Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning.
MetadataShow full item record
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). 15-17 July 2013. Piscataway, NJ: IEEE. Pp. 93 – 98.
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 measurement system aimed at enhancing situation awareness has been developed and tested on simulated traffic surveillance data. The performance of several Computational Intelligence techniques within this system has been examined and compared on the data containing anomalous driving patterns.