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020 ▼a 9780438177253
035 ▼a (MiAaPQ)AAI10828505
035 ▼a (MiAaPQ)washington:18848
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 004
1001 ▼a Li, Hanchuan.
24510 ▼a Enabling Novel Sensing and Interaction with Everyday Objects using Commercial RFID Systems.
260 ▼a [S.l.]: ▼b University of Washington., ▼c 2018.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2018.
300 ▼a 147 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Shwetak N. Patel.
5021 ▼a Thesis (Ph.D.)--University of Washington, 2018.
520 ▼a The Internet of Things (IoT) promises an interconnected network of smart devices that will revolutionize the way people interact with their surrounding environments. This distributed network of physical devices will open up tremendous opportunit
520 ▼a The advancement of IoT has been heavily focused on creating new and smart electronic devices, while the vast majority of everyday non-smart objects are left unchecked. Techniques based on active sensors are limited by their high deployment cost
520 ▼a Radio-frequency identification (RFID) has been widely adopted in the IoT industry as a standard inventory management infrastructure. In this thesis, I apply signal processing and machine learning techniques on low-level channel parameters of com
590 ▼a School code: 0250.
650 4 ▼a Computer science.
690 ▼a 0984
71020 ▼a University of Washington. ▼b Computer Science and Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0250
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999175 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 201812 ▼f 2019
990 ▼a ***1012033