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Wireless Indoor Location Estimation Based on Neural Network RSS Signature Recognition (LENSR)

Description: Location Based Services (LBS), context aware applications, and people and object tracking depend on the ability to locate mobile devices, also known as localization, in the wireless landscape. Localization enables a diverse set of applications that include, but are not limited to, vehicle guidance in an industrial environment, security monitoring, self-guided tours, personalized communications services, resource tracking, mobile commerce services, guiding emergency workers during fire emergencies, habitat monitoring, environmental surveillance, and receiving alerts. This paper presents a new neural network approach (LENSR) based on a competitive topological Counter Propagation Network (CPN) with k-nearest neighborhood vector mapping, for indoor location estimation based on received signal strength. The advantage of this approach is both speed and accuracy. The tested accuracy of the algorithm was 90.6% within 1 meter and 96.4% within 1.5 meters. Several approaches for location estimation using WLAN technology were reviewed for comparison of results.
Date: June 1, 2008
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department

Nightmares with Mobile Devices Are Just Around the Corner!

Description: Mobile Devices (MDs) such as Personal Digital Assistants (PDAs), smart phones, handheld personal computers, and Tablet PCs, are proliferating in the marketplace. Cheap and ubiquitous mobile computing devices represent computing’s fifth wave [1], bringing about new opportunities in the marketplace. As MDs become more powerful and commonplace with ubiquitous connectivity, the line that currently divides these handheld devices from typical network computers will become very unclear. Mobile devices have become integrated into the business processes of both government and commercial institutions. MDs are small, portable, and able to store large amounts of information. The breadth of communication options (infrared, wireless, docking station) for MDs introduces many security risks. Some of the problems associated with MDs are: easy to loose, misplace, or have stolen, potential loss/comprise of company data (user ids, passwords, contacts, sensitive documentation, credit card numbers), increases the opportunity for a backdoor into an enterprise’s network, lack of authentication and limited logging capability. The use of these devices poses a risk to the security of an organization.
Date: March 1, 2007
Creator: Derr, Kurt
Partner: UNT Libraries Government Documents Department

Intelligent Control in Automation Based on Wireless Traffic Analysis

Description: Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.
Date: August 1, 2007
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department

Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments

Description: Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.
Date: May 1, 2009
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department

DSTiPE Algorithm for Fuzzy Spatio-Temporal Risk Calculation in Wireless Environments

Description: Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculation DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.
Date: September 1, 2008
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department

Intelligent Control in Automation Based on Wireless Traffic Analysis

Description: Wireless technology is a central component of many factory automation infrastructures in both the commercial and government sectors, providing connectivity among various components in industrial realms (distributed sensors, machines, mobile process controllers). However wireless technologies provide more threats to computer security than wired environments. The advantageous features of Bluetooth technology resulted in Bluetooth units shipments climbing to five million per week at the end of 2005 [1, 2]. This is why the real-time interpretation and understanding of Bluetooth traffic behavior is critical in both maintaining the integrity of computer systems and increasing the efficient use of this technology in control type applications. Although neuro-fuzzy approaches have been applied to wireless 802.11 behavior analysis in the past, a significantly different Bluetooth protocol framework has not been extensively explored using this technology. This paper presents a new neurofuzzy traffic analysis algorithm of this still new territory of Bluetooth traffic. Further enhancements of this algorithm are presented along with the comparison against the traditional, numerical approach. Through test examples, interesting Bluetooth traffic behavior characteristics were captured, and the comparative elegance of this computationally inexpensive approach was demonstrated. This analysis can be used to provide directions for future development and use of this prevailing technology in various control type applications, as well as making the use of it more secure.
Date: September 1, 2007
Creator: Derr, Kurt & Manic, Milos
Partner: UNT Libraries Government Documents Department