Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence.

Rattadilok, Prapa; Petrovski, Andrei

Abstract

An adaptive inferential measurement framework for control and automation systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making inferences related to the presence of anomalies in the surveillance data with the help of statistical, computational and clustering analysis. Moreover, the performance of the ensemble of these tools can be dynamically tuned by a computational intelligence technique. The experimental results have demonstrated that the framework is generally applicable to various problem domains and reasonable performance is achieved in terms of inferential accuracy. Computational intelligence can also be effectively utilised for identifying the main contributing features in detecting anomalous data points within the surveillance data.

Citation

RATTADILOK, P. and PETROVSKI, A. 2014. Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence. In Proceedings of the 2014 IEEE symposium on computational intelligence in control and automation (CICA 2014), part of the 2014 IEEE symposium series on computational intelligence (SSCI 2014), 9-12 December 2014, Orlando, USA. New York: IEEE [online], article number 7013256, pages 229-236. Available from: https://doi.org/10.1109/CICA.2014.7013256

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2014 IEEE symposium on computational intelligence in control and automation (CICA 2014)
• Start Date: Dec 9, 2014
• End Date: Dec 12, 2014
• Acceptance Date: Sep 5, 2014
• Online Publication Date: Dec 9, 2014
• Publication Date: Jan 19, 2015
• Deposit Date: Feb 12, 2015
• Publicly Available Date: Feb 12, 2015
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Article Number: 7013256
• Pages: 229-236
• Series Title: Proceedings of the IEEE symposium on computational intelligence in control and automation
• ISBN: 9781479945313
• DOI: https://doi.org/10.1109/CICA.2014.7013256
• Keywords: Computational intelligence; Inferential measurement situation awareness; Data anomalies; Traffic surveillance; Unmanned aerial vehicles
• Public URL: http://hdl.handle.net/10059/1143
• Contract Date: Feb 12, 2015