DEVELOPMENT OF A DISTRIBUTED INFORMATION SYSTEM FOR ANALYZING EATING HABITS AND FORMING PERSONAL NUTRITION RECOMMENDATIONS BASED ON AI TECHNOLOGY

A. Nazarova; Ekaterina I. Skvorcova; O. Avilova

doi:doi:10.58168/MIST2026_986-992

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DEVELOPMENT OF A DISTRIBUTED INFORMATION SYSTEM FOR ANALYZING EATING HABITS AND FORMING PERSONAL NUTRITION RECOMMENDATIONS BASED ON AI TECHNOLOGY

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DEVELOPMENT OF A DISTRIBUTED INFORMATION SYSTEM FOR ANALYZING EATING HABITS AND FORMING PERSONAL NUTRITION RECOMMENDATIONS BASED ON AI TECHNOLOGY

Section: SECTION 2. COMPUTER-AIDED DESIGN SYSTEMS

Proceedings: MODELING INFORMATION SYSTEMS AND TECHNOLOGIES – 2026 : PROCEEDINGS OF THE INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE DEDICATED TO THE 5TH ANNIVERSARY OF THE FACULTY OF COMPUTER SCIENCE AND TECHNOLOGY, VORONEZH, MARTH 30, 2026

UDC 519.713.1

A. Nazarova ¹

Ekaterina I. Skvorcova ²

O. Avilova ³

Author and publication information

Authors:

1. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

2. Voronezh State University of Forestry and Technologies named after G.F. Morozov

3. Voronezh State University of Forestry and Technologies named after G.F. Morozov
Russian Federation

Type:

Сonference article

DOI:

https://doi.org/10.58168/MIST2026_986-992

Pages:

from 986 to 992

Published:

30.06.2026

Subject area:

UDC 519.713.1

Language:

Russian

Keywords:

eating habit analysis, tracker, AI, web application, competitors, market, characteristics

Abstract and keywords

Abstract:
Development of a distributed information system for analyzing eating habits and generating personalized nutrition recommendations, based on AI technology. A market analysis is provided, and its competitive advantages are argued.

Keywords:
eating habit analysis, tracker, AI, web application, competitors, market, characteristics

References

1. FatSecret. – URL: https://mobile.fatsecret.com (data obrascheniya 04.02.2026).

2. Lifesum. – URL: https://lifesum.com/ru (data obrascheniya 04.02.2026).

3. CalZen AI. – URL: https://calzen.ai/ru (data obrascheniya 04.02.2026).

4. Borzunov, S. V. Yazyki programmirovaniya. Python: reshenie slozhnyh zadach : uchebnoe posobie dlya vuzov / S. V. Borzunov, S. D. Kurgalin. – 2-e izd., ster. – Sankt-Peterburg : Lan', 2026. – 192 s. – ISBN 978-5-507-51226-3. – Tekst : elektronnyy // Lan' : elektronno-bibliotechnaya sistema. – URL: https://e.lanbook.com/book/508367 (data obrascheniya: 04.02.2026).

5. Artemov, M. A. Mashinnoe obuchenie : uchebno-metodicheskoe posobie / M. A. Artemov, S. V. Zolotarev, E. S. Baranovskiy. – Voronezh : VGU, 2021. – 22 s. – Tekst : elektronnyy // Lan' : elektronno-bibliotechnaya sistema. – URL: https://e.lanbook.com/book/455024 (data obrascheniya: 04.02.2026).

6. Achkasov, D. A. Izuchenie i modelirovanie evristicheskih algoritmov optimizacii / D. A. Achkasov, K. V. Zol'nikov, N. N. Litvinov // Modelirovanie sistem i processov. – 2025. – T. 18, № 1. – S. 17-28. – DOI:https://doi.org/10.12737/2219-0767-2025-17-28.

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