Project Malaysia AirWatch – Air Quality Index Using FAVORIOT
August 29th, 2026 Posted by favoriotadmin BLOG, HOW-TO, Internet of Things, IOT PLATFORM, PRODUCT, SMARTCITY 0 thoughts on “Project Malaysia AirWatch – Air Quality Index Using FAVORIOT”Crowdsourced Air-Quality Monitoring Using the FAVORIOT Developer Plan
1. Project concept
Malaysia AirWatch is a citizen-supported air-quality monitoring project. Schools, universities, community groups, businesses and individual volunteers install low-cost sensor stations at their locations.
Each station measures local air conditions and sends the readings to the FAVORIOT platform. The combined data appears on a public map showing air-quality patterns across Malaysia.
The project does not replace the Department of Environment’s official monitoring stations. It provides denser, neighbourhood-level observations that may help people identify local changes, pollution hotspots and unusual events.
The basic flow is:
flowchart LR
A["Community sensor"] --> B["Wi-Fi or 4G"]
B --> C["FAVORIOT"]
C --> D["Quality checks"]
D --> E["Public map"]
D --> F["Alerts and analysis"]2. Project objectives
The project should pursue five clear objectives:
- Collect PM2.5 and PM10 data from many Malaysian locations.
- Build a public community air-quality map.
- involve schools, universities and citizens in environmental monitoring.
- Detect unusual pollution patterns at neighbourhood level.
- Create a national dataset for education, research and public awareness.
A good pilot target would be:
- 100 monitoring stations
- At least 10 states
- Urban, suburban and rural locations
- One reading every five minutes
- Six months of continuous operation
- At least 85% station uptime
3. Why the FAVORIOT Developer Plan fits
The current Developer Plan costs RM300 per month or RM3,000 per year. It includes:
- 500,000 API calls per day
- Unlimited devices
- Unlimited private and public dashboards
- Up to 30 widgets per dashboard
- Map widgets
- Device connectivity status
- Data import and export
- Edge Gateway
- Firmware OTA
- Advanced analytics and machine-learning models
- Email and Telegram notifications
- HTTP POST forwarding to external systems
- Customer accounts with designated access
- One-year data retention
These features make it suitable for a national crowdsourcing pilot. FAVORIOT pricing page
Estimated platform capacity
If each station sends one message every five minutes:
288\ messages\ per\ station\ per\ day
| Number of stations | Messages per day | Developer Plan usage |
|---|---|---|
| 100 | 28,800 | 5.8% |
| 500 | 144,000 | 28.8% |
| 1,000 | 288,000 | 57.6% |
| 1,500 | 432,000 | 86.4% |
Theoretically, one Developer Plan can support about 1,700 stations at five-minute intervals. A safer operational ceiling would be around 1,300 to 1,500 stations, leaving capacity for testing, device management, retries and external applications.
4. Choose what the stations will measure
Required measurements
Every station should measure:
- PM2.5
- PM10
- Temperature
- Relative humidity
Temperature and humidity matter because low-cost particulate sensors can be affected by environmental conditions.
Optional measurements
Selected research-grade stations may also measure:
- Carbon dioxide
- Carbon monoxide
- Nitrogen dioxide
- Ozone
- Volatile organic compounds
- Atmospheric pressure
- Noise level
I would not put every sensor into the first version. Gas sensors can produce misleading readings without proper calibration. Start with PM2.5, PM10, temperature and humidity.
5. Build the standard AirWatch station
Recommended components
| Component | Purpose |
|---|---|
| ESP32 development board | Reads sensors and sends data |
| PMS5003, PMS7003 or SPS30 | Measures PM2.5 and PM10 |
| BME280 or SHT31 | Measures temperature and humidity |
| Wi-Fi connectivity | Sends data through the host’s internet connection |
| Weather-resistant enclosure | Protects the electronics |
| Ventilation openings | Allows air to reach the sensor |
| 5V power supply | Powers the station |
| Unique QR code | Identifies and registers the station |
For locations without Wi-Fi, use:
- 4G LTE router or modem
- LoRaWAN gateway where local coverage exists
- Store-and-forward memory when connectivity is interrupted
Estimated hardware cost
| Station type | Estimated cost |
|---|---|
| Basic educational station | RM180–RM300 |
| Better outdoor community station | RM350–RM650 |
| 4G-connected station | RM600–RM1,000 |
| Reference or calibration station | RM3,000 and above |
These are planning estimates. The final cost depends on sensor model, enclosure, power and connectivity.
6. Define where sensors may be installed
Participants should place stations:
- Under a sheltered outdoor area
- Between 1.5 and 3 metres above ground
- Away from kitchen exhausts
- Away from cigarette-smoking areas
- Away from direct rain
- Away from air-conditioning outlets
- With unrestricted airflow
- Where the Wi-Fi signal is stable
- Where power is continuously available
The project should record the installation environment:
- Roadside
- Residential
- School
- University
- Industrial vicinity
- Commercial
- Rural
- Agricultural
- Coastal
- Forest-edge
Without this context, two readings may appear comparable when they are actually taken under very different conditions.
7. Create the FAVORIOT project structure
Create the following hierarchy in FAVORIOT:
Project
Malaysia AirWatch
Applications
- Community Air Quality Monitoring
- Station Health Monitoring
- Research and Analytics
- Public Air Quality Map
Groups
Groups can represent states:
- Johor
- Kedah
- Kelantan
- Melaka
- Negeri Sembilan
- Pahang
- Penang
- Perak
- Perlis
- Sabah
- Sarawak
- Selangor
- Terengganu
- Kuala Lumpur
- Putrajaya
- Labuan
For a larger deployment, create subgroups using districts or station categories.
Device naming convention
Use a consistent device ID:
MY-[STATE]-[DISTRICT]-[NUMBER]
Examples:
MY-SGR-PUCHONG-001MY-JHR-JB-003MY-SWK-KUCHING-012
Do not use a volunteer’s name, house address or telephone number in the device ID.
8. Design the data payload
Each station should send a consistent JSON payload:
{
"device_developer_id": "MY-SGR-PUCHONG-001@username",
"data": {
"pm1": 8.4,
"pm25": 18.7,
"pm10": 31.2,
"temperature": 29.8,
"humidity": 71.4,
"latitude": 3.0321,
"longitude": 101.6185,
"location_type": "residential",
"firmware_version": "1.0.0",
"sensor_model": "PMS5003",
"wifi_rssi": -63,
"uptime_seconds": 86420,
"quality_flag": "raw"
}
}FAVORIOT supports HTTPS, MQTT, WebSocket and CoAP for device connectivity. Each device can be given its own access token rather than sharing the account’s main API key. FAVORIOT platform documentation
9. Protect participant privacy
Exact household coordinates should not be displayed publicly.
Use two location levels:
- Exact coordinates: kept in the private administration records.
- Public coordinates: rounded or displaced by approximately 500 metres to 1 kilometre.
Public participants should see only:
- Station ID
- General area
- District and state
- Latest readings
- Historical trend
- Station status
- Sensor type
- Last update time
The registration form should explain:
- What information will be collected
- Which information will be public
- Who owns the contributed data
- How the data may be used
- How participants can withdraw
- Whether researchers may download the dataset
10. Develop the sensor firmware
The ESP32 firmware should perform these steps:
- Start the particulate, temperature and humidity sensors.
- Connect to Wi-Fi.
- Synchronise the clock.
- Allow the particulate sensor to stabilise.
- Take several readings.
- Remove clearly invalid measurements.
- Calculate a short average.
- Send the payload to FAVORIOT over HTTPS or MQTTS.
- Confirm successful transmission.
- Save failed readings locally.
- Retry when connectivity returns.
- Report station-health information.
- Check for firmware updates.
Recommended sampling:
- Read sensors every 30 seconds.
- Calculate the median or trimmed mean over five minutes.
- Send one consolidated message every five minutes.
This reduces noise and consumes fewer API calls than transmitting every raw reading.
11. Test ten prototype stations
Do not immediately distribute 100 stations. Build ten prototypes first.
Place them in several conditions:
- Two beside an official or trusted reference station
- Two at universities
- Two at schools
- Two in residential areas
- One near a busy road
- One in a rural area
Run them for four weeks. During testing, check:
- Differences between units
- Humidity effects
- Missing data
- Sensor drift
- Wi-Fi failures
- Heat inside the enclosure
- Rain protection
- Firmware stability
Put all ten units beside one another for several days before deployment. This co-location test reveals whether one sensor consistently reads higher or lower than the others.
12. Create data-quality rules
Crowdsourced measurements require visible quality labels.
Suggested quality flags
| Flag | Meaning |
|---|---|
| Verified | Station has passed co-location and installation checks |
| Provisional | Station is operating but has limited validation |
| Suspect | Reading failed one or more quality tests |
| Offline | No data received within the expected period |
| Maintenance | Station is being serviced |
| Rejected | Reading is physically impossible or corrupted |
Automatic checks
Flag a reading when:
- PM2.5 or PM10 is negative
- PM2.5 is far higher than PM10
- Temperature or humidity is outside plausible limits
- The same reading repeats for an unusually long time
- The value changes too sharply between intervals
- The station has weak connectivity
- The device clock is wrong
- Readings diverge greatly from nearby stations
A high reading from one low-cost station should be treated as a signal to investigate, not proof of a pollution incident.
13. Build the FAVORIOT dashboards
Public national dashboard
Include:
- Map of all active stations
- Latest PM2.5 readings
- Colour-coded air-quality categories
- National average
- Highest current readings
- State comparison
- Twenty-four-hour trend
- Last update time
- Explanation of the quality flags
- Clear non-regulatory disclaimer
State dashboard
Include:
- State map
- District comparison
- Hourly PM2.5 and PM10 trends
- Seven-day trend
- Active and offline stations
- Locations with unusual readings
Technical dashboard
Keep this private for administrators:
- Device connectivity status
- Wi-Fi strength
- Last message time
- Firmware version
- Sensor age
- Missing-data rate
- Battery or power status
- Stations requiring maintenance
Research dashboard
Include:
- PM2.5 versus humidity correlation
- Weekday versus weekend patterns
- Morning and evening peaks
- Urban versus rural comparisons
- Seasonal trends
- Anomaly detection
- Time-series forecasts
14. Configure rules and alerts
Create platform rules for:
Air-quality alerts
- PM2.5 exceeds the project threshold for three consecutive readings
- PM10 rises sharply within 30 minutes
- Several nearby stations detect the same increase
Station-health alerts
- No data for 20 minutes
- Device repeatedly reconnects
- Wi-Fi strength remains poor
- Sensor produces fixed values
- Firmware is outdated
Send technical alerts to the project team through Telegram or email. Avoid sending public health alerts until the measurements and interpretation method have been properly reviewed.
15. Recruit contributors
Potential participants include:
- Public and private universities
- Secondary schools
- TVET institutions
- Local councils
- Resident associations
- Environmental NGOs
- Makerspaces
- Technology companies
- Factories and industrial parks
- Farms and plantations
- Citizen scientists
Participation models
Sponsor a station
A company pays for stations to be installed at schools or community centres.
Build your own station
Universities, students and makers assemble a station using the approved design.
Host a station
FAVORIOT supplies the station while the participant provides electricity, Wi-Fi and a suitable location.
Research partner
A university supports calibration, analysis and publication.
16. Create the contributor onboarding process
Every participant follows the same steps:
- Apply through an online form.
- Provide the general proposed location.
- Choose to build, sponsor or host a station.
- Accept the data-sharing and privacy terms.
- Receive a station ID and QR code.
- Follow the installation guide.
- Upload installation photographs.
- Run the station for a seven-day probation period.
- Pass the data-quality review.
- Appear on the public map.
The QR code can open the public station page and display its readings, history and validation status.
17. Run a 12-week pilot
| Week | Main activity | Output |
|---|---|---|
| 1 | Confirm objectives, governance and measurements | Project charter |
| 2 | Select sensors and design enclosure | Hardware specification |
| 3 | Configure FAVORIOT hierarchy and payload | Working platform structure |
| 4 | Develop ESP32 firmware | First connected prototype |
| 5 | Assemble ten units | Prototype fleet |
| 6 | Conduct co-location testing | Baseline comparison |
| 7 | Improve hardware and correction method | Revised station |
| 8 | Install at pilot sites | Live field data |
| 9 | Create dashboards and maps | Public beta dashboard |
| 10 | Configure alerts and quality rules | Monitoring workflow |
| 11 | Recruit first community participants | Initial contributor network |
| 12 | Review results and approve expansion | Pilot report |
18. Pilot budget
Ten-station pilot
| Item | Estimated cost |
|---|---|
| Ten sensor stations at RM450 | RM4,500 |
| Spare sensors and components | RM1,000 |
| Enclosures and installation materials | RM800 |
| FAVORIOT Developer Plan, one year | RM3,000 |
| SIM and data for selected sites | RM600 |
| Calibration and field visits | RM2,000 |
| Workshops and participant materials | RM1,500 |
| Contingency | RM1,500 |
| Estimated total | RM14,900 |
Internal staff time, travel across Malaysia and the development of a separate public web application would need their own allocation.
19. Success indicators
Technical indicators
- At least 85% station uptime
- At least 95% valid readings
- Less than 10% missing data
- Data delivered within ten minutes
- All stations remotely identifiable
- Firmware updates completed without visiting every station
Participation indicators
- Ten states represented during the first phase
- At least 20 partner organisations
- At least 100 active contributors
- At least five participating universities
- At least ten participating schools
Data indicators
- Six months of usable observations
- Verified co-location results
- Published data-quality method
- Monthly community air-quality reports
- At least three research or student projects using the data
20. How the project can grow
Phase 1: Ten-station technical pilot
Prove the sensor, firmware, platform and data-quality process.
Phase 2: One hundred community stations
Expand through universities, schools and resident associations.
Phase 3: Five hundred stations
Bring in local councils, corporate sponsors and environmental groups.
Phase 4: National operational network
Move to an Enterprise or dedicated arrangement when the project needs:
- Multiple administrative organisations
- Longer data retention
- Higher API volume
- Dedicated infrastructure
- Formal service levels
- Stronger data-governance controls
- Links with government or emergency systems
21. Important public disclaimer
The dashboard should carry a clear statement:
Malaysia AirWatch uses low-cost community sensors to provide local environmental observations. Its readings are indicative and may be affected by sensor accuracy, placement, humidity and maintenance. The data should not be treated as an official Malaysian Air Pollutant Index or used alone for medical, regulatory or emergency decisions. Refer to the relevant Malaysian authorities for official air-quality information.
Suggested project message
Your neighbourhood’s air should not be invisible.
Malaysia AirWatch allows schools, universities, communities and citizens to help measure the air around them. One sensor may tell us what is happening at one location. Hundreds of connected sensors can help us see patterns across the country.
Build a station. Host a station. Sponsor a community. Help Malaysia see the air we breathe.
