Big data, pollution and the IoT
Anyone who has lived in a big city will know what it’s like to breathe polluted air. Newcomers to London, for instance, never fail to mention the famous ‘black bogie’ effect associated with taking the tube. Cyclists take to wearing masks to avoid being gassed by car exhaust fumes, and many an allergy sufferer might notice that their symptoms are worse inside the city than outside it.
It’s not just London, either. Pollution is a problem across the world, and has significant implications for public health. According to the World Health Organization, over 5.5 million people die each year because of polluted air, making lack of clean air the third leading cause of death after heart disease and smoking.
Unsurprisingly, cities are the worst offenders, thanks to exhaust and emissions from cars, factories and power plants. But some interesting new city initiatives are trying to tackle the problem with IoT and artificial intelligence technologies. Using connected sensors to measure exactly where pollution is coming from, they can pinpoint the numerous factors that contribute to it, and ultimately, reduce it. Below, we take a look at some of these initiatives.
Combined insights: historical vs real-time data
The causes of pollution are many and various: emissions, pollen levels, the weather, humidity, temperature, traffic levels – all are contributing factors. It’s only by viewing data from these influencers alongside one another that we get a complete picture. IoT and artificial intelligence technologies make it possible to combine all these insights with historical data to pinpoint trends and ultimately reduce pollutants.
IBM’s Green Horizons initiative aims to do exactly this. A Green Horizons project in Beijing, for example, uses connected sensors to collect data around traffic levels, exhaust fumes, weather and humidity. A cognitive forecasting system uses this information alongside historical pollution data and weather data to predict air pollution levels in the coming days. Finally, these insights inform various test scenarios for reducing pollution.
Understanding pollution in Chicago with The Array of Things
Chicago is currently home to a project known as ‘The Array of Things’, which is designed to measure and identify major causes of pollution in the city. A vast network of sensors and nodes positioned on lampposts throughout the city measures levels of carbon monoxide, sulphur dioxide, hydrogen sulphide and hydrogen dioxide in real time.
This information helps define the pollution problem more precisely. For one thing, it separates ‘pollution’ out into defined categories: large particles such as pollen, which trigger allergies, or smaller particles that are more dangerous because they go straight into the bloodstream. For another, it helps pin down the sources of pollution, by determining which gases are associated with which vehicles, for instance.
Eventually, data collected by the sensors will be made freely available to the public, so that they can use it to avoid heavily polluted areas. Allergy sufferers, for example, will be able to see which areas they should avoid at which times, and plan their movements accordingly. Others could choose to find alternative routes to school or work.
With sensors, IoT data, artificial intelligence and human expertise can identify pollutants, and design coping mechanisms to reduce the impact of pollution. To read more about how IoT technologies are creating a greener planet, check out IoT and the environment: a greener world.