Abstract
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.
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References
Elander, J., West, R., French, D.: Behavioural correlates of individual differences in road-traffic crash risk: an examination of methods and findings. Psychol. Bull. 113(2), 279 (1993)
Feyer, A.M., Williamson, A., Friswell, R.: Balancing work and rest to combat driver fatigue: an investigation of two-up driving in Australia. Accid. Anal. Prevention 29, 541–553 (1997)
Katal, A., Wazid, M., Goudar, R.H.: Big data: issues, challenges, tools and good practices. In: Contemporary Computing (IC3), pp. 404–409 (2013)
Zhang, D.: Inconsistencies in big data. In: 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), pp. 61–67 (2013)
Rathore, M.M., Ahmad, A., Paul, A., Daniel, A.: Hadoop based real-time big data architecture for remote sensing earth observatory system. In: 2015 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1–7 (2015)
Xhafa, F., Naranjo, V., Caball, S.: Processing and analytics of big data streams with Yahoo! S4. In: 2015 IEEE 29th International Conference on Advanced Information Networking and Applications, pp. 263–270 (2015)
Begum, S., Barua, S., Filla, R., Ahmed, M.U.: Classification of physiological signals for wheel loader operators using multi-scale entropy analysis and case-based reasoning. Expert Syst. Appl. 41, 295–305 (2014)
Begum, S., Barua, S., Ahmed, M.U.: Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning. Sensors 14, 11770 (2014)
Barua, S., Begum, S., Ahmed, M.U.: Clustering based approach for automated EEG artifacts handling. In: 13th Scandinavian Conference on Artificial Intelligence (SCAI 2015) (2015)
Fu, T.-C.: A review on time series data mining. Eng. Appl. Artif. Intell. 24, 164–181 (2011)
Ahmed, M.U., Funk, P.: A computer aided system for post-operative pain treatment combining knowledge discovery and case-based reasoning. In: Agudo, B.D., Watson, I. (eds.) ICCBR 2012. LNCS (LNAI), vol. 7466, pp. 3–16. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32986-9_3
Banaee, H., Ahmed, M.U., Loutfi, A.: Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges. Sensors 13, 17472–17500 (2013)
Ahmed, M.U., Banaee, H., Loutfi, A.: Health monitoring for elderly: an application using case-based reasoning and cluster analysis. ISRN Artif. Intell. 2013, 11 (2013)
Arico, P., Borghini, G., Di Flumeri, G., Sciaraffa, N., Colosimo, A., Babiloni, F.: Passive BCI in operational environments: insights, recent advances and future trends. IEEE Trans. Biomed. Eng. 64, 1431–1436 (2017)
Acknowledgments
The authors would like to acknowledge the project SimuSafe, the project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 723386.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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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: Ahmed, M., Begum, S., Fasquel, JB. (eds) Internet of Things (IoT) Technologies for HealthCare. HealthyIoT 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-319-76213-5_14
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DOI: https://doi.org/10.1007/978-3-319-76213-5_14
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