Research, Methodology & Project Structure

Problem Background

Many people attempt diets for weight loss, muscle gain, or general health, but struggle to maintain them. Western diet plans often include unfamiliar, expensive ingredients that do not align with Sri Lankan food culture. Combined with the availability of fast food and limited nutritional knowledge, this leads to poor long-term outcomes.

Problem Statement

Individuals in South Asian countries find it difficult to follow meal plans because existing plans are mismatched to their lifestyles or include ingredients that are expensive and difficult to find locally.

Proposed Solution

A mobile and web application that generates weekly meal prep plans using local ingredients, personal health data, and nutritional constraints. The app provides grocery lists, local substitutions, and an option to consult dietitians and gym instructors.

Scope

Competitor Overview

The team reviewed HealthifyMe, MyFitnessPal, and Noom. These platforms are strong in calorie tracking and general coaching but weak in local affordability and ingredient availability, especially for South Asian regions.

• No dynamic substitution for unavailable or costly ingredients.
• Limited focus on regional food cultures such as Sri Lankan cuisine.
• Minimal cost-aware diet optimization.

Algorithmic Foundations

Constraint Satisfaction Problems (CSP)

CSPs allow the app to represent diet planning as a set of constraints such as nutrient limits, user allergies, and budget. A solver can search for meal combinations that satisfy all these rules.

Linear Programming (LP)

LP is used to optimize diets by minimizing cost while meeting nutritional requirements. This approach is particularly suitable for low-budget scenarios where affordability is critical.

Evaluation Metrics (Conceptual)

• User retention and churn rate
• Plan adherence (how closely users follow their plans)
• Accuracy of food logging and substitutions
• Mobile App Rating Scale (MARS) criteria

Development Methodology

After reviewing models such as Waterfall, Incremental, and Spiral, the team selected an Agile approach, specifically Scrum. This decision reflects the need for flexibility, iterative feedback, and evolving requirements typical in student and research-oriented projects.

• Short sprints and frequent check-ins
• Regular feedback from supervisors and stakeholders
• Ability to adjust scope as the project matures

Design Methodology

Object-Oriented Analysis and Design (OOAD) was chosen to support modular architecture, easier maintenance, and clear representation of system behavior through UML diagrams such as use case, class, and sequence diagrams.

Project Management

The team adopted Agile-Scrum-style project management supported by tools:

• ClickUp for task management and sprint planning
• Instagantt for visualizing the Gantt chart
• Version control via GitHub (planned for implementation stage)

Risk & Mitigation (Sample Items)

This page is a visual summary of Chapters 1–3 and does not replace the full report. It is meant to give future users and stakeholders a quick overview of the research behind Grist.