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Opening the search space for the design of a future transport system using ‘big data’
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap, Vårdlogistik.
KTH, Skolan för teknik och hälsa (STH), Hälso- och systemvetenskap, Vårdlogistik.
2017 (engelsk)Inngår i: 15th International Conference on Computers in Urban Planning and Urban Management, 2017, Springer Berlin/Heidelberg, 2017, Vol. Part F4, s. 247-261Konferansepaper (Fagfellevurdert)
Abstract [en]

The advent of ‘big data’ already enables a wide range of conveniences to citizens. However, the dominant utilization of this data for systematic improvement is geared towards operations such as informing on real-time events in cities. The impact of big data on the long-term planning and design purposes in cities is still unclear. This chapter presents an application of big data where locations, suitable for deploying charging infrastructure for vehicles, are mined. We conducted an experiment to observe the impact of this information on designs of Electrical Road Systems (ERS). Results prove that insights mined from big data outside the design process do influence the designing process and the resulting designs. Therefore it seems promising to further explore this influence on the quality of designing.

sted, utgiver, år, opplag, sider
Springer Berlin/Heidelberg, 2017. Vol. Part F4, s. 247-261
Emneord [en]
Big data, Design process, Transport system
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-214645DOI: 10.1007/978-3-319-57819-4_14Scopus ID: 2-s2.0-85028673684ISBN: 9783319578187 (tryckt)OAI: oai:DiVA.org:kth-214645DiVA, id: diva2:1142296
Konferanse
15th International Conference on Computers in Urban Planning and Urban Management, 2017, Adelaide, Australia, 11 July 2017 through 14 July 2017
Merknad

QC 20170919

Tilgjengelig fra: 2017-09-19 Laget: 2017-09-19 Sist oppdatert: 2019-09-18bibliografisk kontrollert
Inngår i avhandling
1. Creating Knowledge with Data Science for Design in Systems
Åpne denne publikasjonen i ny fane eller vindu >>Creating Knowledge with Data Science for Design in Systems
2019 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Designing in large-scale engineering systems is a difficult cognitive task undertaken by experts. Knowledge of experts continually changes as they are confronted with similar by different problems in designing in such systems. However, it is also important that designers are presented information that is representative of the system,and that they are cognizant of activities on a system scale so they can create diverse choices for designs in early phase of design process.Data Science has been proven to be effective at informing people for decisions at immediate horizons. But the use of data science to drive long terms designs where experts have to make the right series of decisions i.e. designs is yet unknown. The use of data science is to inform decision makers of activities at system scale.In this thesis, I have looked at how data science can be used to create knowledge in designers for designing in large scale systems. I have also investigated further questions regarding imitation of expertise using AI, and in generating similar knowledge by creating diverse options in design.The results point out that data science can indeed inform designers, change their designs and hence create knowledge. They also point out that design cognition in experts can be partly imitated in data science itself, through careful modeling of the ill-defined problem in design. This therefore points to a promising future direction where data can be used as an interface between human thinking and machine learning, by translation of conceptual forms such as differential diagnoses and cognitive artefacts using data.

sted, utgiver, år, opplag, sider
KTH Royal Institute of Technology, 2019. s. 33
Serie
TRITA-CBH-FOU ; 46
Emneord
Data Science, Design Cognition, Transport, Healthcare, Artificial Intelligence, Imitation, Design Space Exploration
HSV kategori
Forskningsprogram
Teknik och hälsa
Identifikatorer
urn:nbn:se:kth:diva-259566 (URN)978-91-7873-299-9 (ISBN)
Disputas
2019-10-11, T2, Hälsovägen 11, 141 57, Huddinge, 09:30 (engelsk)
Opponent
Veileder
Merknad

QC 2019-09-20

Tilgjengelig fra: 2019-09-20 Laget: 2019-09-18 Sist oppdatert: 2019-10-18bibliografisk kontrollert

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