CYCLOPOLIS stationary sensor kit

As part Chania’s VS2, the bike stations of Chania’s bike sharing system were mounted with customed stationary sensor kits to measure pollutants and noise.

Parameters measured by the sensor:

• Particulates of various sizes (PM1, PM2.5, PM10) as the mobile sensor kit
• SO2
• NOx
• O3
• CO
• NH3
• Cl
• CO2
• organic substances

Particulate matter data are enriched with temperature and relative humidity data from the corresponding sensor, which is also located into the sensor kit. All available data is geolocated to trace possible pollution hotspots. The sensory kit is designed  to be mounted on public bikes and for this reason it is light, reliable and with a low need for power.

These sensor kits have been mounted on 4 bike sharing stations, as well as on Chania’s VS1, the MULaR.

What were the technical need and the market need?

There is extensive research on how exposure to air pollutants has been linked to various acute and chronic health issues, such as the increased risk of cardiovascular disease and respiratory infections, dementia, Parkinson’s disease, cognitive impairment, kidney disease, diabetes, and issues with the reproductive system. However, air pollution levels can vary significantly over short distances, particularly in urban areas such as Chania, and near emission sources.

Therefore, measurements on local pollutants is crucial to understand and develop adequate mitigation actions. However, sensors to measure local pollutants (like PMx and noise) were (and still are) expensive: a multitude of sensors in a dense network is needed, and to make the matter even worse, communicating data of such a size can also be costly.

Although stationary meteorological stations are common and give us data on several aspects of pollution, they remain expensive (approximately 15K € each). In the last few years, technological developments have increased the reliability of low-cost sensors, and facilitated IoT solutions through geolocation and advanced data transmission techniques (eg GPS, LoRa networks),  while at the same time sensor costs and telecom rates kept falling , and machine learning techniques have made their processing and analysis of large data pools more cost effective.

Taking these factors into account, Cyclopolis considered that:

• affordable solutions for measuring effectively on the local level were now possible.
• shared micromobility fleets now flood the streets of modern urban environments
• the severe effects of poor air quality and noise on human health and well-being have been broadly recognised

Cyclopolis therefore proposed to design a stationary low-cost sensor kit to measure local air pollution levels and noise levels.

How was it developed?

The digital ecosystem of the kit has 3 main components:

• A protocol, supporting Wi-Fi communication
• A Front-End server, implementing the network service, the visualization service and the API for data ingestion
• A Back End server, implementing the database.

The stationary kit is directly plugged to the bike station which provides the kit with the necessary electric power. Having no power problem to solve, the stationary kits sensors’ payload was extended.

Data collection

A database stores the data coming from the different registered devices ; for VARCITIES implementation Cyclopolis initially started with a NO-SQL database (InfluxDB), but during the test phase, shifted to another database (PostgreSQL).

The collected data can be shared with APIs. For the purpose of VARCITIES, the collected data are fed into VARCITIES Health & Well-Being Platform.

Data reliability

Although sensors come calibrated, Cyclopolis undertook considerable further calibration efforts, measuring side-by-side with reference stations bearing expensive sensors that measure the same pollutants in an effort to analyse and compared collected data over an extensive time period. From this process Cyclopolis concluded that data did need calibration due to considerable differences between the data produced by expensive and those produced by cheaper sensors. However, given that the deviations were systematic, after long analysis and tests, Cyclopolis inferred the respective calibration algorithms.

In effect, we consider the data produced by Cyclopolis stationary sensor kits as reliable as those produced by any reference station.

Market potential

Any entities looking to improve public health, advertise its good air quality level may be interest in the product. Depending on the payload, which can be as extensive as needed, the cost of the stationary sensor kit remains at a fraction of the respective cost of a meteorological station.