Non-Invasive Localization Using Software-Defined Radios
نویسندگان
چکیده
Non-invasive indoor human activity detection using radio waves has attracted the interest of researchers, contributing to a range new applications including smart healthcare. Localisation activities can assist in developing advanced healthcare systems able identify location patients. Radio frequencies have been shown numerous studies as non-invasive method activity. This is achieved by observing signal propagation described Channel State Information (CSI). paper presents experimental results Universal Software-Defined Peripheral (USRP) devices and localise single subject performing utilizing CSI frequencies. The experiments are carried out retrieve samples perform no-activity, sitting, standing, leaning forward actions various positions room. Additional captured for walking two directions across observed area. Giving total 6 spanning monitored also collected while area empty further comparison. Artificial intelligence used make classifications on CSI. proposed approach uses Super Learner (SL) algorithm that different with 96% accuracy, outperforming existing benchmark approaches.
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ژورنال
عنوان ژورنال: IEEE Sensors Journal
سال: 2022
ISSN: ['1558-1748', '1530-437X']
DOI: https://doi.org/10.1109/jsen.2022.3160796