Beacon-based Indoor Fire Evacuation System using Augmented Reality and Machine Learning

Hwawon Lee, Dohyun Chung, Seongmin Kim, Jiwon Lim, Yoonha Bahng, Suhyun Park, Anthony H. Smith

Abstract: The inefficiency of fire evacuation has been the issue since the present evacuation method is unsuitable for complex buildings. In order to improve the evacuation system, this paper aims at three main components. First, Kalman Filter and deep learning models were utilized to estimate the user’s location accurately. Second, Q-learning based evacuation algorithm was designed to deal with various fire situations. Lastly, AR and a 2D map offer effective navigation systems. The proposed system offers the safest path based on accurate location with a user-friendly visual supplement.