Daisy: the center for data-intensive systems at Aalborg University
ACM SIGMOD Record
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Location-Based Services (LBSs) constitutes one of the most popular classes of mobile services. However, while current LBSs typically target outdoor settings, we lead large parts of our lives indoors. The availability of easy-to-use and low-cost indoor positioning services is essential in also enabling indoor LBSs. Existing indoor positioning services typically use a single technology such as Wi-Fi, RFID or Bluetooth. Wi-Fi based indoor positioning is relatively easy to deploy, but does often not offer good positioning accuracy. In contrast, the use of RFID or Bluetooth for positioning requires considerable investments in equipment in order to ensure good positioning accuracy. Motivated by these observations, we propose a hybrid approach to indoor positioning. In particular, we introduce Bluetooth hotspots into an indoor space with an existing Wi-Fi infrastructure such that better positioning is achieved than what can be achieved by each technology in isolation. We design a flexible and extensible system architecture with an effective online position estimation algorithm for the hybrid system. The system is evaluated empirically in the building of our department. The results show that the hybrid approach improves positioning accuracy markedly.