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

Dr. Jawdat Jamil Alshaer

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

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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.

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

Keywords

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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 January 25, 2016

Version of record

v1.2

Issue date

January 25, 2016

Language

English

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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): 530

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Publish Date: 2015 03, Sun

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