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Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance.

Petrovski, Andrei; Rattadilok, Prapa; Petrovskii, Sergey

Authors

Prapa Rattadilok

Sergey Petrovskii



Contributors

Chrisina Jayne
Editor

Lazaros Iliadis
Editor

Abstract

An adaptive framework for building intelligent measurement systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making intelligent decisions related to the presence of anomalies in the surveillance data with the help of statistical analysis, computational intelligent and machine learning. Computational intelligence can also be effectively utilised for identifying the main contributing features in detecting anomalous data points within the surveillance data. The experimental results have demonstrated that a reasonable performance is achieved in terms of inferential accuracy and data processing speed.

Citation

PETROVSKI, A., RATTADILOK, P. and PETROVSKII, S. 2016. Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance. In Jayne, C. and Iliadis, L. (eds.) Engineering applications of neural networks: proceedings of the 17th International engineering applications of neural networks conference (EANN 2016), 2-5 September 2016, Aberdeen, UK. Communications in computer and information science, 629. Cham: Springer [online], pages 161-175. Available from: https://doi.org/10.1007/978-3-319-44188-7_12 161-175. Available from: https://doi.org/10.1007/978-3-319-44188-7_12

Conference Name 17th International engineering applications of neural networks conference (EANN 2016)
Conference Location Aberdeen, UK
Start Date Sep 2, 2016
End Date Sep 5, 2016
Acceptance Date Jun 5, 2016
Online Publication Date Aug 19, 2016
Publication Date Sep 30, 2016
Deposit Date Jun 6, 2017
Publicly Available Date Jun 6, 2017
Print ISSN 1865-0929
Publisher Springer
Pages 161-175
Series Title Communications in computer and information science
Series Number 629
Series ISSN 1865-0929
ISBN 9783319441870
DOI https://doi.org/10.1007/978-3-319-44188-7_12
Keywords Intelligent measurement; Traffic surveillance; Data anomalies; Computational intelligence; Artificial neural networks; Cyber physical system
Public URL http://hdl.handle.net/10059/2360

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