Air pollution is responsible for 4.2 million deaths per year according to the World Health Organization (WHO). No wonder we should dedicate resources to understand and monitor air quality in our cities and neighbourhoods. This should help authorities in urban planning as they can decide where to plant trees, build green spaces and manage traffic. Also, it can make us all aware of the impact of air pollution in our everyday life, which is critical to our health.

In this article, we approach air pollution from a different angle. We want to introduce and discuss the concept of crowdsourcing air quality monitoring. For those unfamiliar with the concept of crowdsourcing, it is about engaging the public to achieve a common goal. We can achieve this by dividing the work among participants in small tasks; in this case, collect air quality measurements. Our aim is to use crowdsourcing in a smart way to build up an accurate air pollution heatmap with the use of Artificial Intelligence (AI).

We argue that crowdsourcing can potentially be a better approach than the static air quality sensors placed in cities at the moment. First of all, not every city or town has one, and when they do, they are typically placed in a way to capture the average air quality of that area. This means they do not necessarily reflect the pollutants we will breathe in when we are walking in the city centre, for example. Also, we need to consider the cost of acquiring, maintaining and using those static air quality sensors.

On the contrary, the crowdsourcing proposal relies on our willingness to participate. This, however, would also require the use of low-cost mobile air quality devices to take readings in our whereabouts.

Importantly, we do not want to actively be taking measurements everywhere at all times. This relates to practical reasons as well as data privacy ones. For starters, the sensor would have to operate continuously. It would also have to track our location and taking timestamped air quality measurements. That is even if we are indoors or it is in our bag or pocket. As a consequence, the battery life would be easily depleted. To top it all, that this tiny sensor would know more about your movements than your significant other. Not very good.

Thus, the challenge is to

identify when and where air-quality measurements should be taken to efficiently monitor our city.

#crowdsourcing #optimization #artificial-intelligence #air-pollution #air-quality #ai