Localization of individual nodes in a wireless network is useful in many applications, e.g for tracking patients in hospitals. Using the Received Signal Strength Indicator, RSSI, for this purpose has been explored in numerous studies. It is energy efficient and rarely requires customised hardware of configuration. The possibility to use pre-configured, off-the-shelf products is especially important in large scale sensor network deployments. Using RSSI has, however, many drawbacks, since the radio signal is heavily affected by the surrounding envi- ronment. Most studies in this area discuss the impact of multipath effects. Our study on range based distance estimations, using the Telos hardware, shows that individual profiling requirements and antenna quality are equally challenging. Still, RSSI based indoor localization systems remains an active field of research. A multitude of approaches and algorithms have been proposed to gain accuracy in position estimations. The most common of these techniques are explored in this report. Based on previous work at The Polytechnic University of Catalonia, the Telos hardware has been integrated successfully with existing software to form local wireless sensor networks for indoor localization. We present applications developed on top of TinyOS, an operating system for embedded systems. These applications serve as a platform for related future work at The Polytechnic University of Catalonia and elsewhere.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-91844 |
| Date | January 2013 |
| Creators | Pehrson Skidén, Petter |
| Publisher | Linköpings universitet, Kommunikationssystem, Linköpings universitet, Tekniska högskolan |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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