Live Visualization of Emission - Towards Avoidance of Pollution Hotspot (LiVE-TAP)

Project: Research

Project Details


Poor-air-quality is the largest environmental-risk to public-health in the UK, causing tens-of-thousands of early deaths and billions-of-pounds in health-impacts yearly (Parliament-business,2018). Emissions contribute to 40,000 premature-deaths yearly, and contributes to heart problems, dementia, diabetes, cancer, asthma and stroke(Royal-College-of-Physiciansand-of-Paediatrics-and-Child-Health, 2018). Its annual cost to UK economy is £62bn (World-Health-Organization).

Emissions effect can be devastating in highly frequented outdoor places like city/town-centre, high streets and school-run routes. For examples (a) Most UK city/town-centres, including 44 of the 51 listed in WHO's quality database, have over the limit emission levels causing millions of people to inhale dangerous-air (WHO,2017) (b) Cars on school-run-route cause damaging pollution to the 51% of pupils who walk to school with an accompanying adult; Ella recently died from such pollution, with doctors clearly saying use of less-polluted-alternative routes to school would have saved Ella(BBC,2018).

Present ways of predicting pollutant-emissions through estimation of vehicle numbers on roads are inaccurate because emissions-per-vehicle data are unreliable, as evidenced in the recent Volkswagen scandal. Monitoring stations on the other hand give average values for large-areas (e.g. neighbourhood, district, town etc.) over a period (usually monthly), with results published after taking samples to laboratory. The results only inform and cannot help citizens to make eco-healthy pollution-avoidance-decisions.

This project thus aims to develop a holistic system which communicates 'accurate' live-emission-data of city-centre-streets and school-run-routes to citizens through digital means including mobile-phone apps. This will allow citizens/users to decide when (not) to use certain city-centre-streets/school-run-routes, or which ones (not) to use (i.e. avoidance behaviour), based on emission levels. This will help to greatly reduce the amount of emission inhaled by users and divert traffic away from highly polluted areas thereby reducing pollution. The acquired data will also be used to predict future emission- levels to allow eco-healthy planning and inform local-authority policies

The system will include

i) Internet-of-Things sensors installed on city-centre-streets and school-run-routes to accurately measure key pollutants like NO2, CO2 and PM2.5s

ii) Mobile-phone/computer apps to directly relay live-emission-levels data to city-centre-streets and school-run-routes users and stakeholders using heat-maps on digital-geographic-maps.

iii) Cloud-storage, big-data-analytics and machine-learning-algorithms used with acquired data to predict future-emission levels to allow eco-healthy planning and inform local-authority policies

iv) Emission-data-as-service to tour/trip/route plan providers (e.g. Tour-Planner, Google-maps,etc.) for improving their services.

v) A crowdsourcing-platform hosted for future installers of IoT emission sensors to sell their data through Blockchain-Technology.
Research Costing Number: 1469
Project Code: C005117.01
StatusNot started


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