abstract

Human evacuation is essential during calamities due to natural events, or deliberate acts. The convergence of numerous computing paradigms, Internet of Things (IoT), and Fog-Cloud computing holds significant promise for enhancing the evacuation process. This paper presents an advanced evacuation architecture that leverages the IoT-Fog-Cloud (IFC) computing model. The presented model uses IoT technology to perceive environmental data and track the mobility of occupants in real time. The fog computing module employs an Artificial Intelligence-driven Support Vector Machine (SVM) to determine emergent situations promptly. Moreover, the cloud layer provisions the development of an evacuation algorithm that generates safe and efficient routes based on real-time environmental conditions and occupant data collected from the fog module. This innovative approach provides a comprehensive evacuation map to guide individuals to designated safe locations. The effectiveness of this framework has been evaluated in a simulated environment comprising 8055 data segments. Results indicate significant improvements over existing methods, including: minimum delay (5.34 s), dimensional reduction (96.39%), classification performance (accuracy (94.89%), specificity (90.12%), sensitivity (95.02%), and F-measure (94.65%)), and energy efficiency (92%).