Skip to main content

Research Repository

Advanced Search

Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance. (2016)
Conference Proceeding
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

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

Designing a context-aware cyber physical system for detecting security threats in motor vehicles. (2015)
Conference Proceeding
PETROVSKI, A., RATTADILOK, P. and PETROVSKI, S. 2015. Designing a context-aware cyber physical system for detecting security threats in motor vehicles. In Proceedings of the 8th International conference on security of information and networks (SIN'15), 8-10 September 2015, Sochi, Russia. New York: ACM [online], pages 267-270. Available from: https://doi.org/10.1145/2799979.2800029

An adaptive multi-tiered framework, which can be utilised for designing a context-aware cyber physical system is proposed in the paper and is applied within the context of providing data availability by monitoring electromagnetic interference. The ad... Read More about Designing a context-aware cyber physical system for detecting security threats in motor vehicles..

Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence. (2014)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2014. Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence. In Proceedings of the 2014 IEEE symposium on evolving and autonomous learning systems (EALS 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 7009508, pages 87-94. Available from: https://doi.org/10.1109/EALS.2014.7009508

A generic framework for evolving and autonomously controlled systems has been developed and evaluated in this paper. A three-phase approach aimed at identification, classification of anomalous data and at prediction of its consequences is applied to... Read More about Self-learning data processing framework based on computational intelligence enhancing autonomous control by machine intelligence..

Automated inferential measurement system for traffic surveillance: enhancing situation awareness of UAVs by computational intelligence. (2014)
Conference Proceeding
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

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

Anomaly monitoring framework based on intelligent data analysis. (2013)
Conference Proceeding
RATTADILOK, P., PETROVSKI, A. and PETROVSKI, S. 2013. Anomaly monitoring framework based on intelligent data analysis. In Yin, H., Tang, K., Gao, Y., Klawonn, F., Lee, M., Weise, T., Li, B. and Yao, X. (eds.) Proceedings of the 14th International conference on intelligent data engineering and automated learning (IDEAL 2013), 20-23 October 2013, Hefei, China. Lecture notes in computer science, 8206. Berlin: Springer [online], pages 134-141. Available from: https://doi.org/10.1007/978-3-642-41278-3_17

Real-time data processing has become an increasingly important challenge as the need for faster analysis of big data widely manifests itself. In this research, several methods of Computational Intelligence have been applied for identifying possible a... Read More about Anomaly monitoring framework based on intelligent data analysis..

Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. (2013)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2013. Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. In Proceedings of the 2013 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA 2013), 15-17 July 2013, Milan, Italy. New York: IEEE [online], article number 6617402, pages 93-98. Available from: https://doi.org/10.1109/CIVEMSA.2013.6617402

The paper proposes a generic approach to building inferential measurement systems. The large amount of data needed to be acquired and processed by such systems necessitates the use of machine learning techniques. In this study, an inferential measure... Read More about Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning..