Smart cities will be able to discover the long-term impacts of adverse air quality on public services and the health of their people by utilizing GeoSpock’s state-of-the-art data management software.
GeoSpock processed time series measurements of various atmospheric gas and particulate matter concentrations via 19 sensors spread across four areas of Cambridge – the company’s home city, which like many expanding urban destinations across the world is facing a challenge to accommodate increasing populations and traffic volumes.
Analysis of air quality levels over a week-long period at the junction of Lensfield Road and Trumpington Road in Cambridge revealed a clear correlation between the number of vehicles and emissions of Ozone and, to a slightly lesser extent, Nitric Oxide. By exploring these correlations, the pulse of city life can be clearly seen.
POLLUTION AND VEHICLE COUNT
Only by leveraging GeoSpock’s unique extrapol8 software for complex analytics can visualizing pollution levels and the flow of traffic whilst identifying correlations become a reality. This can provide a clear picture for a city’s policy-makers regarding where and when there are air quality issues – and then it is up to them how they act.
However, identifying patterns and being able to adapt policies and strategies to mitigate the impact of harmful emissions is just the tip of the iceberg for smart cities that are keen to understand the secondary effects of vehicle pollution. Interestingly, for example, the data processed by GeoSpock indicates that the temperature in Cambridge city center appears to rise at weekends – perhaps due to the presence of more people on the street, although further investigations are required.
“Some gases appear to be indicators of the presence of people and others show the presence of traffic,” GeoSpock Machine Learning Engineer Alan Roberts said.
GeoSpock is currently exploring introducing additional datasets for smart cities – such as hospital admissions for breathing problems and asthma – to add fresh layers of context to these 21st century challenges that can be tackled through the unique platform. Furthermore, there are other long-term datasets that either have already been added, or are being added to the system to investigate the quality of life experienced by the residents of cities, such as property values, crime rates and road accidents.
“By bringing in other datasets it will be possible to see the life cycles in a city and other correlations,” Roberts added.
“It will be possible for cities to look at ‘what if scenarios’, such as: What would happen if we blocked this road? Or, what impact on congestion and pollution would creating this diversion cause?
“This will create the opportunity for simulation working in the pipeline, so cities can plan ahead effectively.”
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