Inspiration
The inspiration behind this project comes from the growing need for personalized and inclusive health solutions. With unhealthy eating habits being a widespread concern, especially among students with diverse dietary needs and lifestyles, we wanted to create a tool that could bridge the gap between awareness and action. By leveraging logic programming, we aim to empower individuals to make better dietary decisions and reduce the risk of diseases associated with poor nutrition.
What it does
The system assesses the eating habits of individuals by analyzing their diet, nutritional intake, and underlying medical conditions. It provides a risk assessment for diseases linked to poor nutrition and offers personalized food suggestions to mitigate these risks.
How we built it
We used S(CASP) to design a system that evaluates dietary risks.
- Created a database of foods, their nutritional values, and their relevance to specific medical conditions.
- Incorporated user profiles with calorie limits, food preferences, and health conditions.
- Developed logic rules to identify nutritional deficiencies and calculate risks for conditions such as anemia or scurvy.
- Designed a recommendation engine that suggests foods to address deficiencies and reduce health risks.
Challenges we ran into
- Implementing recursive logic in S(CASP) to process lists of risks and generate food suggestions.
- Debugging
Accomplishments that we're proud of
- Successfully built a functional logic system capable of providing personalized risk assessments.
- Developed a recommendation engine that aligns with individual dietary needs and health conditions.
What we learned
- Gained expertise in S(CASP) programming and handling recursive logic effectively.
- Enhanced problem-solving skills by tackling challenges in logical programming and system design.
What's next for NutriSense - Personalized Nutrition and Risk Assessment
- Expanding the database to include a wider range of foods, nutrients, and medical conditions.
Built With
- ciao
- s(casp)
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