以深度學習與建築資訊模型及虛擬實境技術探討室內聲音定位

SOUND-BASED INDOOR POSITIONING FOR RESCUE USING DEEP LEARNING, BUILDING INFORMATION MODELS AND VIRTUAL REALITY

張智雄(Chih-Hsiung Chang) ； 談家成(Jia-Cheng Tan) ； 王如觀(Ru-Guan Wang) ； 吳佰餘(Pai-Yu Wu) ； 周建成(Chien-Cheng Chou)

《中國土木水利工程學刊》 32卷5期 (2020/09) Pp. 383-392

https://doi.org/10.6652/JoCICHE.202009_32(5).0002

摘要

在救災時於建築物室內可快速定位為相當重要的需求。隨著軟體技術演進，應用建築資訊模型與虛擬實境技術已能模擬真實世界建築物之3D視覺場景與聲響效果，例如人物在虛擬世界漫遊可感受到聲音吸收、散射、傳輸與距離等特徵。因此，本研究旨在將某建築空間建構虛擬複本，前處理虛擬空間各點聲音資料，以深度學習法進行聽音辨位，將來能以實際空間任一點聲音值，透過演算法預測室內位置。最後總結研究成果在室內定位應用與未來方向。

關鍵字

深度學習 ； 建築資訊模型 ； 虛擬實境 ； 室內定位

並列摘要

Indoor positioning is one of the most important tasks during disaster relief. As software technology evolves rapidly, various applications based on building information modeling and virtual reality have been utilized to simulate the three-dimensional scenes and sound effects of real-world buildings. For example, characters roaming in the virtual world can perceive sound absorption, scattering, transmission, and distance features. The purpose of this study is to construct the virtual replica of a building space, analyze the sound reception data of each designated point, and use the deep learning algorithm to identify the corresponding indoor position. In addition, although modern deep learning algorithms can produce satisfactory predictions, they may take longer time to reach convergence, which is not feasible during disaster relief. Thus, adjustment of algorithm parameters to balance the trade-off between model accuracy and training time is discussed, followed by model limitations and future directions.

並列關鍵字

deep learning ； building information modeling ； virtual reality ； indoor positioning system

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