Vital-AI
Your AI Health & Fitness Guardian: Predict. Prevent. Thrive
Created on 5th April 2025
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Vital-AI
Your AI Health & Fitness Guardian: Predict. Prevent. Thrive
The problem Vital-AI solves
Vital-AI
By giving users direct access to AI-powered health insights, VitalAI bridges the crucial gap between reactive healthcare, fitness, and true prevention.
Useful Applications:
- Recognise health issues early on before they worsen
- Receive individualised training programs that change based on your equipment and goals
- Keep tabs on culturally relevant nutrition, particularly with regard to Indian food
- Track health indicators over time to identify any alarming patterns
- Get preventive advice from AI based on your data on which ML models are trained(RF model-95% accuracy)
Breaking the Red Tape(or Barriers):
- Cost: State-of-the-art health analytics without costly medical testing
- Access: Medical tracking and analysis available anywhere to anyone
- Knowledge: Complex health data translated into simple, actionable advice
- Cultural: Consists of aspects unique to a given culture that most platforms overlook
- Integration: Brings together health monitoring, nutrition, and exercise in one location
Vital-AI democratizes preventive healthcare by making personalized health insights accessible to everyone, not just those with access to specialists. It transforms scattered health data into a comprehensive picture of your wellbeing, helping you take control of your health journey before problems develop rather than treating them after.
Challenges we ran into
Development Challenges & Solutions
Creating VitalAI's integrated platform connecting workout tracking, calorie monitoring, and predictive analysis required overcoming key technical hurdles.
Overcoming Technical Difficulties
1. Hydration Mismatches in Next.js
Serious hydration errors were caused by rich user interface animations.
Remedy: Static versions are delivered during SSR by a custom debugging system with conditional rendering patterns.
2. Stability of AI Integration
Recipe recommendations were occasionally broken by the Gemini API's unparseable responses.
Solution: When identifying API failures, the fallback mechanism switches to mock data.
3. Browser Extension Interference Our health visualisations were broken by extensions that injected DOM attributes.
A defence system based on MutationObserver that eliminates attributes in real time is the solution.
4. Database Schema Evolution Without affecting current user data, health metrics requirements changed.
A table verification system that handles missing tables while triggering admin migrations is the solution.
5. Performance With Complex Animations On mobile devices, 3D visualisations led to performance problems.
Conditionally rendering simplified versions according to device capabilities is the solution.
Integration Achievements
Successfully integrated multiple health monitoring dimensions:
- Workout Sessions: Personalized routines adapting to progress - Calorie Tracking: Culture-specific food database with AI identification
- Predictive Analysis: Early warning system for potential health concerns
- Unified Dashboard: All metrics in one intuitive interface
Premium Features at No Cost
We've made typically paid features available completely free:
- Advanced Analytics: Comprehensive health trend analysis - AI-Powered Insights: Personalized recommendations
- Expert Meal Planning: Customised nutrition guidance
Tracks Applied (3)
Gemini API
Major League Hacking
Midnight
Major League Hacking
Track: GitHub
GitHub
Technologies used