Air Quality Monitoring With IoT Big Data

Smart London

Poor air quality in London and many other cities is causing an acknowledged public health problem. Air pollution is now the world’s fourth-leading fatal health risk, causing one in ten deaths in 2013. If cities are to continue to flourish and prosper then they must tackle this air pollution crisis.

The GSMA is working with the Royal Borough of Greenwich on an air quality initiative utilising mobile, IoT and Big Data technologies, which aims to improve the health prospects and quality of life for citizens, while providing city administrators with vital information to implement new solutions and quantify their success. Find out more in the video below:

Taiwan, Province of China

For the initial Greenwich study, the GSMA had determined that machine learning could be applied to the task of predicting air quality for the near future based on historical air quality and weather data and a short-term weather forecast. The GSMA then worked with Far EasTone Communications (FET) in Taiwan, Province of China to include mobile network analytics into the machine learning models.

FET replicated the GSMA IoT Big Data and Machine Learning architecture in Taiwan for weather & air quality data acquisition. The key aims of this proof of Concept was to:


The resources below provide more information on air quality, IoT and Big Data

Addressing Air Quality with IoT Big Data is a value generation report exploring the roles mobile operators could undertake and the types of products, services and solutions that they could offer to create additional value. Our other report Air Quality Monitoring with IoT Big Data: A Technical Guide for Data Processing and Analytics shares experiences and common data analytical techniques from the experience of developing analytics services in the air quality field based on joint projects firstly with Royal Borough of Greenwich in the UK and secondly with Far EasTone Telecommunications (FET) in Taiwan, Province of China.