Application of Dijkstra’s Algorithm in the Smart Exit Sign

Abstract

Previous studies on automated fire-egress guidance systems have focused on providing the shortest path information from a specific person at a certain point to the closest exit mostly using a mobile device. This study aims to develop a Smart Exit Sign system that can detect dangerous areas in real time and direct evacuees to the shortest safe evacuation path by dynamically changing the direction signs to the safe egress. The challenge was to provide the shortest safe egress to any evacuees at any point. We have developed a sensor network and algorithm that could exclude unsafe paths and calculate the shortest safe path from multiple starting points to multiple exit points based on Dijkstra's algorithm-the most commonly used algorithm for finding the shortest path. The validity of the proposed system was tested through simulations of test cases.

Design and testing of a dynamic reactive signage network towards fire emergency evacuations

“…The identification and the changing state were the principal values to ingress into the service, in addition to the configured identifier with the same department number from the graph. With the support of the modified Dijkstra algorithm [6], the software managed the route among the nodes, providing to all of them the shortest path to the exits. Depending on the exit status, it discarded or updated the routes designed.…”

“…Besides, computer vision guaranteed the recognition of obstacles at exits or unexpected incidents that occurred spontaneously during an evacuation [5], supported by data collected from sensors. We used computer vision for the crowding analysis in the emergency exits and for the physical obstacles that can turn the evacuation delayed and complex [6][7][8][9]. Then, people identification was attained by a neuro learning convolutional network [10][11][12] using two different types of libraries.…”

Deep learning surrogate models for spatial and visual connectivity

“…It, therefore, allows for the analysis of walking distances between points of interest, and use cases include analysis of escape routes, analysis of connectivity between different teams within an office plan and so on. 8–10 It can also be used to understand how isolated (or difficult to reach) a specific space is compared to other spaces within the same floor plan. 11 In contrast, visual connectivity can be used to analyse visual rather than physical distances.…”