Smart watch RSSI localization and refinement for behavioral classification using laser-SLAM for mapping and fingerprinting
| Autor: | Lance C. Perez, David Bayne, Eric T. Psota, Steven A. Parkison, Stephen J. Bonasera, Pedro Sathler, Mateusz Mittek, Jay D. Carlson |
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| Rok vydání: | 2014 |
| Předmět: |
Engineering
Calibration (statistics) Movement Real-time computing Monitoring Ambulatory Simultaneous localization and mapping Smartwatch Home automation Activities of Daily Living Humans Probability Behavior Electronic Data Processing Internet Signal processing business.industry Lasers Node (networking) Signal Processing Computer-Assisted Embedded system Calibration The Internet business Wireless Technology Wireless sensor network Algorithms |
| Zdroj: | EMBC |
| DOI: | 10.1109/embc.2014.6944048 |
| Popis: | As a first step toward building a smart home behavioral monitoring system capable of classifying a wide variety of human behavior, a wireless sensor network (WSN) system is presented for RSSI localization. The low-cost, non-intrusive system uses a smart watch worn by the user to broadcast data to the WSN, where the strength of the radio signal is evaluated at each WSN node to localize the user. A method is presented that uses simultaneous localization and mapping (SLAM) for system calibration, providing automated fingerprinting associating the radio signal strength patterns to the user's location within the living space. To improve the accuracy of localization, a novel refinement technique is introduced that takes into account typical movement patterns of people within their homes. Experimental results demonstrate that the system is capable of providing accurate localization results in a typical living space. |
| Databáze: | OpenAIRE |
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