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Future Internet 2015, 7(4), 372-392; doi:10.3390/fi7040372

Towards an “Internet of Food”: Food Ontologies for the Internet of Things

1
The Alexander Graham Bell Centre for Digital Health, University of the Highlands and Islands, Elgin, IV30 1JJ Scotland, UK
2
Distributed and Collaborative Virtual Environments Research (DISCOVER) Lab, University of Ottawa, Ottawa K1N6N5, Canada
3
College of Engineering and Natural Sciences, Istanbul Şehir University, Istanbul 34662, Turkey
4
Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
5
Faculty of Education, Naresuan University, Phitsanulok 65000, Thailand
*
Author to whom correspondence should be addressed.
Academic Editor: Andrew Hudson-Smith
Received: 23 July 2015 / Revised: 7 September 2015 / Accepted: 24 September 2015 / Published: 1 October 2015
View Full-Text   |   Download PDF [5274 KB, uploaded 1 October 2015]   |  

Abstract

Automated food and drink recognition methods connect to cloud-based lookup databases (e.g., food item barcodes, previously identified food images, or previously classified NIR (Near Infrared) spectra of food and drink items databases) to match and identify a scanned food or drink item, and report the results back to the user. However, these methods remain of limited value if we cannot further reason with the identified food and drink items, ingredients and quantities/portion sizes in a proposed meal in various contexts; i.e., understand from a semantic perspective their types, properties, and interrelationships in the context of a given user’s health condition and preferences. In this paper, we review a number of “food ontologies”, such as the Food Products Ontology/FOODpedia (by Kolchin and Zamula), Open Food Facts (by Gigandet et al.), FoodWiki (Ontology-driven Mobile Safe Food Consumption System by Celik), FOODS-Diabetes Edition (A Food-Oriented Ontology-Driven System by Snae Namahoot and Bruckner), and AGROVOC multilingual agricultural thesaurus (by the UN Food and Agriculture Organization—FAO). These food ontologies, with appropriate modifications (or as a basis, to be added to and further expanded) and together with other relevant non-food ontologies (e.g., about diet-sensitive disease conditions), can supplement the aforementioned lookup databases to enable progression from the mere automated identification of food and drinks in our meals to a more useful application whereby we can automatically reason with the identified food and drink items and their details (quantities and ingredients/bromatological composition) in order to better assist users in making the correct, healthy food and drink choices for their particular health condition, age, body weight/BMI (Body Mass Index), lifestyle and preferences, etc. View Full-Text
Keywords: food ontologies; Food Informatics; health; diabetes; diet; food scanning; Internet of Things; Semantic Web; linked data food ontologies; Food Informatics; health; diabetes; diet; food scanning; Internet of Things; Semantic Web; linked data
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Boulos, M.N.K.; Yassine, A.; Shirmohammadi, S.; Namahoot, C.S.; Brückner, M. Towards an “Internet of Food”: Food Ontologies for the Internet of Things. Future Internet 2015, 7, 372-392.

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