Cloud-Based Data Analytics on Human Factor Measurement to Improve Safer Transport
Autor: | Bertil Hök, Gianluca Di Flumeri, Shahina Begum, Mobyen Uddin Ahmed, Lior Limonad, Carlos A. Catalina |
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Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Computer science
SimuSafe safer transport data-analysis big data human factor Big data 050109 social psychology Cloud computing 02 engineering and technology Variation (game tree) SAFER Factor (programming language) Human factor 0202 electrical engineering electronic engineering information engineering 0501 psychology and cognitive sciences Data-analysis computer.programming_language business.industry 05 social sciences Cognition Data science SimuSafe Categorization Safer transport Data analysis 020201 artificial intelligence & image processing business computer |
Zdroj: | Internet of Things (IoT) Technologies for HealthCare Internet of Things (IoT) Technologies for HealthCare ISBN: 9783319762128 HealthyIoT Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering-Internet of Things (IoT) Technologies for HealthCare |
ISSN: | 1867-8211 1867-822X |
Popis: | 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. |
Databáze: | OpenAIRE |
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