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Omnifood – Exploring the Possibilities of a Consumer System With Ubiquitous Access to Data About the Food We Eat
KTH, School of Industrial Engineering and Management (ITM), Learning, Learning in Stem.ORCID iD: 0000-0001-6457-5231
2022 (English)In: Eighth conference on computing within limits, 2022, PubPub , 2022Conference paper, Published paper (Refereed)
Abstract [en]

Data about food, and data about individuals’ purchases and consumption of food are becoming increasingly ubiquitous. Through bonus cards, supermarkets can track exactly which products we buy, through diet apps we can track what we eat, and through blockchains and other technologies producers can track the origin and history of individual products. From a technical point of view, we are not far away from a world where all this information could be combined to one omniscient system - OmniFood. In this paper we explore current possibilities to collect data on what products we buy, how environmental and nutritional data can be mapped to these products and possibilities to track what we actually eat. Next, we present a number of prototype systems where the possibilities to use this data has been explored, and what limitations we have encountered with current implementations and available data. We end with a discussion of some services that could be possible if current technologies would be fully implemented and made available to consumers and system developers. What possibilities could such systems offer for consumers who want to eat both sustainable and healthy food? What limitations would still exist? What ethical aspects would need to be considered? The focus is on using such a system as a decision support system to support consumers in making food purchase choices that are sustainable from both environmental and health perspectives, thereby supporting the global food system to stay within sustainable limits.

Place, publisher, year, edition, pages
PubPub , 2022.
Keywords [en]
Sustainable Food Systems, Sustainable HCI, Behavior Change, Digital Behavior Change, Consumption Data, Sustainability Data
National Category
Human Computer Interaction
Research subject
Technology and Learning; Human-computer Interaction
Identifiers
URN: urn:nbn:se:kth:diva-314277DOI: 10.21428/bf6fb269.1e8b10afOAI: oai:DiVA.org:kth-314277DiVA, id: diva2:1676388
Conference
LIMITS’22, Eighth conference on computing within limits, June 21-22, 2022
Funder
Vinnova, 2018-04115
Note

QC 20220627

Available from: 2022-06-25 Created: 2022-06-25 Last updated: 2022-06-27

Open Access in DiVA

fulltext(1706 kB)532 downloads
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File name FULLTEXT01.pdfFile size 1706 kBChecksum SHA-512
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Publisher's full texthttps://limits.pubpub.org/pub/omni/release/1

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Hedin, Björn

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
  • rtf