created by ‘crowd sourcing’, described by Lee et al. (2010), where the user themselves generate the data through a process known as ‘wardriving’. Wardriving involves driving around and passively listening for signals from access points and mapping the location with a GPS device. This data is sent back to the host company which allows other users to try and estimate their location by looking for the same radio fingerprint as that previously recorded. This only works where databases of access points’ location exist, usually in large urban areas like cities. Table 2.2: Comparison table of Wide Area Positioning Systems System Approach Accuracy (and precision) Scale Cost Constraints GPS (Malik, 2009) RF TOA 15 m Global High Does not work indoors Indoor GPS (Wang et al., 2008) RF TOA 5-75 m Global High Requires pseudolites Differential GPS (Malik, 2009) RF TOA plus correction updates 3 – 5 m Global High Requires non standard receivers Assisted GPS (Djuknic and Richton, 2002) RF TOA plus other Wi-Fi or cellular <10 to >100 m Global High Requires cellular or Wi-Fi network connection Skyhook (Skyhook Wireless, 2011) GPS, Wi-Fi and Cellular triangulation 10 to 1000m dependent on available devices Depends on areas mapped – most urban Free Requires smart phone or PDA Navizon (Lee et al., 2010) GPS, Wi-Fi and Cellular triangulation 10 to 1000m dependent on available devices Depends on areas mapped – most urban Low Requires smart phone or PDA Rosum TV (Malik, 2009) TDOA 5 – 50m Coverage of TV signals Low Need for signal monitors, no standardisation
intermediate node) recorded by Ekahau. This check also reveals whether a node sequence has been visited during the time period. Table 5.5: Transition Matrix for one week’s movement 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 1 U 1 0 0 0 U 0 0 0 0 U 0 0 0 0 0 0 0 0 2 U 0 .33 0 U 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 U 0 0 .23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 .46 0 0 0 0 0 0 0 0 0 .40 0 0 0 0 5 0 U .67 .40 0 1 1 .17 0 0 0 0 0 0 0 U 0 0 0 6 U 0 0 0 .31 U 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 0 0 U 0 0 .33 0 0 0 0 0 0 0 0 0 0 0 8 0 0 0 0 U 0 U 0 1 .36 0 0 0 0 0 0 0 0 0 9 0 0 0 0 0 0 0 .33 0 0 0 0 0 0 0 0 0 0 0 10 0 0 0 0 0 0 0 .17 0 0 0 0 0 0 0 0 0 0 .59 11 1 0 0 0 0 0 0 0 0 0 0 U U U 0 U 0 0 0 12 0 0 0 0 0 0 0 0 0 0 1 0 U U 0 U 0 0 0 13 0 0 0 0 0 0 0 0 0 0 U U 0 U 0 .04 0 0 0 14 0 0 0 0 0 0 0 0 0 0 U U U 0 0 .20 0 0 0 15 0 0 0 .60 U 0 0 0 0 0 0 0 0 0 0 .16 0 0 0 16 0 0 0 0 0 0 0 0 0 0 U 1 1 1 .60 0 .17 .46 U 17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .04 0 .21 U 18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .56 0.5 0 .41 19 0 0 0 0 0 0 0 0 0 .64 0 0 0 0 0 U .33 .33 0
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