Deep learning algorithms to be used to measure social distancing
Many countries have introduced social distancing measures to slow the spread of the COVID-19 pandemic. To understand if these recommendations are effective, we need to assess how far they are being followed.
To assist with this, our team has developed an urban data dashboard to help understand the impact of social distancing measures on people and vehicle movement within a metropolitan city in real time.
The Newcastle University Urban Observatory was established to better understand the dynamics of movement in a city. It makes use of thousands of sensors and data sharing agreements to monitor movement around the city, from traffic and pedestrian flow to congestion, car park occupancy and bus GPS trackers. It also monitors energy consumption, air quality, climate and many other variables.
Changing movement
We have analyzed over 1.8 billion individual pieces of observational data, as well as other data sources, with deep learning algorithms. These inform and update the dashboard in real time.