Object tracking using wireless sensor networks

Download
Author
Salatas, Vlasios.
Date
2005-09Advisor
Singh, Gurminder
Das, Arijit
Metadata
Show full item recordAbstract
Wireless sensor network (WSN) is a promising new technology. It could be a way to achieve ubiquitous computing and embedded Internet. WSNs are an efficient solution for applications that involve deep monitoring of a deployment environment. The objective of this thesis is to explore the use of WSNs for object tracking and motion estimation. It introduces the WSN technology, their theoretical characteristics, system constraints, WSN architectures, deployment topologies and standards. The object-tracking system that this thesis introduces, demonstrates a real-world application that uses a WSN to track objects and communicate their information. It is an event-driven application implemented in Java, built on top of the Crossbow MSP 410 wireless sensor system. The algorithm process the data returned from the WSN detection signals and tracks the object's motion. Deployment scenarios are proposed that demonstrate suitable node topologies for the system. The evaluation of the object-tracking system is performed by conducting a number of indoor and outdoor experiments.
Collections
Related items
Showing items related by title, author, creator and subject.
-
Design, implementation, and testing of a real-time software system for a quaternion-based attitude estimation filter
Duman, Ildeniz. (Monterey, California: Naval Postgraduate School, 1999-03);Human limb segment angle tracking requires a system which can track through all orientations. The major problem addressed by this research was to develop a real time inertial motion tracking system based on quaternions to ... -
Multiframe Temporal Estimation of Cardiac Nonrigid Motion
McEachen, John C. II; Nehorai, Arye; Duncan, James S. (IEEE, 2000-04);A robust, flexible system for tracking the point to point nonrigid motion of the left ventricular (LV) endocardial wall in image sequences has been developed. This system is unique in its ability to model motion ... -
Onboard and parts-based object detection from aerial imagery
Zaborowski, Robert Michael (Monterey, California. Naval Postgraduate School, 2011-09);The almost endless amount of full-motion video (FMV) data collected by Unmanned Aerial Vehicles (UAV) and similar sources presents mounting challenges to human analysts, particularly to their sustained attention to detail ...