Clustered Blockchain Platform for Air pollution Data Aggregation and Dissemination– A Big Data and Artificial Intelligence Approach to Air Pollution Tracking (Air-PoT)
Lead Participant:
NEW LEAF TECHNOLOGY SOLUTIONS LTD
Abstract
Like other lung-diseases, Covid-19 is exacerbated by air-pollution. Numerous studies from Cambridge University, Harvard University, among others revealed that higher pollutants concentrations correspond with exacerbated symptoms, fatalities spike and increased Covid-19 virus transmission (The Guardian, 2020; Healthcare-in-Europe, 2020; NCBI's journal on Environmental-Pollution, etc.). Previous studies similarly showed that air-pollution exposure dramatically increased complications/death-risk from SARS \[2003 coronavirus outbreak\], and other lung-diseases like Asthma.
Scientists propose that since Covid-19 and high air-pollution concentrations will likely be around for a longtime, people with lung-diseases like Covid-19, Asthma, etc. should consider actively avoiding places at their times of high pollution concentrations to reduce pollution associated complications/transmission/death toll. This will consequently reduce potential Covid-19 deaths triggered lockdowns which are currently decimating businesses and economy. Avoidance behaviour requires active pollution monitoring at granular levels, and effective/live dissemination of monitoring results. Such results can support informed decision to lock down small pockets, as against a whole city, with spike in Covid-19 complications/transmission/death toll that correspond with high pollution concentrations, providing the opportunity to return pollution and associated Covid-19 complications/transmission/death in such pockets to lower levels quickly.
The UK currently has the infrastructure for such granular monitoring, with tens of thousands of Internet-of-Things (IoT) enabled pollution-sensors in operation (BBC,2019). These equipment/sensors are owned by 100s of councils (e.g. London Mayor has 100s of sensors in London, Newcastle has over 600, etc.); 100s of consortiums' schemes (e.g. Happy Crocodile, Beat the street, etc.); numerous authorities/organisations (e.g. Port of London Authority); and numerous private groups (e.g. Clean-Air Eastbourne has over 10 sensors)
These owners however share their results through many different uncoordinated sources/websites (e.g. breathe London web, hackair web, among countless others) which display information in very different ways thus making access and ability to understand this data/information difficult. The trend is similar across Europe with massive number of sensors (EU Science Hub, 2017; iSCAPE, 2017) and USA with over 100,000 sensors (Understory, 2019; BBC, 2019), disseminated via many different means.
This project thus aims to provide a central platform that allows pollution equipment/sensors owners a single plug and play access to share live pollution data, which is then relayed to interested users in a simplified and personalised understandable format using an app. This in line with the UK government's clean air strategy to provide a personal air-quality messaging system to inform public of air-pollution levels. The project will include:
1) A clustered blockchain centralised platform that
1a) IoT pollution sensors owner can directly plug their data into for onward sharing.
1b) will pay sensors owners for use of their data
2) an app that will use big-data-analytics, deep learning and predictive analytics (artificial intelligence) to
2a) display pollution data based on end users' areas of interest (e.g. using postcode or route search)
2b) produce a data centric air pollution model for areas without monitoring equipment.
2c) predict forthcoming pollution levels using historic weather, traffic and other pollution driving data
3) Databank of historic pollution data that can be bought for research, consultancy, policy making, etc.
Scientists propose that since Covid-19 and high air-pollution concentrations will likely be around for a longtime, people with lung-diseases like Covid-19, Asthma, etc. should consider actively avoiding places at their times of high pollution concentrations to reduce pollution associated complications/transmission/death toll. This will consequently reduce potential Covid-19 deaths triggered lockdowns which are currently decimating businesses and economy. Avoidance behaviour requires active pollution monitoring at granular levels, and effective/live dissemination of monitoring results. Such results can support informed decision to lock down small pockets, as against a whole city, with spike in Covid-19 complications/transmission/death toll that correspond with high pollution concentrations, providing the opportunity to return pollution and associated Covid-19 complications/transmission/death in such pockets to lower levels quickly.
The UK currently has the infrastructure for such granular monitoring, with tens of thousands of Internet-of-Things (IoT) enabled pollution-sensors in operation (BBC,2019). These equipment/sensors are owned by 100s of councils (e.g. London Mayor has 100s of sensors in London, Newcastle has over 600, etc.); 100s of consortiums' schemes (e.g. Happy Crocodile, Beat the street, etc.); numerous authorities/organisations (e.g. Port of London Authority); and numerous private groups (e.g. Clean-Air Eastbourne has over 10 sensors)
These owners however share their results through many different uncoordinated sources/websites (e.g. breathe London web, hackair web, among countless others) which display information in very different ways thus making access and ability to understand this data/information difficult. The trend is similar across Europe with massive number of sensors (EU Science Hub, 2017; iSCAPE, 2017) and USA with over 100,000 sensors (Understory, 2019; BBC, 2019), disseminated via many different means.
This project thus aims to provide a central platform that allows pollution equipment/sensors owners a single plug and play access to share live pollution data, which is then relayed to interested users in a simplified and personalised understandable format using an app. This in line with the UK government's clean air strategy to provide a personal air-quality messaging system to inform public of air-pollution levels. The project will include:
1) A clustered blockchain centralised platform that
1a) IoT pollution sensors owner can directly plug their data into for onward sharing.
1b) will pay sensors owners for use of their data
2) an app that will use big-data-analytics, deep learning and predictive analytics (artificial intelligence) to
2a) display pollution data based on end users' areas of interest (e.g. using postcode or route search)
2b) produce a data centric air pollution model for areas without monitoring equipment.
2c) predict forthcoming pollution levels using historic weather, traffic and other pollution driving data
3) Databank of historic pollution data that can be bought for research, consultancy, policy making, etc.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
  | ||
Participant |
||
NEW LEAF TECHNOLOGY SOLUTIONS LTD |
People |
ORCID iD |
Simon Chambers (Project Manager) |