Mobile Object-Tracking Approach using A Combination of Fuzzy Logic and Neural Networks

Mobile Object-Tracking Approach using A Combination of Fuzzy Logic and Neural Networks

Dr. Jawdat Jamil Alshaer

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Al-Balqa Applied University

Mobile Object-Tracking Approach using A Combination of Fuzzy Logic and Neural Networks

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Abstract

Ability to locate a specific object in a dynamic environment has several practical applications including security surveillance, navigation and search and rescue operations. The objective of this paper is to develop an object-tracking algorithm using a combination of fuzzy logic and neural networks. The aim is to originate an algorithm that matches the history locations of an object and predicts its location when it goes offline. Determining the location of an object on specific trajectory becomes difficult if the mobile object stopped reporting its location and goes offline. Therefore, in this analytical article, a proposed approach relies on estimations from sensor data of historical movement patterns and geometric models, is fed into special Neural Network to get best accurate present or future object locations. Fuzzy logic application is used to overcome the challenge of imprecision in data. Although this approach is complex; but it can be one of the ways to be applied on large area applications with acceptable accuracy (80%) as shown by experiments.

References

16 Cites in Article

Reference Format

L Al-Matarneh (2014). Development of Temperaturebased Weather Forecasting Models Using Neural Networks and Fuzzy Logic.
Krasimira Kapitanova,Sang Son,Kyoung-Don Kang (2011). Using fuzzy logic for robust event detection in wireless sensor networks.
M Mozer (1998). The Neural Network House: An Environment that Adapts to its Inhabitants.
Michael Mozer (2004). Lessons from an Adaptive Home.
J Subramanian (2014). Implementation of Artificial Neural Network for Mobile Movement Prediction.
P Pakyan Learning and Predicting Moving Object Trajectory: a piecewise trajectory segment approach.
L Vintan (2004). Person Movement Prediction Using Neural Network.
Roberto Buizza (2001). Accuracy and Potential Economic Value of Categorical and Probabilistic Forecasts of Discrete Events.
Kai Nagel,Michael Schreckenberg (1992). A cellular automaton model for freeway traffic.
S Henver,J March,S Park,Ram (2004). Design Science in Information Systems Research‖.
Charu Aggarwal,Dakshi Agrawal (2003). On nearest neighbor indexing of nonlinear trajectories.
C Kothari (1990). Research Methodology‖, Methods and Techniques.
P Pakyan Learning and Predicting Moving Object Trajectory: A Piecewise Trajectory Segment Approach.
T Mitchell (1997). Machine Learning.
Tomáš Mikluščák,Michal Gregor,Aleš Janota (2011). Using Neural Networks for Route and Destination Prediction in Intelligent Transport Systems.
Vijay Vaishnavi,Vijay Vaishnavi,William Kuechler (2007). Design Science Research Methods and Patterns.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. Jawdat Jamil Alshaer. 2016. \u201cMobile Object-Tracking Approach using A Combination of Fuzzy Logic and Neural Networks\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 15 (GJCST Volume 15 Issue E8).

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GJCST Volume 15 Issue E8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

F.1.1 I.5.1

Submission ReceivedFebruary 13, 2015
Peer Review Double Blind
Handling Editor
Accepted March 1, 2015
Published March 15, 2015

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v1.2

Issue date

January 25, 2016

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Article Matrices

Total Score: 106

Country: Jordan

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: Dr. Jawdat Jamil Alshaer (PhD/Dr. count: 1)

View Count (all-time): 288

Total Views (Real + Logic): 7970

Total Downloads (simulated): 2014

Publish Date: 2016 01, Mon

Monthly Totals (Real + Logic):

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Total Views: 7970

Total Downloads: 2014

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