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FoodCoach: Societal Implications of Digital Receipt-based Diet Monitoring & Interventions enabled by Graph Analytics Techniques

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About the FoodCoach research project

Diet-related non-communicable diseases are the leading cause of mortality worldwide, accounting for more deaths than all other, non-diet-related mortality causes combined (Forouzanfar et al., 2015). Previous research on developing effective strategies to improve dietary consumption primarily focus on the individual level (Schneider, 2019), on monitoring dietary intake and behavioral interventions influencing dietary habits. Unfortunately, until today, such strategies that are enabled by digital dietary self-tracking remain limited by resource- and personal constraints (Vignerová et al. 2011), are discontinued due to the manual logging involved (Fuchs et al. 2018), are not tailored to the individual (Brug et al. 2003), or suffer under self-selection of healthy individuals (König et al. 2018).

Aiming to overcome these drawbacks, this interdisciplinary Swiss-Korean research collaboration entitled ‘FoodCoach’ proposes a novel, scalable and tailored approach towards diet monitoring and interventions. Therefore, we plan to apply artificial intelligence to process customers’ automatically collected digital receipts from grocery purchases in order to i) estimate households’ and individual dietary behavior, and ii) tailor adaptive interventions to participants, based on their purchase behavior and estimated nutritional context, in order to support healthier food choices.

Thereby, ‘FoodCoach’ aims to overcome the contemporary limitations of modern diet-related mobile health applications (mHealth). Simultaneously, the proposed project identifies potential adoption drivers (e.g. convenience) and barriers (e.g. privacy concerns) by exploring people’s lived experience of digital receipt-based dietary tracking based on survey and focus group research. This affords the opportunity for users’ responses (but also non-users’ responses) to co-shape the set-up of the study, the design of the interfaces, as well as the kinds of information and hence interventions provided. The project aims to compile the largest digital receipt-based diet panel globally and assess this novel approach’s accuracy, scalability, efficacy and ability to reach previously uninvolved users, an important prerequisite in the mitigation of diet-related diseases.

Collaborators

Swiss Collaborators

Prof. Tanja Schneider
Prof. Tanja SchneiderPrincipal Investigator & Associate Professor in Technology Studies @ SHSS
Tanja is a collaborator of the Auto-ID Labs ETH/HSG in the area of food & transparency. She is the PI of the SNF-NRF project ‘FoodCoach’ in which we collaborate on developing novel monitoring and intervention methods leveraging digital receipts and AI. She works at the Institute of Sociology (SfS-HSG) and her research interest includes Digital Food Activism.
Prof. Simon Mayer
Prof. Simon MayerAssociate Research Director, ICS-HSG
Simon heads the Chair for Interaction- and Communication-based Systems (ICS-HSG) at the University of St. Gallen. He is also affiliated with the Distributed Systems Group at ETH Zurich, as a Senior Scientist. Simon’s research concerns interactions of machines and people in industrial IoT settings.

 

Klaus Fuchs
Klaus FuchsAssociate Research Director, IM-ETH
Klaus works at the Chair of Information Management at ETH Zurich (IM-ETH) on Promoting Nutritional Literacy & Behavior Change based on Automated Purchase Logging & Food Product Databases. His research interest include Consumer mobile applications & diet-related mHealth applications.
Jie Lian
Jie LianDoctoral Researcher ICS HSG
Jie is a doctoral researcher at the Institute of Computer Science (ICS-HSG) at University of St. Gallen. Jie’s research interests include artificial intelligence and digital health.

 

Korean Collaborators

Prof. Jaewook Buyn
Prof. Jaewook BuynPrincipal Investigator & Assistant Professor, Halla University & Associate Director, Auto-ID Labs, KAIST
Jaewook received his Ph.D. degree in computer science from KAIST, Republic of Korea, in 2018. Currently, he is an assistant professor with Department of Information, Communication and Software Engineering, Halla University, Republic of Korea. His research interests include temporal graph, graph mining, graph database, semantic web, and the Internet of Things.
Dr. Sangtae Kim
Dr. Sangtae KimSenior Researcher, Auto-ID Labs & KI Institutes, KAIST
Sangtae Kim received his PhD degree in culture technology in KAIST in 2011. He is currently a senior researcher in KAIST Institutes for Information Technology Convergence and is also a member of Auto-ID Labs, KAIST. He has contributed to GS1 standardization activities since 2015, and is participating in EPCIS MSWG. He also is a member of TTA ICT International Standardization Committee for Smart Agriculture. His research interests include food traceability system and data visualization.
Funding
Working Group
Runtime

01.01.2020 – 31.12.2023

Partners
  • Bitsaboutme
  • Swiss Society for Nutrition
  • Adnexo
  • GS1 trustbox
  • FoodRepo
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