COVID-19: Odisha partners with IIT Tirupati, Facebook to analyse people's movement

Odisha Chief Minister Naveen Patnaik has announced that to analyze physical distancing in red zones and what all areas need more stringent enforcement, it has partnered with Facebook and Indian Institute of Technology (IIT) Tirupati.

Odisha Chief Minister Naveen Patnaik has announced that to analyze physical distancing in red zones and what all areas need more stringent enforcement, it has partnered with Facebook and Indian Institute of Technology (IIT) Tirupati.

In order to contain further spread of COVID-19 in the state, Odisha government has decided to analyze the movement patterns of people in coronavirus hot spots. For this purpose, it has partnered with IIT Tirupati. The team from IIT Tirupati, led by Dr. Kalidas Yeturu of Computer Science Department, used artificial intelligence (AI) to analyze Facebook datasets, also referred to as Disease Prevention Maps, available for researchers and non-profits as a part of their Data for Good Program, a media house reported.

Facebook's location feature is used to pull anonymized data from the smartphone and other devices with GPS. This data is used to generate a map that provides area-level information about the movement of the people and the distance.

These Facebook data helps in establishing near real-time mobility of people that can use to find out if anyone has breached the lockdown restrictions in particular areas of the state. This analysis will help the state administration in-turn to shape its strategic action.

“A software developed by IIT-Tirupati, GeoCov19, is being used to generate automated reports to list top 10 regions for the state administration to focus on,” Dr Kalidas, principal investigator for the project told a media house.

Apart from Facebook datasets, the IIT team also used red zone and ward-level coordinates, received from the Odisha Government, to prioritize areas.

Dr Kalidas said: “These values are computed for morning, evening, and night times. Average values of mobility are determined to prioritize regions of high mobility especially during nights.”