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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM54068
Volume:
9 |
11 |
Nov 2025
Pages:
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.
Maintaining a healthy lifestyle has become increasingly challenging due to modern-day schedules, limited awareness of nutrition, and the absence of structured fitness planning tools. Although many applications exist for diet tracking or workout routines, they often function as separate systems, requiring users to switch between multiple platforms. This fragmentation results in reduced user engagement, inconsistent health routines, and difficulty in achieving long-term fitness goals. The proposed Integrated Diet and Workout Management System addresses these issues by offering a unified, web-based platform that combines personalized meal planning, customized workout routines, progress tracking, and automated shopping list generation. Developed using HTML, CSS, and JavaScript, the system provides a responsive and user-friendly interface accessible across devices. Users can choose dietary preferences such as vegetarian or non-vegetarian options, set fitness goals, log workouts, and monitor their improvement through visual charts and summaries. A structured development methodology was followed, including requirement analysis, system design, modular implementation, and extensive testing. The system successfully integrates diet and workout management in a seamless manner, making it easier for users to follow consistent routines. Testing results indicate high usability, accuracy of generated plans, and positive user feedback. Overall, this project demonstrates the feasibility and effectiveness of a combined diet and fitness management solution. The system reduces dependency on multiple applications, enhances user motivation, and provides a holistic approach to health management. Future enhancements include backend integration, AI-driven recommendations, and wearable device connectivity to further improve personalization and performance.
KEYWORDS
Publication Date
11/18/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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