ASCE International Conference on Computing in Civil Engineering 2019
Applying Deep Learning and Building Information Modeling to Indoor Positioning Based on Sound
Publication: Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
ABSTRACT
At present, indoor positioning has great potential for disaster mitigation, such as guiding evacuees to safe places. This research aims at developing such a sound-based method using artificial intelligence (AI) and building information modeling (BIM). Amid a disaster, first responders can quickly set up the proposed system to help indoor positioning, which relies on BIM, virtual reality (VR), and head related transfer functions (HRTF) techniques to simulate virtual sound fields. Then, a deep learning model is trained so as to be able to predict the current zone within a room based on the sound received. Unity, a serious game platform, and Steam Audio, a Unity plugin designed for adding 3D audio to VR experience, are employed to generate input data sets. The overall accuracy of the output results is about 90% though the training time is long, which can be reduced if more powerful computing resources are utilized.
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Information & Authors
Information
Published In
Computing in Civil Engineering 2019: Visualization, Information Modeling, and Simulation
Pages: 193 - 199
Editors: Yong K. Cho, Ph.D., Georgia Institute of Technology, Fernanda Leite, Ph.D., University of Texas at Austin, Amir Behzadan, Ph.D., Texas A&M University, and Chao Wang, Ph.D., Louisiana State University
ISBN (Online): 978-0-7844-8242-1
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Jun 13, 2019
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