Automated Image Recognition System for Determining Energy Composition of Meals by AI-Powered Detection and Identification of Food Items – A Study Utilizing Flavoria Flex

dc.contributor.authorBhetuwal, Shyam
dc.contributor.authorKoivunen, Lauri
dc.contributor.authorKoskimäki, Sanna
dc.contributor.authorKhalil, Rehan
dc.contributor.authorLähde, Hanna
dc.contributor.authorHouttu, Veera
dc.contributor.authorLaitinen, Kirsi
dc.contributor.authorMäkilä, Tuomas
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=ohjelmistotekniikka|en=Software Engineering|
dc.contributor.organizationfi=ravitsemus- ja ruokatutkimuskeskus|en=Nutrition and Food Research Center (NuFo)|
dc.contributor.organization-code1.2.246.10.2458963.20.12007811941
dc.contributor.organization-code1.2.246.10.2458963.20.71310837563
dc.contributor.organization-code1.2.246.10.2458963.20.77952289591
dc.converis.publication-id506005026
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/506005026
dc.date.accessioned2026-01-22T10:31:23Z
dc.date.available2026-01-22T10:31:23Z
dc.description.abstract<p>Nutrition is a modifiable lifestyle factor that has a fundamental role in human development and health. Recently, there has been growing interest in food recognition and nutritional analysis, driven by the strengths of machine vision based models to estimate portion weight, volume, and nutrition of food dishes. However, research has shown that relying solely on image recognition techniques may not provide accurate weight and nutritional information. The latest AI-based object detection algorithms have also enhanced the accuracy of food recognition and nutritional estimation. This study utilizes an AIoT system as Flavoria Flex to integrate popular AI based algorithms for food recognition, weight estimation, and nutritional analysis to compare their performance against ground truth data collected from the Flavoria restaurant’s lunch line. The AIoT platform helps in collecting and validating this data by combining AIpowered food recognition with scaled weight and menu-based information.<br></p>
dc.embargo.lift2027-12-16
dc.identifier.eisbn979-8-3315-6879-5
dc.identifier.isbn979-8-3315-6880-1
dc.identifier.olddbid214193
dc.identifier.oldhandle10024/197211
dc.identifier.urihttps://www.utupub.fi/handle/11111/29220
dc.identifier.urlhttps://ieeexplore.ieee.org/document/11275545
dc.identifier.urnURN:NBN:fi-fe202601227540
dc.language.isoen
dc.okm.affiliatedauthorBhetuwal, Shyam Raja
dc.okm.affiliatedauthorKoivunen, Lauri
dc.okm.affiliatedauthorKoskimäki, Sanna
dc.okm.affiliatedauthorKhalil, Rehan
dc.okm.affiliatedauthorLähde, Hanna
dc.okm.affiliatedauthorHouttu, Veera
dc.okm.affiliatedauthorLaitinen, Kirsi
dc.okm.affiliatedauthorMäkilä, Tuomas
dc.okm.discipline113 Computer and information sciencesen_GB
dc.okm.discipline3141 Health care scienceen_GB
dc.okm.discipline113 Tietojenkäsittely ja informaatiotieteetfi_FI
dc.okm.discipline3141 Terveystiedefi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA4 Conference Article
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.conferenceIEEE Global Conference on Artificial Intelligence and Internet of Things
dc.relation.doi10.1109/GCAIoT68269.2025.11275545
dc.source.identifierhttps://www.utupub.fi/handle/10024/197211
dc.titleAutomated Image Recognition System for Determining Energy Composition of Meals by AI-Powered Detection and Identification of Food Items – A Study Utilizing Flavoria Flex
dc.title.book2025 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)
dc.year.issued2025

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