Novel Dynamic KNN with Adaptive Weighting Mechanism for Beacon-based Indoor Positioning System

This work proposes a novel dynamic K Nearest Neighbor (KNN) with an adaptive weighting (DKNN-AW) mechanism that performs beacon-based indoor positioning. Four cases are used to prove that DKNN-AW (Dynamic KNN algorithm with Adaptive Weight algorithm) is better than KNN (k-Nearest Neighbors algorithm), KNN-W (KNN with Weight algorithm), DKNN (Dynamic KNN algorithm) and DKNN-W (Dynamic KNN with Weight algorithm). The experimental results demonstrate that, in terms of approximate positioning accuracy, the proposed mechanism outperforms exiting mechanism such as KNN, DKNN, KNN-W and DKNN-W.

[1]  Anindya Iqbal,et al.  On demand-driven movement strategy for moving beacons in sensor localization , 2014, J. Netw. Comput. Appl..

[2]  David Taniar,et al.  Indexing Moving Objects in Indoor Cellular Space , 2012, 2012 15th International Conference on Network-Based Information Systems.

[3]  Shigehiro Ano,et al.  Short paper: experimental study of long-term operation of BLE tags for realizing indoor location based service , 2015, 2015 18th International Conference on Intelligence in Next Generation Networks.

[4]  Shinji Uebayashi,et al.  A Study of TDOA Positioning Using UWB Reflected Waves , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[5]  Doo-Seop Eom,et al.  A TDoA-based localization using precise time-synchronization , 2012, 2012 14th International Conference on Advanced Communication Technology (ICACT).

[6]  Aboelmagd Noureldin,et al.  Dynamic Propagation Modeling for Mobile Users' Position and Heading Estimation in Wireless Local Area Networks , 2012, IEEE Wireless Communications Letters.

[7]  Veena Gulhane,et al.  Hybrid Mechanism for Multiple User Indoor Localization Using Smart Antenna , 2015, 2015 Fifth International Conference on Advanced Computing & Communication Technologies.

[8]  Jenq-Shiou Leu,et al.  Received Signal Strength Fingerprint and Footprint Assisted Indoor Positioning Based on Ambient Wi-Fi Signals , 2012, 2012 IEEE 75th Vehicular Technology Conference (VTC Spring).

[9]  Kaveh Pahlavan,et al.  Modeling the effect of human body on TOA ranging for indoor human tracking with wrist mounted sensor , 2013, 2013 16th International Symposium on Wireless Personal Multimedia Communications (WPMC).

[10]  Bala Srinivasan,et al.  Partial Fingerprint Matching through Region-Based Similarity , 2014, 2014 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

[11]  Yasmine A. Fahmy,et al.  Two-way TOA with limited dead reckoning for GPS-free vehicle localization using single RSU , 2013, 2013 13th International Conference on ITS Telecommunications (ITST).

[12]  Shing-Tsaan Huang,et al.  ALRD: AoA Localization with RSSI Differences of Directional Antennas for Wireless Sensor Networks , 2012, International Conference on Information Society (i-Society 2012).

[13]  M. H. Park,et al.  GPS-tag for indoor location information and additional user information providing , 2012, 2012 14th International Conference on Advanced Communication Technology (ICACT).

[14]  Jun Park,et al.  Digital map based pose improvement for outdoor Augmented Reality , 2012, 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR).

[15]  Yunhao Liu,et al.  LANDMARC: Indoor Location Sensing Using Active RFID , 2004, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[16]  Fuqiang Liu,et al.  Indoor Location Position Based on Bluetooth Signal Strength , 2015, 2015 2nd International Conference on Information Science and Control Engineering.

[17]  Akira Fukuda,et al.  A Multilateration-based Localization Scheme for Adhoc Wireless Positioning Networks Used in Information-oriented Construction , 2013, 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA).

[18]  Chengbiao Fu,et al.  GPS Single Point Positioning Algorithm Based on Least Squares , 2013, 2013 Sixth International Symposium on Computational Intelligence and Design.

[19]  Song Yang,et al.  Design of an experimental indoor position system based on RSSI , 2010, The 2nd International Conference on Information Science and Engineering.

[20]  Subrat Kar,et al.  Novel RSSI evaluation models for accurate indoor localization with sensor networks , 2014, 2014 Twentieth National Conference on Communications (NCC).

[21]  Joe-Air Jiang,et al.  A Distributed RSS-Based Localization Using a Dynamic Circle Expanding Mechanism , 2013, IEEE Sensors Journal.

[22]  Ma Yan,et al.  Wireless Local Area Network Assisted GPS in Seamless Positioning , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[23]  Mohamad Yassin,et al.  Performance comparison of positioning techniques in Wi-Fi networks , 2014, 2014 10th International Conference on Innovations in Information Technology (IIT).

[24]  José Luis Lázaro,et al.  Infrared local positioning system using phase differences , 2014, 2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS).

[25]  Christoph Busch,et al.  A novel approach used for measuring fingerprint orientation of arch fingerprint , 2014, 2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[26]  Mohammed Abdul Qadeer,et al.  GPS Locator: An Application for Location Tracking and Sharing Using GPS for Java Enabled Handhelds , 2011, 2011 International Conference on Computational Intelligence and Communication Networks.

[27]  Regina Kaune,et al.  Accuracy studies for TDOA and TOA localization , 2012, 2012 15th International Conference on Information Fusion.

[28]  Marcos V. T. Heckler,et al.  Hybrid method uses RSS and AoA to establish a low-cost localization system , 2013, 2013 Fourth Argentine Symposium and Conference on Embedded Systems (SASE/CASE).