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1	e-DTS 2.0: A Next-Generation of a Distributed Tracking System Rybarczyk, Ryan Thomas 20 March 2012 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / A key component in tracking is identifying relevant data and combining the data in an effort to provide an accurate estimate of both the location and the orientation of an object marker as it moves through an environment. This thesis proposes an enhancement to an existing tracking system, the enhanced distributed tracking system (e-DTS), in the form of the e-DTS 2.0 and provides an empirical analysis of these enhancements. The thesis also provides suggestions on future enhancements and improvements. When a Camera identifies an object within its frame of view, it communicates with a JINI-based service in an effort to expose this information to any client who wishes to consume it. This aforementioned communication utilizes the JINI Multicast Lookup Protocol to provide the means for a dynamic discovery of any sensors as they are added or removed from the environment during the tracking process. The client can then retrieve this information from the service and perform a fusion technique in an effort to provide an estimation of the marker's current location with respect to a given coordinate system. The coordinate system handoff and transformation is a key component of the e-DTS 2.0 tracking process as it improves the agility of the system. Distributed Tracking System Vision-based Tracking Augmented Reality Multisensor data fusion Optical detectors Augmented reality
2	Designing and experimenting with e-DTS 3.0 Phadke, Aboli Manas 29 August 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / With the advances in embedded technology and the omnipresence of smartphones, tracking systems do not need to be confined to a specific tracking environment. By introducing mobile devices into a tracking system, we can leverage their mobility and the availability of multiple sensors such as camera, Wi-Fi, Bluetooth and Inertial sensors. This thesis proposes to improve the existing tracking systems, enhanced Distributed Tracking System (e-DTS 2.0) [19] and enhanced Distributed Object Tracking System (eDOTS)[26], in the form of e-DTS 3.0 and provides an empirical analysis of these improvements. The enhancements proposed are to introduce Android-based mobile devices into the tracking system, to use multiple sensors on the mobile devices such as the camera, the Wi-Fi and Bluetooth sensors and inertial sensors and to utilize possible resources that may be available in the environment to make the tracking opportunistic. This thesis empirically validates the proposed enhancements through the experiments carried out on a prototype of e-DTS 3.0. Opportunistic Tracking Android-based tracking Distributed Tracking System Indoor tracking system Smartphone-based indoor tracking system Embedded computer systems -- Programming Embedded computer systems -- Reliability Mobile computing Bluetooth technology Multisensor data fusion Sensor networks Androids Remote sensing Wireless LANs Global Positioning System Ubiquitous computing Cell phone systems Ad hoc networks (Computer networks)

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e-DTS 2.0: A Next-Generation of a Distributed Tracking System

Designing and experimenting with e-DTS 3.0