WLAN positioning methods and supporting learning technologies for mobile platforms
Arsen Melkonyan, The University of Texas at San Antonio, United States
The University of Texas at San Antonio . Awarded
Location technologies constitute an essential component of systems design for autonomous operations and control. The Global Positioning System (GPS) works well in outdoor areas, but the satellite signals are not strong enough to penetrate inside most indoor environments. As a result, a new strain of indoor positioning technologies that make use of 802.11 Wireless LANs (WLAN) appeared. Contemporary WLAN positioning methods maintain a database of location fingerprints, which is used to identify the most likely match of incoming signal data with those preliminary surveyed and saved in the database. An issue with these systems, however, is the operation robustness and computational complexity, which is the subject of the proposed research. WLAN is not designed for positioning and access points are often not available which may disrupt operation. Also conventional WLAN-based algorithms are computationally very heavy for deployment on mobile devices. Thus a thorough investigation of these aspects along with possible solutions will enhance the research in this area.
Another important aspect of the proposed research is the accessibility of testbed platforms. Positioning research requires routine hardware and software installations, which make affordable platform selection actual in the community. Responding to this need, this proposal investigates a remote experimentation technique to broaden accessibility and sharing of platforms between researchers. As another benefit of remote experimentation is the applicability of the approach to education by enabling remote lab installations. Today's electrical and computer engineering graduates need marketable skills to work with electronic devices. Hands-on experiments prepare students to deal with real-world problems and help to efficiently digest theoretical concepts and relate those to practical tasks. However, shortage of equipment, high costs, and the lack of human resources for laboratory maintenance and assistance decrease the implementation capacity of the hands-on training laboratories. In addition, experimental equipment at many sites is typically underutilized. Thus, remote laboratories accessible through the Internet can resolve cost and efficient exploitation constraints as they can be used at flexible times and from various locations.
Melkonyan, A. WLAN positioning methods and supporting learning technologies for mobile platforms. Ph.D. thesis, The University of Texas at San Antonio.
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