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Cloud-based Data An...
Cloud-based Data Analytics on Human Factor Measurement to Improve Safer Transport
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- Ahmed, Mobyen Uddin, 1976- (author)
- Mälardalens högskola,Inbyggda system
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- Begum, Shahina, 1977- (author)
- Mälardalens högskola,Inbyggda system
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- Catalina, Carlos Alberto (author)
- ITCL Polígono Industrial Villalonquéjar c/López Bravo, 70. 09001 BURGOS, Spain
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- Limonad, Lior (author)
- Smart Wearable and IoT Solutions, IBM Research, Haifa, Israil
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- Hök, Bertil (author)
- Hök Instrument AB, Sweden
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- Flumeri, Gianluca Di (author)
- Cognitive States in Operative Environment, BrainSigns, Italy
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(creator_code:org_t)
- 2018-02-17
- 2018
- English.
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In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225. - Cham : Springer International Publishing. - 9783319762128 ; , s. 101-106
- Related links:
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https://iris.uniroma...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- 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, Behavioural and Physiological 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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Keyword
- SimuSafe
- safer transport
- data-analysis
- big data
- human factor
Publication and Content Type
- ref (subject category)
- kon (subject category)
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