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March 27, 2020

Computer Vision Fighting The Coronavirus Outbreak

Author:




Kaja Grzybowska


Reading time:




5 minutes


Lately, the whole world is struggling with fighting the outbreak of the coronavirus. As the disease is exceptionally easy to transmit, the best safety measure you can take is to limit contact with any publically used surface. Here, advanced technologies like computer vision, image recognition, and processing turn out to be highly effective. Let’s take a closer look at how computer vision can help in fighting the coronavirus.

Computer Vision – Overview

What “computer vision” actually stands for? 

Computer vision (CV) is an artificial intelligence-based technology that allows computers to observe the world. By analyzing visual data, this innovation can almost perfectly understand a particular situation, and without missing any factors, find the best solutions or the most reasonable decisions.

Computer vision technology has been developing rapidly in the last few years. It was possible thanks to a reach source of its fuel – data. Nowadays, each of us generates a huge amount of data, especially visual like photos and videos, every day. It allowed CV systems to learn on it and become more and more efficient. Lately, computer vision has also explored new territory – thermal and infrared sensors.

Lately, computing power has become more affordable, which allowed computer vision to influence diverse industries. Easier access has also resulted in fast-progressing development. The algorithms which stand for computer vision reached an amazing level of accuracy in understanding what is happening around. Today’s systems are right in 99% of cases – which makes them more accurate than humans.

How AI-driven technology can help in fighting the coronavirus?

In the last month, the whole world has been struggling with the outbreak of the coronavirus. COVID-19 is exceptionally easy to transmit between humans and is extremely hard to eliminate – as movement between countries has never been that fast and accessible to anyone.

coronavirus, COVID-19

To fight the virus, the first step is to identify who transmits the disease. The most common symptoms are cough, difficulty breathing, and fever. While the first two are easily noticeable, the last one is more tricky.

Using computer vision to detect coronavirus infection

For now, the most popular way of checking the temperature at airports or border crossings is through thermometer guns. Unfortunately, this method requires human assistance (usually health officers) and is time-consuming considering the number of people who pass through those centers.

Temperature checks

Computer vision offers an efficient alternative. Specially designed algorithms can perform temperature checks on a larger scale. Cameras with built-in infrared sensors, connected to the CV system, can predict temperatures of two hundred people per minute, with accuracy within a range of 0.5 degrees Celsius. The AI-driven software automatically marks anyone with a temperature above 37.3 degrees.

This innovation has been already applied in Beijing’s Qinghe Railway Station.

CT scans

One of the most recent innovations, developed in China, is an algorithm that can diagnose patients with coronavirus from chest CT scans within 20 seconds. The accuracy turned out to be 95%. Medical centers can now gain precious time as this process used to take at least 15 minutes for healthcare professionals.

Moreover, a computer vision-based system can distinguish coronavirus from common pneumonia. In China, this new technology has been applied to many hospitals.

Mask check

Whether to wear a mask or not has been a vivid discussion in the past months. Some experts advise to wear, some undermine its effectiveness. There is only one conclusion – wearing a mask can’t hurt. Most likely it helps to prevent COVID-19 from spreading or at least puts an extra obstacle.

In some countries, like China or the Czech Republic, wearing masks in public places has become mandatory. It is a challenge though to monitor if all citizens follow the rule.

mask, woman, train

AI models using image recognition are able to detect people who don’t wear masks while being at a train station, airport, supermarket, etc. Moreover, the system is so advanced that it can also spot those who don’t wear their masks correctly.

Other computer vision-driven innovations

Besides identifying people who are sick or irresponsible, computer vision technology can support us in a few different ways. Some of the latest innovations are presented below.

To fight the pandemic, it is crucial to apply social distancing means. While it is relatively easy on the streets or even shops, the real challenge is in the hospital. Healthy people need to be separated from sick ones, as well as doctors and nurses have to avoid by all means getting infected.

Computer vision technology offers a solution – vision-guided robots. Thanks to the 3D camera and image recognition software, robots can deliver food, clean and sanitize buildings, and even navigate patients through different departments.

Outside, vision-guided drones can spread messages to people and alert them to avoid gatherings if they spot a group of people.

drones

Summary

Computer vision offers unbelievable opportunities for the future. Some innovations are already in test faze like self-driving cars or iris recognition. Both’s goal is to automate processes that usually required human assistance.

Hopefully, the world will fight the coronavirus with as few victims as possible. Computer vision technology is already supporting us in this battle. In the future, if a similar, unfortunate event takes place, we will be equipped with new tools that will make social distancing and recognizing those with a disease easier and faster.

We need to be open-minded and eager to invest in image recognition technologies, as they are helping society in countless ways. High tech companies specializing in AI software development services will play an important role in fighting the COVID-19 pandemic, as well as any other challenges the future might bring.



Category:


Computer Vision