Open-source, affordable, accurate air quality monitoring for India
Vaayu (वायु) — Sanskrit for wind/air
Air pollution is India's largest environmental health threat, reducing average life expectancy by over 5 years nationally and up to 10 years in cities like Delhi.
Yet there's a fundamental gap in how we measure and communicate air quality.
When you check the AQI on your phone or a weather app, you're seeing a reading from a government CPCB (Central Pollution Control Board) monitoring station. These stations are sparse — a city like Bangalore with 13 million people has only a handful of monitors spread across the metropolitan area.
The problem: Air quality isn't uniform across a city. It varies dramatically within short distances:
| Location | Typical AQI Difference |
|---|---|
| Near construction site vs. 500m away | 50-100+ points |
| Busy intersection vs. residential lane | 30-60 points |
| Ground floor vs. 10th floor | 20-40 points |
| Morning rush hour vs. 2 AM | 50-150 points |
Consider a mother living in Koramangala, Bangalore. She checks the AQI on her phone before taking her child to the park. The app shows AQI 85 (Moderate) ; seems acceptable for outdoor play.
But that reading comes from the CPCB monitoring station in BTM Layout, approximately 4 kilometers away, positioned near a major road for traffic pollution monitoring.
The actual AQI at her neighborhood park which is adjacent to an ongoing construction project could be AQI 160 (Unhealthy). Her child spends two hours breathing air that's nearly twice as polluted as she believed.
She has no way to know. The infrastructure to tell her doesn't exist.
This isn't a hypothetical edge case. It's the daily reality for hundreds of millions of Indians making health decisions based on air quality data that doesn't represent their actual environment.
Project Vaayu is an open-source hardware project to create an affordable, accurate, portable air quality monitor that enables true hyperlocal AQI measurement.
- Accuracy over features : ±10% accuracy target, validated against government reference stations
- Accessibility over complexity : No app required, no technical knowledge needed
- Affordability over premium : Target cost ≤₹5,000 (~$60 USD)
- Open over proprietary : All designs, code, and documentation freely available
| Feature | Specification |
|---|---|
| Pollutants Measured | PM2.5, PM10 |
| Accuracy Target | ±10% vs. CPCB reference stations |
| Display | 0.96" OLED — AQI value + category (Good/Moderate/Unhealthy/Severe) |
| Power | USB-C (5V) — works with any phone charger or power bank |
| Connectivity | WiFi (for initial calibration only) — then fully offline |
| Enclosure | Weather-resistant, designed for outdoor use |
| Target Cost | ≤₹5,000 BOM for single unit |
Most affordable air quality sensors suffer from two accuracy problems:
Problem 1: Environmental Sensitivity
Humidity causes particles to absorb water and swell. A sensor calibrated in dry conditions will significantly over-read in humid environments (common during monsoon or coastal areas). Temperature also affects laser sensor behavior.
Solution: Vaayu includes a BME280 environmental sensor and applies peer-reviewed correction algorithms in real-time based on current humidity and temperature.
Problem 2: Unit-to-Unit Variance
Two identical sensors from the same manufacturing batch can read 10-20% differently due to slight variations in laser alignment and photodetector sensitivity.
Solution: Vaayu implements auto-calibration via the CPCB public API. During initial setup, the device compares its readings against the nearest government monitoring station over 24-48 hours and learns its specific bias correction factor. No need to physically visit a reference station.
| Component | Model | Purpose | Est. Cost (INR) |
|---|---|---|---|
| PM Sensor | Plantower PMS5003 | Laser light-scattering particle detection | ₹900-1,100 |
| Environmental Sensor | Bosch BME280 | Temperature, humidity, pressure for corrections | ₹250-350 |
| Microcontroller | ESP32-C3 SuperMini | Processing, WiFi, USB-C native | ₹350-450 |
| Display | 0.96" OLED (SSD1306) | AQI readout | ₹150-200 |
| Enclosure | 3D printed (PETG) | Weather-resistant housing | ₹300-500 |
| Miscellaneous | Wires, connectors, PCB | Integration | ₹200-400 |
| Total BOM | ₹2,150 - ₹3,000 |
- Firmware: C/C++ (Arduino framework on ESP-IDF)
- Correction Algorithms: Based on peer-reviewed research on PMS5003 humidity response
- Calibration: CPCB API integration for reference data
- Display: Simple AQI number + category, no complex UI
PMS5003 (raw PM2.5) ──┐
├──▶ ESP32-C3 ──▶ Correction ──▶ Calibration ──▶ AQI ──▶ OLED
BME280 (temp/humidity)┘ │ Algorithm Offset Display
│
└──▶ WiFi ──▶ CPCB API (calibration phase only)
Vaayu uses the India National Air Quality Index (NAQI) standard:
| AQI Range | Category | Health Implications |
|---|---|---|
| 0-50 | Good | Minimal impact |
| 51-100 | Satisfactory | Minor breathing discomfort to sensitive people |
| 101-200 | Moderate | Breathing discomfort to people with lung/heart disease |
| 201-300 | Poor | Breathing discomfort to most people on prolonged exposure |
| 301-400 | Very Poor | Respiratory illness on prolonged exposure |
| 401-500 | Severe | Affects healthy people, serious impact on those with existing diseases |
🚧 Active Development
- Problem definition and use case validation
- Technical architecture design
- Component selection and sourcing research
- Correction algorithm research (literature review)
- Breadboard prototype assembly
- Basic firmware development
- Environmental correction implementation
- CPCB API integration
- Auto-calibration system
- Enclosure design (3D printable)
- Field testing and validation
- Documentation and build guides
| Phase | Timeline | Deliverables |
|---|---|---|
| 1. Prototype | Month 1-2 | Working breadboard prototype, basic firmware, initial accuracy baseline |
| 2. Correction | Month 2-3 | Humidity/temperature correction algorithms, validated accuracy improvement |
| 3. Calibration | Month 3-4 | WiFi provisioning, CPCB API integration, auto-calibration system |
| 4. Enclosure | Month 4-5 | 3D printed housing, thermal management, weather resistance validation |
| 5. Release | Month 5-6 | Complete documentation, build guides, public release |
Air pollution-related health costs in India are estimated at 1.4% of GDP annually. Access to accurate air quality information shouldn't be a privilege limited to those who can afford expensive monitoring equipment.
By open-sourcing Vaayu:
- Individuals can build their own monitor at component cost
- Communities can establish local monitoring networks
- Schools can use it as an educational platform for environmental science
- Researchers can improve algorithms and contribute corrections for different regions
- Local makers can adapt the design for specific use cases
The long-term vision: thousands of Vaayu devices across Indian cities, optionally contributing anonymized readings to create hyperlocal air quality maps with street-level resolution.
Contributions are welcome across all aspects of the project:
- PCB design optimization
- Alternative component suggestions (especially for local sourcing)
- Enclosure improvements for different manufacturing methods
- ESP32 sensor integration code
- Correction algorithm implementation and tuning
- Power optimization for battery operation (future)
- CPCB API integration
- Regional correction factor calibration
- Validation against reference instruments
- Build guides and tutorials
- Translations (Hindi, regional languages)
- Video assembly instructions
- Field validation in different cities/conditions
- Long-term reliability testing
- Comparison against reference monitors
Detailed build instructions coming soon
- Basic soldering skills (or access to pre-assembled modules)
- Arduino IDE or PlatformIO
- 3D printer access (for enclosure) or willingness to use alternative housing
# Clone the repository
git clone https://github.com/61-Keys/vaayu.git
cd vaayu
# Firmware instructions (coming soon)
# Hardware assembly guide (coming soon)vaayu/
├── firmware/ # ESP32 firmware source code
│ ├── src/
│ └── platformio.ini
├── hardware/ # Hardware design files
│ ├── schematic/
│ └── pcb/
├── enclosure/ # 3D printable enclosure files
│ └── stl/
├── docs/ # Documentation
│ ├── build-guide.md
│ ├── calibration.md
│ └── troubleshooting.md
├── research/ # Reference papers and data
├── funding.json # Open source funding manifest
├── LICENSE
└── README.md
Software: MIT License
Hardware: CERN Open Hardware License v2 - Permissive (CERN-OHL-P-2.0)
You are free to use, modify, and distribute both for personal and commercial purposes.
This project builds on the work of the global air quality monitoring community:
- AQICN.org — Extensive research on PMS5003 sensor behavior and correction factors
- PurpleAir — Demonstrating that low-cost monitoring networks can provide valuable data
- AirGradient — Open-source air quality monitor designs
- CPCB — India's Central Pollution Control Board for reference data access
- Academic researchers — Peer-reviewed studies on optical particle counter correction algorithms
-
Zheng, T., et al. (2018). "Field evaluation of low-cost particulate matter sensors in high and low concentration environments." Atmospheric Measurement Techniques.
-
Barkjohn, K.K., et al. (2021). "Development and Application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor." Atmospheric Measurement Techniques.
-
Central Pollution Control Board. "National Air Quality Index." Ministry of Environment, Forest and Climate Change, Government of India.
Asutosh Rath
- 📧 Email: [email protected]
- 🐙 GitHub: github.com/61-Keys
- 📍 Bengaluru, India
Project Vaayu is seeking funding through open-source grant programs. See funding.json for details.
If you'd like to support this work:
- ⭐ Star this repository
- 🔄 Share with others who might benefit
- 🛠️ Contribute code, designs, or documentation
- 📣 Spread the word about hyperlocal air quality monitoring
Breathe informed. Breathe better.