Application of Dijkstra’s Algorithm in the Smart Exit Sign Jehyun Cho a , Ghang Lee a , Jongsung Won a and Eunseo Ryu a a Dept. of Architectural Engineering, University of Yonsei, South Korea E-mail: jkun86@naver.com, glee@yonsei.ac.kr, quietman111@gmail.com, eunseo4773@naver.com 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. Keywords - Shortest path algorithm; Evacuation system; Exit sign 1 Introduction Navigating the indoor spaces of large and complex buildings such as shopping malls is challenging. This makes building occupants often disoriented while they explore a building. Yet, this issue is more problematic during an emergent situation such as fires rather than general situations. During an emergent situation, exit signs may be helpful. However, traditional exit signs in buildings usually have a fixed direction sign towards exits and may direct evacuators to dangerous paths where a fire has broken out. Consequently, in this type of situation, individuals cannot dynamically change directions reflecting the fire hazard. In order to respond to this issue, we have developed a smart exit sign that can dynamically change direction signs and guide evacuators to safe evacuation paths. This paper presents an Automated Direction Setting Algorithm (ADSA), which was developed as part of the Smart Exit Sign system. The ADSA was designed to dynamically change the direction signs on a smart exit sign—reflecting the fire situations—and indicate the proper directions towards safer evacuation paths. Previous research has studied evacuation path based on the shortest path algorithms such as Dijkstra’s algorithm, Floyd-Warshall Algorithm, and A* algorithm. The main goals of those studies were to find the shortest evacuation path and guide a certain person to the path by showing the path on a mobile phone or on other systems. However, in an emergent case, such as fire, most evacuees may not have or may not be able to download the smart device application that is required to visualize the shortest evacuation path on their mobile devices. The eventual goal of this study is to develop a Smart Exit Sign system that detects unsafe areas and calculate the shortest safe path in real time and dynamically change its direction sign toward the shortest safe path. In the first step, this paper presents an algorithm and a simulator that can calculate and visualize a network of smart exit signs, which can guide any evacuees at any point in a building to the nearest exit via a safe route. The algorithm, developed based on Dijkstra’s algorithm, which is one of the famous shortest path algorithms, calculates safe evacuation paths from multiple starting points while directing individuals toward the nearest exits. This study was conducted in the following order. First, through review of related literature, we determined the characteristics needed to make the algorithm for the system effective. Then, we developed an algorithm and a simulator. Finally, we tested the applicability and validity of the algorithm through simulations of test cases. 2 Literature Review Many studies have been conducted to develop systems that could provide indoor navigation information in an unknown space during an emergent situation. In a study conducted by Kobes et al., it examined how people determined evacuation paths, during fire related situations, through a series of tests that were The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)