Nutritional Value Calculator A Personal Digital Guide Towards Nutrition You Need

Nutritional value of food is of utmost importance in our daily life. It is important to consider that, not only that if our diet is lacking in essential ingredients/nutrients, but also to find if we are getting excess of any particular nutrient that may be harmful for our body. Our system will calcu

Project Title

Nutritional Value Calculator A Personal Digital Guide Towards Nutrition You Need

Project Area of Specialization

Artificial Intelligence

Project Summary

Nutritional value of food is of utmost importance in our daily life. It is important to consider that, not only that if our diet is lacking in essential ingredients/nutrients, but also to find if we are getting excess of any particular nutrient that may be harmful for our body. Our system will calculate nutritional value of a meal/platter by just using its picture. Our system mainly comprises of two major components: A personal assistant that will use only a picture of the item to estimate the nutritional value. The picture will be uploaded to the application which will then identify and predict every food item and its quantity. Using these values, the amount of nutrients and the total calories will be calculated. The user will be able to interact with the chatbot by asking for meal suggestions within a specified range of calories/nutritional value. The chatbot will return a list of meals fulfilling the stated requirements. Second component is of more larger scale, where the system can be deployed at restaurant etc, where a weight scale, a fixed camera along with deployable system (in Raspberry Pi) will be used.

Project Objectives

The project’s goal is to make healthy living affordable for  everyone by reducing the need for nutritionists and dieticians. This project will give more control to the users in distinguishing the healthy food items from the unhealthy ones which will minimize the number of food-related illnesses among the users. The individual objectives are:

1. To design and implement a framework to identify the food items in a platter/utensil.
2. To estimate the nutritional value of the food by identifying the contents and estimate their weights/quantities.
3. To develop a chatbot that can suggest meals within a specified range of calories/nutritional value.
4. To deploy a system in Android as well as in Raspberry Pi.

Project Implementation Method

Architectural Design

The architectural design of NVC is Model-View-Controller Architecture. Model-View-Controller divides the system into the following modules to achieve the complete functionality.

1) User interaction system-View

The user interacts with the user interface system to upload photo or for login/sign-up to use the whole application.

For Deployed System (Rasberry Pi), the system will identify an object being placed in front of camera and start processing.

2) Calorie Calculator and Recommender-Controller

The user’s meal image will be preprocessed and processed inside Controller to get the number of calories of that meal

The user will be entertained with several cuisines/meals corresponding to the required number of calories

3) Database- Model

It stores the data of user and images of meals.

4) Chat Module

User interacts with the Chatbot and it will recommend customized meal plans.

Some of the diagrams to illustration the working are shown below.

Fig.1 shows the expected output of nutritional values.

https://drive.google.com/file/d/1h6J_jQrXPgOBkSLrZLQSpLY7U-5RFzOc/view?usp=sharing

Fig.2 Component Diagram for Mobile App

https://drive.google.com/file/d/141_pCaT4EJT5bPkQBgNr_yeG-DiaQvJV/view?usp=sharing

Benefits of the Project

1. At Individual Level:

Personal nutritionist/dietician that can estimate the food nutritional value based on its contents, just by taking a picture. Some of the related systems are available for English food, however, there is no such app that can work with traditional /desi food 

A personal chatbot will interact with user and suggest items/food as per needs/season of the year.

2. Deployed at production level

A prototype system will be created that can be deployed on restaurants/food markets to estimate the nutrients.

Technical Details of Final Deliverable

1. A dataset of images of (traditional/Pakistani/Desi) food to augment will already available online datasets which mostly work with English food.

2. A Machine Learning model is to be trained on the newly created images of food to detect their ingredients. Model will be created in TensorFlow-Lite so that it can be easily deployed on Mobile as well as Raspberry Pi.

3. A mobile app that can take images of food and return the ingredients/nutritional value. (Flutter)

4. A system deployed on Raspberry PI along with a camera app that can take images in real time and quicly process the images to provide nutrients.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Food , Health

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com