As well as delivering high speed internet, Wireless LAN (WLAN) can be used as an effective indoor positioning system. It is competitive in terms of both accuracy and cost compared to similar systems. To date, several signal strength based techniques have been proposed. Researchers at the University of New South Wales (UNSW) have developed several innovative implementations of WLAN positioning systems. This paper describes the techniques used and details the experimental results of the research.

/pdf/indoor-positioning-techniques-based-on-wireless-lan-2c0xdeyfpn.pdf

Indoor Positioning Techniques Based on Wireless LAN

In this paper, we present a robust, decentralized approach to RF-based location tracking. Our system, called MoteTrack, is based on low-power radio transceivers coupled with a modest amount of computation and storage capabilities. MoteTrack does not rely upon any back-end server or network infrastructure: the location of each mobile node is computed using a received radio signal strength signature from numerous beacon nodes to a database of signatures that is replicated across the beacon nodes themselves. This design allows the system to function despite significant failures of the radio beacon infrastructure. In our deployment of MoteTrack, consisting of 20 beacon nodes distributed across our Computer Science building, we achieve a 50th percentile and 80th percentile location-tracking accuracy of 2 meters and 3 meters respectively. In addition, MoteTrack can tolerate the failure of up to 60% of the beacon nodes without severely degrading accuracy, making the system suitable for deployment in highly volatile conditions. We present a detailed analysis of MoteTrack's performance under a wide range of conditions, including variance in the number of obstructions, beacon node failure, radio signature perturbations, receiver sensitivity, and beacon node density.

/pdf/motetrack-a-robust-decentralized-approach-to-rf-based-4lzthw2us2.pdf

MoteTrack: a robust, decentralized approach to RF-Based location tracking

In this paper, we present a robust, decentralized approach to RF-based location tracking. Our system, called MoteTrack, is based on low-power radio transceivers coupled with a modest amount of computation and storage capabilities. MoteTrack does not rely upon any back-end server or network infrastructure: the location of each mobile node is computed using a received radio signal strength signature from numerous beacon nodes to a database of signatures that is replicated across the beacon nodes themselves. This design allows the system to function despite significant failures of the radio beacon infrastructure. In our deployment of MoteTrack, consisting of 23 beacon nodes distributed across our Computer Science building, we achieve a 50th percentile and 80th percentile location-tracking accuracy of 0.9 and 1.6 m respectively. In addition, MoteTrack can tolerate the failure of up to 60% of the beacon nodes without severely degrading accuracy, making the system suitable for deployment in highly volatile conditions. We present a detailed analysis of MoteTrack's performance under a wide range of conditions, including variance in the number of obstructions, beacon node failure, radio signature perturbations, receiver sensitivity, and beacon node density.

MoteTrack: a robust, decentralized approach to RF-based location tracking

Location fingerprinting in wireless LAN positioning has received much attention recently. One of the key issues of this technique is generating the database of fingerprints. The conventional method does not utilise the spatial correlation of measurements sampled at adjacent reference points, and the training process is not an easy task. A new method based on kriging is presented which can not only achieve more accurate estimation, but can also greatly reduce the workload and save training time. This can make the fingerprinting technique more flexible and easier to implement.

/pdf/method-for-yielding-a-database-of-location-fingerprints-in-1uko1smx96.pdf

Method for yielding a database of location fingerprints in WLAN

Redpin is a fingerprint-based indoor localization system designed and built to run on mobile phones. The basic principles of our system are based on known systems like Place Lab or Radar. However, with Redpin it is possible to consider the signal-strength of GSM, Bluetooth, and WiFi access points on a mobile phone. Moreover, we devised methods to omit the time-consuming training phase and instead incorporate a folksonomy-like approach where the users train the system while using it. Finally, this approach also enables the system to expeditiously adapt to changes in the environment, caused for example by replaced access points.

/pdf/redpin-adaptive-zero-configuration-indoor-localization-4h32cy16zi.pdf

Redpin - adaptive, zero-configuration indoor localization through user collaboration

Future mobile devices will increasingly have multiple sources of location information associated with them, such as GPS, cellular cell-sector ID, Bluetooth or 802.11 wireless LAN. In fact, cellular phones with GPS receivers and 802.11 wireless LAN are already becoming available. However, not all location technologies will operate everywhere (e.g. GPS typically will not work indoors whereas 802.11 coverage may be available) and they typically have different accuracies and range. This paper presents an experimental study of the feasibility of using multiple wireless technologies simultaneously for location estimation. We have collected signal strength information from both IEEE 802.11 and Bluetooth wireless network technologies, developed and applied algorithms for determining location using data for each wireless technology, and then used a simple algorithm for fusing the location estimates from both technologies to try to enhance the accuracy of the location estimates.

/pdf/indoor-location-estimation-using-multiple-wireless-1x5fsuw9kk.pdf

Dhruv Pandya

Papers

Indoor location estimation using multiple wireless technologies

Learner Attention Quantification Using Eye Tracking and EEG Signals