Sniffle

Sniffle is a mobile allergy companion that helps users predict and track symptoms in real time, combining environmental data with personal health patterns to provide actionable risk analysis.

Motivation

Allergy sufferers often don't know what's triggering their symptoms or when conditions will be worst. Existing tools show generic pollen counts but don't personalize to individual sensitivity patterns. I wanted to build something that learns from you.

How it works

• Users log daily symptoms through a quick, low-friction interface
• The app pulls real-time environmental data: pollen counts, air quality, humidity, weather
• A machine learning model correlates personal symptom history with environmental factors
• Predictive alerts warn users when conditions match their worst symptom days

Technical details

Built in React Native for cross-platform mobile support. Firebase handles auth, real-time database, and cloud functions. The ML pipeline runs serverside, training personalized models per user as enough symptom data accumulates. Environmental data is sourced from public APIs and cached for low-latency lookups.