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:

1. Collect PM2.5 and PM10 data from many Malaysian locations.
2. Build a public community air-quality map.
3. involve schools, universities and citizens in environmental monitoring.
4. Detect unusual pollution patterns at neighbourhood level.
5. 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

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

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

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-001
• MY-JHR-JB-003
• MY-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:

1. Start the particulate, temperature and humidity sensors.
2. Connect to Wi-Fi.
3. Synchronise the clock.
4. Allow the particulate sensor to stabilise.
5. Take several readings.
6. Remove clearly invalid measurements.
7. Calculate a short average.
8. Send the payload to FAVORIOT over HTTPS or MQTTS.
9. Confirm successful transmission.
10. Save failed readings locally.
11. Retry when connectivity returns.
12. Report station-health information.
13. 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

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:

1. Apply through an online form.
2. Provide the general proposed location.
3. Choose to build, sponsor or host a station.
4. Accept the data-sharing and privacy terms.
5. Receive a station ID and QR code.
6. Follow the installation guide.
7. Upload installation photographs.
8. Run the station for a seven-day probation period.
9. Pass the data-quality review.
10. 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

18. Pilot budget

Ten-station pilot

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.