Indoor Location and Orientation Determination for Wireless Personal Area Networks Zekeng Liang, Ioannis Barakos, Stefan Poslad School of Electronic Engineering and Computer Science, Queen Mary, University of London, UK {zekeng.liang, ioannis.barakos, stefan.poslad}@elec.qmul.ac.uk Abstract. This paper presents a Wireless Personal Area Network (WPAN) indoor location determination system that adapts to both dynamic physical environmental conditions and human movement changes in order to find estimated user locations and their orientation. This system has been realized using the Sun SPOT sensor platform. This research identifies the challenges when deploying indoor location determination systems based upon a combination of radio signal strength indication (RSSI) and accelerometer measurements of users’ mobile terminals. The experimental results show that users’ indoor locations can be estimated more precisely and with greater computational efficiency compared to current systems. Keywords: indoor location determination, user positioning, radio map, RSSI, accelerometer values, adaptive. 1 Introduction Indoor location determination technologies have many useful pervasive computing application areas. Our main focus is towards Wireless Personal Area Networks (WPANs) applications, such as smart home service management related to users’ locations, hands free local device activation, gesture based control and monitoring and assisting the elderly and disable people [1]. The most commonly used position determination method, Global Positioning System (GPS), does not work indoors because it usually requires a line-of-sight between the receiver and the transmission satellites used for positioning. Three distinguishing requirements for indoor location determination systems are the location determination accuracy (represented using the error distance between the estimated location and the actual location), the location determination precision (the repeatability of location determination) and the processing time [2], [5], [6]. The granularity for location information can vary across various applications. For instance, locating a person in a room needs more fine-grained location information whereas locating a person in a building, i.e., which room a person is in, requires more coarse-grained location information. Real-time location tracking systems require a real time response and a fixed processing time in order to locate fast moving humans or objects or to track more slowly moving objects and elderly humans. Various methods have been proposed for indoor location determination such as received signal