ISSN2320-2882
Impact Factor9.17
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ESTD2013
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Paper Title
Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System
Authors
Niraj Doiphode , Anushree Kekapure , Jidnyasha Khapne , Rutuja Lambat , Mansi Nanwani
Keywords
Ayurveda , Food Recommendation, Random forest, Prakriti, Hybrid Recommendation System, Dosha Balancing, AI in Healthcare
Abstract
In Ayurveda, personalized nutrition is based on an individual's constitution (Prakriti), seasonal variations (Ritu), and digestive strength (Agni), which play a crucial role in maintaining health and preventing diseases. However, existing Artificial Intelligence (AI)-based Ayurvedic systems mainly focus on diagnostic analysis and lack effective implementation of constitution-specific dietary recommendations. This research proposes VedAahar, a machine learning-based Ayurvedic meal recommendation system that integrates Random Forest multi-class classification with rule-based filtering derived from Ahara Vidhi principles. The system utilizes structured datasets, including vegetarian, non-vegetarian, and fasting meal categories, and considers features such as prakriti, ritu, health goals, and meal slots to generate personalized recommendations. Additionally, Top-K probabilistic ranking and history-based de-duplication techniques are applied to ensure diverse and relevant meal suggestions. Experimental results show that the model achieves an accuracy of 69.14%, demonstrating its effectiveness in providing constitution-aware dietary guidance. Overall, the proposed system bridges traditional Ayurvedic knowledge with modern AI techniques, contributing to the development of intelligent and personalized preventive healthcare solutions.
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IJCRT — journal style
"Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.14, Issue 4, page no.b114-b122, April 2026, Available :https://ijcrt.org/papers/IJCRT2604140.pdf
APA — 7th edition
Doiphode, N., Kekapure, A., Khapne, J., Lambat, R., & Nanwani, M. (2026). Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System. International Journal of Creative Research Thoughts, 14(4), b114-b122. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140
MLA — 9th edition
Doiphode, Niraj, et al. "Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System." International Journal of Creative Research Thoughts, vol. 14, no. 4, 2026, pp. b114-b122, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140.
Chicago — 17th, bibliography
Doiphode, Niraj, et al. "Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System." International Journal of Creative Research Thoughts 14, no. 4 (2026): b114-b122. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140.
Harvard — author–date
Doiphode, N. et al. (2026) 'Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System', International Journal of Creative Research Thoughts, 14(4), pp. b114-b122. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140
IEEE — numbered reference
N. Doiphode, A. Kekapure, J. Khapne, R. Lambat and M. Nanwani, "Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System," IJCRT, vol. 14, no. 4, pp. b114-b122, Apr. 2026.
Vancouver — biomedical
Doiphode N, Kekapure A, Khapne J, Lambat R, Nanwani M. Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System. IJCRT. 2026 Apr;14(4):b114-b122.
AMA — 11th edition
Doiphode N, Kekapure A, Khapne J, Lambat R, Nanwani M. Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System. IJCRT. 2026;14(4):b114-b122. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2604140,
author = {Niraj Doiphode and Anushree Kekapure and Jidnyasha Khapne and Rutuja Lambat and Mansi Nanwani},
title = {Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System},
journal = {International Journal of Creative Research Thoughts},
volume = {14},
number = {4},
pages = {b114-b122},
year = {2026},
month = {April},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Doiphode, Niraj
AU - Kekapure, Anushree
AU - Khapne, Jidnyasha
AU - Lambat, Rutuja
AU - Nanwani, Mansi
TI - Vedaahar: An AI-Based Personalized Ayurvedic Food Recommendation System
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 14
IS - 4
PY - 2026
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140
SP - b114-b122
ER -
Issue
Volume 14 Issue 4,
April-2026
Pages : b114-b122
Article Information
- Pages
- b114-b122
- Published
- April 2026
- Registration ID
- IJCRT_304851
- Published Paper ID
- IJCRT2604140
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Amravati, India, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 194
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2604140
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2604140.pdf
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