The Odysseus project’s overall goal is to help manage the Covid-19 crisis, inform the return to normality, and act as a springboard to London’s economy in the long term.
Researchers from the Alan Turing Institute in partnership with Lloyd’s Register Foundation (LRF) have been mobilised to provide crucial insights to help London authorities during lockdown and support planning for the future after Covid-19 lockdown.
The remit of the project, codenamed ‘Odysseus’, falls under the themes which help to understand “London’s busyness”, and how positively the public are responding to interventions. London is regarded as a “particularly complex and varied environment”, in which to understand how the pandemic has affected people’s lives and how they are responding to it.
The project’s overall goal is to help manage the crisis, inform the return to normality, and act as a springboard to London’s economy in the long-term.
The institute was already working on a collaboration with the Greater London Authority (GLA) and Transport for London (TfL) through the Data-centric Engineering programme, funded by LRF.
Now, working alongside a team of researchers from the universities of Warwick, Cambridge, and UCL, the team has repurposed their existing models, infrastructure, and machine learning algorithms from the air quality work, shifting focus and deploying similar techniques to understand how and when ‘busyness’ is changing across the UK capital in the wider context of Covid-19. Microsoft is a key partner, bringing Azure Cloud and AI services, and expertise, to the project.
Outputs from this research are already providing insights to the GLA’s Strategic Coordination Group (SCG) and Public Health England.
“The data, algorithms, and outputs from our research have the potential to act as an early warning system to trigger different interventions and more targeted policies.”
According to the partners, there has been a significant amount of anecdotal information about how busy parts of London have been during lockdown. The aim of this work is to provide a more consistent picture of behaviour to deliver:
The project is founded on detailed data privacy and ethical protections, with much of the data already in the public domain and other data just looking at high level patterns and trends. Researchers are also using their expertise in detecting “change points” (revealing where and when changes are occurring) and integrating the evidence from a range of heterogeneous data sources to build an intricate and granular model of activity.
“The data, algorithms, and outputs from our research have the potential to act as an early warning system to trigger different interventions and more targeted policies. They can shed light into how the transmission of the virus is driven by human mobility, social interaction and social distancing across the city,” said Theo Damoulas, deputy programme director for the Turing’s Data-centric Engineering programme, and Turing’s lead on this project.
“We are delighted to be collaborating with our university partners, the GLA, TfL and others to provide valuable real-time insights to support planning for London’s managed emergence from the pandemic.”
The research uses open data to help explore information gathered from vehicle and transport movements, traffic cameras, economic activity and data from running apps.
“Bringing together open data gives us another tool to understand how the capital is responding to public health measures.”
The team is also collaborating with London First and the London Data Commission to understand how businesses themselves might use the busyness data to inform their recovery planning.
“City Hall has been doing important work with the Turing on air quality and this is now being repurposed to help deepen our understanding of Londoners’ movements during the lockdown,” added Theo Blackwell, London’s chief digital officer.
“Bringing together open data gives us another tool to understand how the capital is responding to public health measures, as well as how our high streets and shopping centres are doing, as we move from restrictions to recovery.”
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