Smartphone-based Acoustic Indoor Space Mapping
| Autor: | Ghufran Baig, Swadhin Pradhan, Guohai Chen, Wenguang Mao, Lili Qiu, Bo Yang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science RSS 020206 networking & telecommunications 02 engineering and technology Construct (python library) computer.file_format Space mapping Human-Computer Interaction Lidar Signal strength Hardware and Architecture 020204 information systems Mapping system 0202 electrical engineering electronic engineering information engineering Trajectory Wireless Computer vision Artificial intelligence business computer |
| Zdroj: | Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2:1-26 |
| ISSN: | 2474-9567 |
| DOI: | 10.1145/3214278 |
| Popis: | Constructing a map of indoor space has many important applications, such as indoor navigation, VR/AR, construction, safety, facility management, and network condition prediction. Existing indoor space mapping requires special hardware (e.g., indoor LiDAR equipment) and well-trained operators. In this paper, we develop a smartphone-based indoor space mapping system that lets a regular user quickly map an indoor space by simply walking around while holding a phone in his/her hand. Our system accurately measures the distance to nearby reflectors, estimates the user's trajectory, and pairs different reflectors the user encounters during the walk to automatically construct the contour. Using extensive evaluation, we show our contour construction is accurate: the median errors are 1.5 cm for a single wall and 6 cm for multiple walls (due to longer trajectory and the higher number of walls). We show that our system provides a median error of 30 cm and a 90-percentile error of 1 m, which is significantly better than the state-of-the-art smartphone acoustic mapping system BatMapper [64], whose corresponding errors are 60 cm and 2.5 m respectively, even after multiple walks. We further show that the constructed indoor contour can be used to predict wireless received signal strength (RSS). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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