People detection and social distancing classification in smart cities for COVID-19 by using thermal images and deep learning algorithms

TL;DR

This paper presents an AI system using thermal images and deep learning to detect people, monitor social distancing, and measure body temperature, aiming to reduce COVID-19 spread in smart city environments.

Contribution

It introduces a novel integration of YOLOv2-based detection with thermal imaging for real-time social distancing and temperature monitoring in indoor and outdoor settings.

Findings

High accuracy in detecting and tracking people in thermal images

Effective classification of social distancing compliance

Potential for deployment in smart city surveillance systems

Abstract

COVID-19 is a disease caused by severe respiratory syndrome coronavirus. It was identified in December 2019 in Wuhan, China. It has resulted in an ongoing pandemic that caused infected cases including some deaths. Coronavirus is primarily spread between people during close contact. Motivating to this notion, this research proposes an artificial intelligence system for social distancing classification of persons by using thermal images. By exploiting YOLOv2 (you look at once), a deep learning detection technique is developed for detecting and tracking people in indoor and outdoor scenarios. An algorithm is also implemented for measuring and classifying the distance between persons and automatically check if social distancing rules are respected or not. Hence, this work aims at minimizing the spread of the COVID-19 virus by evaluating if and how persons comply with social distancing rules. The proposed approach is applied to images acquired through thermal cameras, to establish a complete AI system for people tracking, social distancing classification, and body temperature monitoring. The training phase is done with two datasets captured from different thermal cameras. Ground Truth Labeler app is used for labeling the persons in the images. The achieved results show that the proposed method is suitable for the creation of a smart surveillance system in smart cities for people detection, social distancing classification, and body temperature analysis.