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

Petrovski, Andrei; Rattadilok, Prapa; Petrovskii, Sergey


Andrei Petrovski

Prapa Rattadilok

Sergey Petrovskii


Chrisina Jayne

Lazaros Iliadis


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.

Start Date Sep 2, 2016
Publication Date Sep 30, 2016
Print ISSN 1865-0929
Publisher Springer (part of Springer Nature)
Pages 161-175
Series Title Communications in computer and information science
Series Number 629
Series ISSN 1865-0929
ISBN 9783319441870
Institution 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: 161-175. Available from:
Keywords Intelligent measurement; Traffic surveillance; Data anomalies; Computational intelligence; Artificial neural networks; Cyber physical system


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