Building a Personalized Nutrition Recommendation Engine for Children and Families
This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.
You can find our upcoming AI Innovation Challenges at https://omdena.com/projects.
The problem
Due to their high levels of dietary fiber, vitamins, minerals, particularly electrolytes, and more recently, phytochemicals, particularly antioxidants, fruits, and vegetables are taken into account while providing nutritional advice. Insufficient consumption of fruits and vegetables has been linked in several studies to chronic illnesses such as cardiovascular disease, high blood pressure, hypercholesterolemia, osteoporosis, various malignancies, chronic obstructive pulmonary disorders, respiratory issues, and mental health. Despite an increased emphasis on the health advantages of fruits and vegetables, individuals still consume less than is advised in light of the fact that worldwide, nutritionally associated health issues have dramatically increased.
There is a global need to change eating behavior. This Omdena-Venner project aims to solve children’s low usage of fruit and vegetables, leading to obesity, type 2 diabetes risk, and other health problems. This AI-based solution will better lives as it addresses one of the most under-consumed dietary groups: vegetables and fruits, in a unique and innovative way.
The project goals
Venner currently has a partial dataset required for solution development.
Project Scope:
- Use AI to catalog data of the photographed fruit and vegetables
- Personalize the data relative to the user profile and their goals, and compare this data with other users’ ones
- The model will provide suggestions to users based on this data and uncover patterns and insights into the problem
- The model will also be able to read and extract the latest health and nutrition recommendations, know nutrients that may be lacking in the diet, and provide personal inspiration based on this data
- The personalized suggestions will incorporate dietary recommendations, local produce, and seasonality info, combined into meaningful and personal recommendations for the whole family
**More details will be shared once the project is joined.
Why join? The uniqueness of Omdena Top Talent Projects
Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.
Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.
If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.
Find more information on how an Omdena Top Talent Program works
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Eligibility to join an Omdena Top Talent project
Finished at least one AI Innovation Challenge
Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus
Skill requirements
Good English
Machine Learning Engineer
Experience working with Smartphone Sensor Data is a plus.
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