Object Tracking Based on the Prediction of Trajectory in Wireless Sensor Networks

Wireless sensor network has been used for many years, and a great number of schemes and applications have been developed based on it. Object tracking is one of key tasks which are required in a number of applications of WSN. In this paper we propose an efficient prediction-based object tracking scheme employing the face network topology. The proposed scheme uses the trajectory of the object and enhanced least square method to predict the path. Computer simulation reveals that the proposed scheme improves the tracking accuracy and energy efficiency compared to the existing prediction-based scheme. The improvement gets more significant as the moving speed of the object becomes higher.

[1]  Paolo Santi,et al.  The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks , 2003, IEEE Trans. Mob. Comput..

[2]  Leong Wai Yie,et al.  Investigating Target Detection and Localization in Wireless Sensor Network , 2012 .

[3]  Chao-Chun Chen,et al.  Model-based object tracking in wireless sensor networks , 2011, Wirel. Networks.

[4]  K. Ramya,et al.  A Survey on Target Tracking Techniques in Wireless Sensor Networks , 2012 .

[5]  Hee Yong Youn,et al.  Tree-Based Clustering(TBC) for Energy Efficient Wireless Sensor Networks , 2010, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.

[6]  Chao-Chun Chen,et al.  POOT: An efficient object tracking strategy based on short-term optimistic predictions for face-structured sensor networks , 2012, Comput. Math. Appl..

[7]  Biplab Sikdar,et al.  A protocol for tracking mobile targets using sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[8]  Wang-Chien Lee,et al.  Dual prediction-based reporting for object tracking sensor networks , 2004, The First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004..

[9]  Hee Yong Youn,et al.  An Energy Efficient Clustering Scheme for Self-Organizing Distributed Wireless Sensor Networks , 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

[10]  Hee Yong Youn,et al.  An Energy-Efficient MAC Protocol Employing Dynamic Threshold for Wireless Sensor Networks , 2012, Int. J. Distributed Sens. Networks.

[11]  Tzung-Shi Chen,et al.  Mobile object tracking in wireless sensor networks , 2007, Comput. Commun..

[12]  Chao-Chun Chen,et al.  Short-Term Prediction-Based Optimistic Object Tracking Strategy in Wireless Sensor Networks , 2011, 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing.

[13]  Wang-Rong Chang,et al.  CODA: A Continuous Object Detection and Tracking Algorithm for Wireless Ad Hoc Sensor Networks , 2008, 2008 5th IEEE Consumer Communications and Networking Conference.

[14]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[15]  Yu-Chee Tseng,et al.  Efficient in-network moving object tracking in wireless sensor networks , 2006, IEEE Transactions on Mobile Computing.

[16]  Voon Chin Phua,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1999 .

[17]  John R. Wolberg,et al.  Data Analysis Using the Method of Least Squares: Extracting the Most Information from Experiments , 2005 .

[18]  T. Andrew Yang,et al.  OCO: Optimized Communication & Organization for Target Tracking in Wireless Sensor Networks , 2006, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC'06).

[19]  Yu-Chee Tseng,et al.  Structures for in-network moving object tracking in wireless sensor networks , 2004, First International Conference on Broadband Networks.

[20]  Chenyang Lu,et al.  Reliable mobicast via face-aware routing , 2004, IEEE INFOCOM 2004.

[21]  Radhakisan Baheti.  Efficient Approximation of Kalman Filter for Target Tracking , 1986, IEEE Transactions on Aerospace and Electronic Systems.

[22]  Feng Zhao,et al.  Information-Driven Dynamic Sensor Collaboration for Tracking Applications , 2002 .

[23]  Li Zhang,et al.  Prediction-based energy-efficient target tracking protocol in wireless sensor networks , 2010 .

[24]  Chenyang Lu,et al.  FAR: Face-aware routing for mobicast in large-scale sensor networks , 2005, TOSN.

[25]  W..  Relative Neighborhood Graphs and Their Relatives , 2004 .

[26]  Shashi Phoha,et al.  Space-time Coordinated Distributed Sensing Algorithms for Resource Efficient Narrowband Target Localization and Tracking , 2005, Int. J. Distributed Sens. Networks.