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🌍 BreathSafe

Breathing Smarter, Living Better — Powered by NASA TEMPO Data

🔗 Live Demo


🫧 Introduction

Every breath we take tells a story about our planet.
For millions of people around the world, that story has become one of silent danger — the air they breathe is slowly harming their health.

According to the World Health Organization (WHO), nearly 99% of the global population is exposed to air that exceeds safe pollution levels.
Yet, despite the urgency, real-time and accessible air quality information is still lacking for most communities.

That’s where BreathSafe comes in. 🌱


💡 Why We Make the Difference

BreathSafe, developed by Team TEMPO 11, transforms NASA’s atmospheric science into an intelligent, user-centered health protection system.

By integrating real-time data from the NASA TEMPO (Tropospheric Emissions: Monitoring of Pollution) mission with ground-based sensors, public health datasets, and AI analytics, we help people understand, anticipate, and act upon air quality conditions that affect their lives.


🖥️ Main Features

🌎 Home Screen — Where Data Meets Action

A dynamic interface combining real-time air quality data with personalized insights.
Home Screen

🫧 Air Quality View

Visualizes pollutants such as PM2.5, NO₂, and O₃ through an intuitive map, combining NASA satellite and local ground sensor data.
Air Quality View

📍 Personalized Location

Uses real-time geolocation to display precise air quality information for each user’s exact position.
Personalized Location

🔔 Subscription for Alerts

Sends instant notifications when pollution levels change — allowing users to plan outdoor activities safely.
Alerts

🩺 Recommendations Based on Profile

Delivers personalized health guidance for groups such as children, elderly, pregnant users, and those with respiratory conditions.
Recommendations

💡 Tips

Provides daily eco-health suggestions and protective habits based on real-time air quality.
Tips


🛰️ Technical Approach

1. Data Sources & APIs

  • NASA TEMPO: high-resolution air pollution data (O₃, NO₂, CO, CH₂O, PM, Aerosol Index)
  • Meteomatics API: real-time weather parameters (temperature, humidity, wind speed, radiation, precipitation)
  • IPCC CIESIN SRES Dataset: historical and projected emissions data

2. Data Processing & Integration

  • Spatial harmonization with WGS84 / EPSG:4326
  • Bilinear interpolation & nearest neighbor sampling
  • Data normalization with quality flag validation
  • Missing data recovery using exponential decay and median neighborhood fill

3. Analytical Model

  • Mamdani-type Fuzzy Logic System with 100+ expert rules
  • Fuzzy sets: Low → Moderate → High → Extreme
  • Triangular & Gaussian membership functions
  • Centroid defuzzification producing final air-quality class (Good → Hazardous)

4. AI & Automation Layer

  • Qwen2.5-1.5B Transformer (Small Language Model)
  • Generates bilingual (EN/PT) explanations and recommendations
  • Low-latency reasoning (<800 ms) for real-time insights
  • Automates environmental reports and summary generation

5. System Architecture

  • Progressive Web App (PWA) collecting geolocation data
  • Serverless backend with autoscaling & sub-second response
  • REST API endpoints for inference and explainability
  • Secure infrastructure using key vaults, containers & OpenTelemetry

6. Calibration & Validation

  • Cross-validation using AERONET and urban monitoring stations
  • Metrics: F1 (unhealthy+), macro accuracy, weighted kappa, rank correlation
  • Bayesian optimization to fine-tune fuzzy thresholds

⚡ Capabilities

✅ Integration of NASA satellite, ground, and weather data
Near real-time monitoring and forecasting
Validated accuracy across multiple data sources
Historical trends and seasonal visualizations
Health-based alerts and proactive recommendations
User-tailored insights by health and location profile


🔭 Future Features

🚀 Digital Phenotypes — analyze human and community responses to air conditions
🤖 Edge AI — local, privacy-preserving, real-time analysis
🎯 Hyper-Personalization — adapt to exposure, habits, and local environments
🧩 Causal AI Models — move from correlation to cause-and-effect relationships
💬 Explainable AI (XAI) — transparency in why alerts and predictions are made
🌐 System Integrations — future partnerships with other mobile and IoT systems


🧠 Use of Artificial Intelligence

We applied AI throughout the project lifecycle:

Application Tools
Code generation & system logic ChatGPT, Manus, Claude, Gemini
Text & data interpretation Qwen2.5
Image & video generation Manus, Gemini, Google Labs Flow (VEO 3 Quality)
Personalized communications OLLAMA / Qwen2.5

🌎 Data & Partners

Source Type Role
NASA TEMPO / EARTHDATA / AIR QUALITY Satellite Atmospheric pollutants
Meteomatics API Weather data
IPCC CIESIN SRES Dataset Emission projections
WHO / EPA / AirNow / NEJM / EHP / Springer Validation Health and environmental research
GitHub Platform Repository & version control

👩‍🚀 NASA Space Apps Challenge — Team TEMPO 11

  • Project: BreathSafe
  • Theme: Data for Health & Environment
  • Mission: Empower communities to understand and act upon air quality conditions through real-time NASA data and AI-driven insights.

📫 Contact

Team TEMPO 11 — BreathSafe Project
🌐 www.tempo11.earth
✉️ [email protected]


“We don’t just monitor the air. We make it understandable, actionable, and personal.” 🌬️


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NASA Space Apps Challenge - Global Nominee

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