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Opening the search space for the design of a future transport system using ‘big data’
KTH, School of Technology and Health (STH), Health Systems Engineering, Health Care Logistics.
KTH, School of Technology and Health (STH), Health Systems Engineering, Health Care Logistics.
2017 (English)In: 15th International Conference on Computers in Urban Planning and Urban Management, 2017, Springer Berlin/Heidelberg, 2017, Vol. Part F4, p. 247-261Conference paper (Refereed)
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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2017. Vol. Part F4, p. 247-261
Keywords [en]
Big data, Design process, Transport system
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-214645DOI: 10.1007/978-3-319-57819-4_14Scopus ID: 2-s2.0-85028673684ISBN: 9783319578187 (print)OAI: oai:DiVA.org:kth-214645DiVA, id: diva2:1142296
Conference
15th International Conference on Computers in Urban Planning and Urban Management, 2017, Adelaide, Australia, 11 July 2017 through 14 July 2017
Note

QC 20170919

Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2019-09-18Bibliographically approved
In thesis
1. Creating Knowledge with Data Science for Design in Systems
Open this publication in new window or tab >>Creating Knowledge with Data Science for Design in Systems
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019. p. 33
Series
TRITA-CBH-FOU ; 46
Keywords
Data Science, Design Cognition, Transport, Healthcare, Artificial Intelligence, Imitation, Design Space Exploration
National Category
Computer Systems Health Sciences Transport Systems and Logistics
Research subject
Technology and Health
Identifiers
urn:nbn:se:kth:diva-259566 (URN)978-91-7873-299-9 (ISBN)
Public defence
2019-10-11, T2, Hälsovägen 11, 141 57, Huddinge, 09:30 (English)
Opponent
Supervisors
Note

QC 2019-09-20

Available from: 2019-09-20 Created: 2019-09-18 Last updated: 2019-10-18Bibliographically approved

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