3-Dimensional Indoor Positioning System based on WI-FI Received Signal Strength using Greedy Algorithm and Parallel Resilient Propagation

Abstract

The importance of services, based on current location of objects is growing. This is because Global Navigation Satellite System (GNSS) cannot provide object position inside buildings. In modern era the Location Based Services (LBS) are tremendously dependent on Indoor Positioning System (IPS). Parallel RPROP and greedy algorithm were combined for development of IPS using Received Signal Strength (RSS) in heterogeneous environment, the environment comprised of human activity, walls material, cupboards, and various type of surveying machines etc. The propagation of Wi-Fi signal varies directionally, therefore to cope with direction changes in signals; this proposed model produces three sets of weights, which could be considered best for easting, northing and height respectively. Proposed model was trained with 75% of collected data and tested on remaining 25% data. Distance error between known points and predicted coordinates was used for accuracy assessment. Through experiments a maximum accuracy of 0.87m was achieved and it was found that median error was less than mean error. Median error between known points and predicted coordinates was about 3.32m and their mean error was about 4.62m, which is satisfactory as far as 3D position determination is concerned. On the basis of results the use of parallel RPROP and greedy algorithm for 3D position determination in heterogeneous environment is recommended.

A Smartphone 3D Positioning Method using a Spinning Magnet Marker

“…Zandbergen et al [1], Cheng et al [2], and Alam et al [3] studied a positioning method using the radio field intensity fingerprint from from Wi-Fi access points. However, these methods require recreating fingerprints when the environment changes.…”

“…In addition, when it is possible to estimate the route of a visitor within an accuracy of several centimeters, it is possible to estimate the behavior pattern of visitors in detail. Various in- 1 Graduate School of Engineering, Nagoya University, Nagoya, Aichi 464-0814, Japan 2 Institutes of Innovation for Future Society, Nagoya University, Nagoya, Aichi 464-8601, Japan 3 IoT Business Department, NTT DOCOMO, INC., Yokosuka, Kanagawa 239-8536, Japan 4 Research Laboratories, NTT DOCOMO, INC., Yokosuka, Kanagawa 239-8536, Japan 5 Product Department, NTT DOCOMO, INC., Yokosuka, Kanagawa 239-8536, Japan 6 R&D Information Service Department, DOCOMO Technology, Inc., Yokosuka, Kanagawa 239-8536, Japan 7 Faculty of Information Science, Aichi Institute of Technology, Toyota, Aichi 470-0392, Japan a) nabeko@ucl.nuee.nagoya-u.ac.jp door positioning methods have been studied to date. For example, there are methods based on radio waves such as Wi-Fi access points [1], [2], [3], [4], BLE (Bluetooth Low Energy) [5], [6], [7], and UWB (Ultra Wide Band) technology [8].…”