Internet of things(IoT)

You affect the world by what you browse ~Tim Berners-Lee.

Artificial Intelligence(AI)

Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks ~Stephen Hawking.

Industrialis

Power and wealth are not two of my main stakes ~Ratan Tata.

Autonomous

My opinion is it's a bridge too far to go to fully autonomous cars ~Elon Musk.

Robotics

Robotics and other combinations will make the world pretty fantastic compared with today ~Bill Gates.

Monday 11 May 2020

Active RFID Based Indoor Localization

By  May 11, 2020  1 comment
Abstract:
Indoor localization of staff and patients based on radio frequency identification (RFID) technology has promising potential application in the healthcare sector. The use of an active RFID in real-time indoor positioning system without any sacrifice of localization accuracy is intended to provide security, guidance and support service to patients. In this paper maximum likelihood estimation along with its Cramer-Rao lower bound of the locations of active RFID tags are presented by exploring the received signal strength indicator which is collected at the readers. The performance of real-time localization system is implemented by using an extended Kalman filter (EKF).


Published in: 2019 22th International Conference on Information Fusion (FUSION)
Date of Conference: 2-5 July 2019
Date Added to IEEE Xplore: 27 February 2020
 ISBN Information:
Electronic ISBN: 978-0-9964527-8-6
Print on Demand(PoD) ISBN:978-1-7281-1840-6
INSPEC Accession Number: 19411273
Publisher: IEEE
Conference Location: Ottawa, ON, Canada, Canada.
https://ieeexplore.ieee.org/abstract/document/9011191 this link will redirect you to a new window where the paper was published.
Regards,
dhanapar@uwindsor.ca
+1(519)-999-0056



Read More

Sunday 10 May 2020

Quickest Detection of Abnormal Vehicle Movements on Highways

By  May 10, 2020  4 comments
Abstract:
 The quest to develop self-driving vehicles remain an active research topic. A self-driving vehicle on a highway employs numerous sensors to track the state of its surrounding vehicles. Considering the proximity of surrounding vehicles, it is critical to detect their unusual maneuvers as quickly as possible, especially when autonomous vehicles operate among human-operated traffic. In this paper, we present an approach to quickly detect lane-changing maneuvers of a nearby vehicle. The proposed algorithm is based on the optimal likelihood ratio test, known as Page test. The proposed approach is presented in the form of a novel process model to be employed by autonomous vehicles. In addition to traditional states, such as position and velocity, the proposed process model adds two additional states of a surrounding vehicle being monitored: the lane-index (LIDX) and the lane-change-index (LcIDX). Then we present an approach to keep these two indices up to date in the quickest possible manner through the proposed Page test based algorithm.



Published in: 2019 22th International Conference on Information Fusion (FUSION)
Date of Conference: 2-5 July 2019
Date Added to IEEE Xplore: 27 February 2020
 ISBN Information:
Electronic ISBN: 978-0-9964527-8-6
Print on Demand(PoD) ISBN:978-1-7281-1840-6

INSPEC Accession Number: 19411393

Publisher: IEEE

Conference Location: Ottawa, ON, Canada, Canada.
https://ieeexplore.ieee.org/abstract/document/9011374
The above link will redirect to research paper.

Regards,
dhanapar@uwindsor.ca
+1(519)-999-0056

Read More