GlucoTrack
GlucoTrack is a mobile-first app for people with Type 1 Diabetes. It helps users monitor glucose trends, log meals, estimate insulin units, and make smart choices at restaurants. The app uses a user-centered design and pairs accessible health features with a lightweight AI agent (“NutriTrackr”) and secure cloud services.
Features
Glucose monitoring
Track blood sugar, visualize trends, and surface simple insights.Smart food logging
Snap a photo or enter food details. Get estimated carbs and insulin units with AI support.Restaurant recommendations
Search by ZIP code. See low-carb, lower-sugar options and quick swaps.Predictive insights
Spot recurring patterns, forecast likely highs or lows, and receive helpful reminders.Accessibility first
Friendly copy, manual input paths, offline-tolerant flows, and support for diverse cuisines.Privacy and security
Client-side protections, secure auth, encrypted storage where supported, and user control of data.Cloud integration
Cloud hosting, database, real-time APIs, and notifications for scale and reliability.
Tech Stack
Frontend: React, Tailwind CSS, shadcn/ui
Backend: Node.js + Express (HTTP API)
Database: Firebase Firestore (or Postgres via a managed provider)
Machine Learning: TensorFlow.js and/or hosted models
Cloud Services: Firebase, AWS, or GCP for hosting, auth, storage, and notifications
APIs: Nutrition and restaurant data sources for menu items and carb estimates
AI Agent: ai.py (Gemini-based assistant with USDA + web search tools)
Key files recap
ai/ai.py— Gemini-powered NutriTrackr agent. Pulls nutrition data from USDA FoodData Central, performs retrieval on past context, and answers in kid-friendly language.ai/procedures.json— Curated procedures used to guide the agent’s step-by-step behavior.frontend/src/components/RestaurantSearch.tsx— ZIP search and selection callback for restaurant suggestions.backend/routes/aiChat.js— Bridges frontend chat input to the NutriTrackr agent.backend/routes/restaurants.js— ZIP-based restaurant discovery and menu lookups.
Requirements
langchain-google-genai langchain langgraph chromadb python-dotenv requests
Tracks Applied
Product Design Cybersecurity Predict the Unpredictable Civics and Accessibility Healthcare Optimization
Awards Applied
Best Use of the Cloud Best Beginner
Team: BuckHacks
Krista Bair — kristalbair@gmail.com
Anika Talyan — anikatalyan@gmail.com
Joselyn Vasquez — joselynlilyanna@gmail.com
Melvin Vasquez — melvin.60834@gmail.com

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