Concerns about air pollution and its harmful effects on human health have been growing in recent years, particularly in urban areas. However, monitoring air quality is often difficult due to the specialized equipment and resources required, which may not be readily available to everyone. To address this problem, researchers at the Massachusetts Institute of Technology (MIT) have developed an open-source platform for building a low-cost air-quality detector called Flatburn, which can be assembled using affordable parts that can be purchased online.
The Flatburn platform includes instructions for building the detector, with a 3D-printable shell and a shopping list of additional components such as solar panels for power and magnets for attaching it to a vehicle. The device runs on code provided by the platform, and there is a visual assembly guide available.
The platform also provides information on how to interpret and share the data that the device collects, so that users can spot trends or pollution hot spots. By making this information accessible, the Senseable City Lab at MIT hopes to empower communities and give researchers access to local experts and qualitative data about pollution sources.
One of the main challenges in building a low-cost air-quality detector is ensuring that the data it collects is accurate and reliable. Cheap sensors tend to be imprecise, and their readings can drift over time, making them inaccurate. To address this problem, the researchers at MIT have developed a machine-learning algorithm that calibrates the data collected by the Flatburn device based on stationary air-quality sensors.
These sensors are more expensive but provide more accurate readings, taking into account factors such as wind and weather conditions that can affect air quality. By using the readings from these sensors to calibrate the data collected by the Flatburn device, the researchers have made it comparable in accuracy to more costly sensors used by organizations such as the Environmental Protection Agency (EPA).
The Senseable City Lab at MIT, which developed the Flatburn platform, has been working on a mobile air-pollution detector since 2017. They have done pilot projects using fleets of these devices on garbage trucks, buses, and taxis in cities such as Cambridge, Massachusetts, New York, and Stockholm. These projects helped to refine the sensing hardware and processing the air-quality data. The open-source Flatburn platform is the latest development in their efforts to make air-quality monitoring more accessible and democratic.
The Flatburn device can provide more granular data on air quality than the broader measurements provided by most weather apps, which tend to be aggregated for an entire region. This is important because air quality can vary widely even within a single city block, depending on factors such as car exhaust, road work, or construction sites.
These sources of pollution can have serious health impacts, increasing the risk of heart disease, lung cancer, asthma attacks, and other respiratory problems. By providing more detailed information, the Flatburn platform can help communities identify pollution hot spots and develop mitigation strategies.
The Senseable City Lab hopes that the Flatburn platform will be a tool for communities, allowing people to build their own air-quality monitors and share the data they collect. They also hope that people will become more involved in understanding and using the data collected by these monitors.
By democratizing environmental data, the Senseable City Lab is helping to create a network of citizen scientists who can collect and share data on air quality in their communities. This data can then be used to identify pollution hot spots, develop pollution-exposure maps, and design-mitigation actions to address the problem of air pollution.
