Encoding materials and data for iterative personalization

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Abstract

Data is changing how we design consumer products. Shoe production is a prime example of this; foot size, footstep pressure and personal preferences can be used to design personalized shoes. Research done around metamaterials, programming materials and computational composites illustrate the possibilities of creating complex data & material relationships. These new relationships allow us to look at future products almost like software apps, becoming a kind of product service systems, where the focus is on its iterative personalized improvement over time. Can we create systems of such data driven objects that in turn allow us to design new objects that are informed by the data trail? In this paper we report on four RtD project iterations that explore this challenge and provide a set of insights on how to close this new iterative loop.

Original languageEnglish
Title of host publicationCHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Number of pages13
ISBN (Electronic)978-1-4503-5970-2
DOIs
Publication statusPublished - 2 May 2019
Event37th ACM International Conference on Human Factors in Computing Systems (CHI2019) - Glasgow, UK, Glasgow, United Kingdom
Duration: 4 May 20199 May 2019
Conference number: 37
https://chi2019.acm.org
https://chi2019.acm.org/
https://chi2019.acm.org/
https://chi2019.acm.org/
https://chi2019.acm.org/

Conference

Conference37th ACM International Conference on Human Factors in Computing Systems (CHI2019)
Abbreviated titleCHI2019
CountryUnited Kingdom
CityGlasgow
Period4/05/199/05/19
Internet address

Keywords

  • Data and material relationship
  • Iterative design
  • Personalization
  • Programmable materials
  • Shoe design

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