Thousands of Public Cameras Used to Analyze Changes in Actual Social Distancing

Purdue University engineers have a built a website ( ) that gathers live video and images from about 30,000 network cameras in more than 100 countries and they are using the system to monitor and analyze COVID-19 social distancing.

The system automatically discovers thousands of network cameras in public spaces. After the system discovers cameras, a computer program saves image data and downloads videos about every 10 minutes. Data recorded from these cameras are sent to cloud data centers for processing.

The discovered cameras are a subset of a much larger system developed in Lu’s lab in 2016, called the Continuous Analysis of Many CAMeras (CAM2). The CAM2 system is the world’s largest camera network, accessing more than 120,000 cameras worldwide in settings ranging from public parking garages to highways.

The cameras that Lu’s lab has discovered for studying the effects of COVID-19 restrictions focus on places typically dominated by pedestrians.

Lu and his collaborators have been using the system and artificial intelligence tools to see how policies have affected crowd size over time. The data also is helping to build models for human interactions and the spread of disease.

Arxiv – Observing Responses to the COVID-19 Pandemic
using Worldwide Network Cameras

They observed a dramatic decrease in the number of people on the streets in most countries around the world from Spring 2019 and earlier, to Spring 2020. They will continue observing what may happen in these locations over time after social distancing policies are lifted.

SOURCES – Purdue University
Written By Brian Wang,