@inproceedings{a4e4173fbb964e8a87cda6f67d0824f0,
title = "Automated inferential measurement system for traffic surveillance: Enhancing situation awareness of UAVs by computational intelligence",
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.",
keywords = "computational intelligence, data anomalies, inferential measurement, situation awareness, traffic surveillance, unmanned aerial vehicles",
author = "Prapa Rattadilok and Andrei Petrovski",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 4th IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2014 ; Conference date: 09-12-2014 Through 12-12-2014",
year = "2014",
month = jan,
day = "16",
doi = "10.1109/CICA.2014.7013256",
language = "English",
series = "IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CICA 2014: 2014 IEEE Symposium on Computational Intelligence in Control and Automation, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CICA 2014",
address = "United States",
}