Title: Pollution Avoidance Support System (PASS) using GIS, Machine Learning and Big Data

Air pollution kills millions every year. Like a 'pandemic in slow motion', dirty air is a plague on our health, causing 7 million deaths and many more preventable illnesses like stroke, heart disease, chronic obstructive pulmonary disease, lung cancer and acute respiratory infections worldwide each year (WHO, 2021). In the UK, it causes 36,000 premature deaths yearly (government's Committee on the Medical Effects of Air Pollutants COMEAP) and costs £20 billion every year.
Although, pandemic-induced lockdowns have caused the largest absolute drop in annual global emissions in 2020, lockdown easing has now seen emission surge back to more than pre pandemic levels. Despite the actions taken by many governments (e.g. enacting clean air zones), poor air quality is projected to continue into 2050 (OECD, 2019).
Scientists have thus recommended dodging approach to vulnerable people like those with respiratory illness (e.g. coronavirus, asthma, bronchitis, etc.) who develop complications and sometimes die due to exposure to high pollution levels (European Public Health Alliance, 2020). Pollution levels can vary widely between different areas of a city/town and will vary from time to time for a particular area. Current pollution information platforms, which provide city-wide information, are thus ineffective for dodging approach as a vulnerable person is unable to decipher which area to use or avoid if they were out on walk/journey/exercise etc. A far more useful solution would be to provide pollution data on a much smaller scale, at postcode-units level for example, thereby supporting informed decision for users. However, the UK does not, and probably cannot, have monitoring equipment for each of its approximately 1.7 million postcode-units. Nonetheless, the 10s of 1000s of emission-sensors operational across UK (BBC, 2019) provide enough data to develop models for all postcode-units if the right tools are deployed.
This project therefore aims to develop a system that can provide pollution data for every 5,000meter-square (minimum postcode-units size is 76,000square meter) and postcode-units-specific pollution data to users using machine learning algorithms, ordinance survey location data, telematics, weather data and big data analytics. The platform will be available via both web and mobile app and will include