Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67632
Volume:
10 |
10 |
Oct 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer science
Chikitsak Samuha’s Sir Sitaram and Lady Shantabai Patkar College of Arts and Science and V.P. Varde College of Commerce and Economics
SMARTFIT – Fitness & Diet Planner is a web application based on rules that provides personalized recommendations on fitness and diet taking into account some details about the user and person daily activities. The application uses basic details provided by the user, including age, gender, height, weight, daily activity, fitness goal, and food preferences. These details are used to work out the user’s BMI and BMR and to estimate the daily calorie requirement. The system then uses its rule base to produce a suggestion for an initial diet and exercise plan in accordance with the chosen fitness goal. A notable feature of the system is that it continuously adjusts the daily plan in light of the user's activities. For instance, suppose the system suggests that the user have dal with two rotis for lunch, but instead the user eats pizza; the system will take this into consideration and alter the diet plan for the remainder of the day in accordance with its rules. The same applies to the exercise component: if the user fails to carry out the exercises that the system has arranged for him or only does them in part, changes will be made to the exercise plan. Hence, a rule-based system can offer a solution that is not static and does not adhere to a general plan, but instead changes dynamically in response to the user's current activities. The system proposed has among its features a food database, six kinds of exercises, the ability to track both planned and actual food and exercise intake, a feature that allows the user to compare planned and actual activity levels, the capability to modify the plan in light of new information and rules, progress monitoring and dashboards. Moreover, the system has a YouTube finder which displays relevant videos to assist the user with exercises and recipes. SMARTFIT is a system which does not make use of technologies such as Artificial Intelligence or Machine Learning, instead it operates on a series of rules and calculations in order to give the user the appropriate information immediately. The paper demonstrates how such a system can be used to develop a web application for fitness and diet planning
KEYWORDS
SMARTFIT – the Fitness & Diet Planner – helps users plan and manage their daily fitness and diet based on a set of simple rules. The system can also adjust the plan according to the user’s daily activities and actual behaviour by using information specific to the user for calculating their BMI, BMR, and calorie requirements and by applying a set of predefined rules when producing and dynamically adjusting the daily plans. Its ability to compare planned versus actual activities and modify recommendations accordingly distinguishes it from static solutions, all while maintaining transparency and ease of understanding. SMARTFIT thus offers a robust foundation for further innovation in web-based health management applications.
[1] M. D. Mifflin, S. T. St Jeor, L. A. Hill, B. J. Scott, S. A. Daugherty, and Y. O. Koh, “A new predictive equation for resting energy expenditure in healthy individuals,” The American Journal of Clinical Nutrition, vol. 51, no. 2, pp. 241–247, 1990. DOI: 10.1093/ajcn/51.2.241. [2] S. Abhari, R. Safdari, L. Azadbakht, K. B. Lankarani, S. R. Niakan Kalhori, B. Honarvar, et al., “A Systematic Review of Nutrition Recommendation Systems: With Focus on Technical Aspects,” Journal of Biomedical Physics & Engineering, vol. 9, no. 6, pp. 591–602, 2019. DOI: 10.31661/jbpe.v0i0.1248. [3] World Health Organization, “Healthy Diet,” World Health Organization, 2026. [4] World Health Organization, “Nutrition for a Healthy Life – WHO Recommendations,” World Health Organization. [5] World Health Organization, “WHO Guidelines on Physical Activity and Sedentary Behaviour,” World Health Organization, 2020/2021. [6] World Health Organization and Food and Agriculture Organization of the United Nations, “What are Healthy Diets? Joint Statement,” World Health Organization, 2024. [7] U.S. Department of Agriculture, Agricultural Research Service, “FoodData Central,” USDA. [8] Google for Developers, “YouTube Data API Documentation,” Google Developers. [9] Google for Developers, “YouTube Data API Overview,” Google Developers. [10] Y. Zhao, X. Xue, N. Chen, Y. Qi, J. Gong, W. Hu, Y. Li, L. Shi, and J. Yu, “Mapping the Landscape of Nutrition Recommendation Systems: Evidence from Peer-Reviewed Research, Apps, and Patents,” Nutrition Reviews, 2026. DOI: 10.1093/nutrit/nuaf265.
Publication Date
10/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
9
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...