BROCCOLI - Nutrition Instrument
1. the problem
Most fitness trackers deceive users with pseudo-mathematical certainty: claiming a chicken breast is "165.2 calories". In reality, biological variance, cooking evaporation, and human portion estimation carry a natural ±10% to ±15% standard error. False precision is a bug: when an app claims four decimal places on biology, it trains users to optimize noise over habits.
ROLE: On-device natural language text tokenization. Parses food items, quantities, and metric units on the client UI thread with zero cloud roundtrips.
2. what i built
Caloric and body composition tracking engineered as an honest physical instrument:
3. problems i had to crack
Click card to view root cause & code diffCalculating rotation physics and gesture dampening across the React Native bridge dropped frames on Snapdragon 400 test devices. Fix: ported the entire gesture pipeline onto the native UI thread using Reanimated 3 worklets and shared memory values.
Food names containing mixed units and metric measurements (e.g. 100g, 2.5oz) broke standard SQLite tokenizers. Fix: created a normalized fts5 prefix tokenizer with custom unicode folding.
Aggressive Android task killers terminated the app during food search over heavy lists. Fix: authored an aggressive virtualized windowing layer that strictly caps resident memory heap below 42MB, eliminating OEM background terminations.
Google Play App Signing generated an internal key fingerprint that conflicted with initial local release builds, blocking automated tracks. Fix: configured automated eas build credentials with pinned SHA-256 fingerprint verification in assetlinks.
SHIPPED PRODUCT. Available worldwide on Google Play ↗. Built with React Native & SQLite.
| PROJECT | BROCCOLI |
| DRAWN BY | BIDYA B. NANDA |
| STATUS | LIVE ON PLAY STORE ↗ |