Recently, the prevalence of WiFi devices and ubiquitous coverage of WiFi network provide us the opportunity to extend WiFi capabilities beyond communication, particularly in sensing the physical environment. Most existing systems that enable human sensing utilizing commodity WiFi devices are simply rely on profile training based techniques. Such techniques suffer from performance degradation when configuration changes after training. Furthermore, those systems can not work under multi-user scenarios. To overcome the limitations of existing solutions, this dissertation introduces the design and implementation of three systems. First, we propose MultiTrack, a multi-user indoor tracking and activity recognition system. It leverages multiple transmission links and all the available bandwidth at 5GHz of commodity WiFi to achieve tracking multiple users simultaneously. Second, we present WiFinger, a fine-grained finger gesture recognition system, which utilizes single RF device and does not require per-user or per-location training. Lastly, we present FruitSense, a RF based fruit ripeness level detection system that achieves environment-independent sensing. Such system demonstrates the wireless sensing can be utilized beyond human sensing to the biosensing field. / A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2019. / April 1, 2019. / activity recognition, fruit sensing, gesture recognition, indoor tracking, localization, wireless sensing / Includes bibliographical references. / Jie Yang, Professor Directing Dissertation; Sachin Shanbhag, University Representative; An-I Andy Wang, Committee Member; Zhenhai Duan, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_709838 |
| Contributors | Tan, Sheng (author), Yang, Jie (Professor Directing Dissertation), Shanbhag, Sachin (University Representative), Wang, An-I Andy (Committee Member), Duan, Zhenhai (Committee Member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Computer Science (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (99 pages), computer, application/pdf |
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