search

nathan-wick / nutrition-ai

A mobile app that uses machine learning to provide personalized nutrition recommendations based on a user's dietary preferences, health goals, and exercise habits.
1 stars 1 forks source link

readme

NutriMind

NutriMind

Problem

A survey conducted by the Centers for Disease Control and Prevention found that at least 23% of adults in the United States were following a one-size-fits-all diet approach (CDC, 2018). The one-size-fits-all diet approach assumes that all individuals have the same nutritional needs and that a single diet can be universally applied to all people. A study published in the journal Nutrients found that personalized nutrition advice based on individual factors, including age, sex, body size, activity level, genetics, and underlying health conditions was more effective in promoting weight loss, muscle gain, and improving dietary quality than a one-size-fits-all approach (D'Alessandro et al., 2020).

A survey conducted by the International Food Information Council Foundation found that 58% of respondents were interested in personalized nutrition advice based on their individual needs and preferences (IFIC, 2020). This suggests that there is a growing demand for more personalized nutrition guidance.

Solution

NutriMind, a mobile software application that uses machine learning to provide personalized nutrition recommendations based on a user's dietary preferences, health goals, and exercise habits. It aims to solve the one-size-fits-all diet approach problem by providing users with tailored nutrition advice.

NutriMind enables users to:

Rena Patel

Socials: LinkedIn, GitHub

Modupeoluwa Daniel

Socials: LinkedIn, GitHub

Tara Poudyel

Socials: LinkedIn, GitHub

Emilee Schweitzer

Socials: LinkedIn, GitHub

Developer Documentation

Work Breakdown Structure

  1. Ideation and Planning (1 week)

    • Define project scope and goals
    • Outline the app's key features and functionalities
    • Develop a high-level project plan, including a timeline

  2. Design and Prototype (4 weeks)

    • Create wireframes and prototypes of the app's user interface
    • Define the app's visual design and brand identity
    • Develop an information architecture that supports the app's functionalities
    • Finalize the app's user flow and navigation

  3. Development (12 weeks)

    • Implement the front-end and back-end components of the app
    • Integrate machine learning algorithms to provide personalized nutrition recommendations
    • Integrate with APIs for accessing dietary information and health data
    • Implement security and data protection measures
    • Test and debug the app to ensure optimal performance and usability

  4. Testing and Launch (4 weeks)

    • Conduct user testing to gather feedback and identify any remaining bugs or issues
    • Make any necessary updates and improvements based on feedback
    • Launch the app on the app store

      Getting Started

      How To Start Working On An Issue

  5. Update the Project Board

    • Open Project Board
    • Find the issue you wish to work on from the Ready column
    • Assign yourself to the issue
    • Drag the issue from the Ready column to the In progress column

  6. Clone the Repository (if you haven't already)

    • Open Visual Studio Code
    • Open a terminal at the folder you'd like to store the project in
    • Type the command git clone https://github.com/nathan-wick/nutrition-ai.git
    • Press Enter to run the command

  7. Create a New Branch

    • Open Visual Studio Code
    • Open a terminal at the repository's root
    • Type the command git checkout -b branchName dev
    • Replace branchName with the issue number (For example, a branch for issue #42 would be named 42)
    • Press Enter to run the command

      How To Finish Working On An Issue

  8. Commit and push your changes

    • Open Visual Studio Code
    • Open a terminal at the repository's root
    • Type the command git commit -m "description"
    • Replace description with a very short description of the changes you have made (For example, if you updated the README, a good description would be Update README)
    • Press Enter to run the command
    • Type the command git push
    • Press Enter to run the command

  9. Create a pull request

    • Open Pull Requests
    • Press New pull request
    • Compare the issue's branch to the dev branch
    • Verify the changes shown are correct and solve any merge conflicts
    • Write a description that contains Closes #issueNumber where issueNumber is replaced with the issue's number
    • Request review from at least one other teammate
    • Assign yourself to the pull request
    • Submit the pull request

  10. Update the Project Board