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Understanding London's busyness during COVID-19.

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Theo Damoulas Deputy Programme Director for Data-Centric Engineering and Turin AI Fellow, the Alan Turing Institute

By showing how people are behaving, we can help London return to normal, post-lockdown.

An empty street in the City of London, London.

Project Odysseus

COVID-19 has changed the way we all live, with society challenged as never before. A return to something approaching ‘normal’ life – whatever that may look like – will depend on government and local leaders understanding precisely how people are behaving under lockdown or other restrictions.

A woman wearing a face mask in a London tube station.

The Lloyd’s Register Foundation Data Centric Engineering Programme at The Alan Turing Institute was already exploring how data from mobile networks and traffic cameras could be brought together to model and understand air pollution in London. But the onset of the pandemic prompted a swift change of direction. “We knew we could reimagine our data sources as a busyness sensor for London,” says Theo Damoulas. “So we talked to our partners and offered to help, with the support of Lloyd’s Register Foundation. Together, we came up with a plan to learn how people’s behaviours change as policy evolves – and Project Odysseus was born.”

In addition to organisations such as the Greater London Authority, Transport for London and the Office for National Statistics, the project’s findings feed directly into Public Health England and, ultimately, the UK Government.

“Data centric engineering facilitates machine-assisted human decision making,” comments Theo. “Project Odysseus enables the Government and others to understand the public’s response to policy decisions and to tweak actions accordingly, so that London – and ultimately many other cities – can exit this pandemic in a safer way.”

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