This thesis explores the possibilities of constructing an indoor positioning system based on Bluetooth Smart technology. Two non-trainable trilateration approaches and two trainable fingerprinting were implemented and evaluated at Mobiento's offices in Stockholm, Sweden. A trilateration approach is based on finding a sought location based on known distances towards know locations, at least three locations and distances are needed. A fingerprinting approach is based on creating a radio map, which describes transmission signals within the room, towards different transmitters. A set amount of coordinates are assigned a fingerprint. These are then used as reference points for a sought location. For each major approach, trilateration and fingerprinting, a weighted approach is conducted. These approaches are evaluated in a disturbance free environment in term of accuracy, implementation and setup. In terms of accuracy, the non-weighted fingerprinting approach performs slightly better than the weighted fingerprinting approaches. Both of these are more accurate than the trilateration approaches. When it comes to implementation and setup, the trilateration algorithms impose less cost. These allow for better scalability when the indoor environment becomes larger.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-178968 |
| Date | January 2015 |
| Creators | Nygård, Niklas |
| Publisher | KTH, Skolan för datavetenskap och kommunikation (CSC) |
| 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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