Improving safer transport includes individual and collective behavioural aspects and their interaction. A system that can monitor and evaluate the human cognitive and physical capacities based on human factor measurement is often beneficial to improve safety in driving condition. However, analysis and evaluation of human factor measurement i.e. demographics, behaviour and physiology in real-time is challenging. This paper presents a methodology for cloud-based data analysis, categorization and metrics correlation in real-time through a H2020 project called SimuSafe. Initial implementation of this methodology shows a step-by-step approach which can handle huge amount of data with variation and verity in the cloud.
CITATION STYLE
Ahmed, M. U., Begum, S., Catalina, C. A., Limonad, L., Hök, B., & Di Flumeri, G. (2018). Cloud-Based Data Analytics on Human Factor Measurement to Improve Safer Transport. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 225, pp. 101–106). Springer Verlag. https://doi.org/10.1007/978-3-319-76213-5_14
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