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The mix of IoT and AI is being used by tech enthused agencies for curbing the rise of coronavirus cases, and flattening the curve. Read all about it here.

By the time you finish reading this article, the number of new coronavirus cases would have increased in tens of thousands.

While the world has slowly started to live and adapt in this environment as a new norm, scientists and tech enthusiasts around the globe have not settled down. They are constantly finding new ways to curb the COVID-19 rise. One of the ways they have been working is the adoption of technologies – to be more precise, AI and IoT technology.

Let’s look into how these two technologies are bringing the world closer to a time where we will have a better control of the situation.

How is AI Fighting Against the Pandemic?

The role of AI in healthcare is far-reaching and has already validated its potential. But a slightly new use case is the inclusion of AI in the fight against the coronavirus pandemic. Here are some of the ways AI is curbing the rise.

Throwing Light on the COVID-19 Structure

DeepMind – Alphabet’s AI domain – has been using data from genomes for predicting organisms’ protein structure. This is known to shed some light on which drugs would work against coronavirus.

They have released AlphaFold, a deep learning library that use neural networks for predicting how the proteins that make organisms crinkle or curve on the basis of their genome. These protein structures also help with determining the receptor shape in the organism’s cells. Once we know the receptor shape, it becomes possible to work on the drugs that could bind to them and then disrupt the vital processes inside the cells. In case of coronavirus, it can help in disrupting how the virus binds to the human cells, or can even help with slowing down its reproduction rate.

Detection of the Outbreak and Rise of New Diseases

Artificial-intelligence models are known to be the first systems to have detected the COVID-19 outbreak. AI was able to make the deduction back when the virus was only restricted to Wuhan, and was not even global.

It’s believed that the AI-driven HealthMap that is working in the Boston Children’s Hospital first picked on the rising clusters of strange pneumonia cases very shortly before the human researchers.

The data since then has been made available to the public, and for combing through by researchers and scientists who are looking for links between the virus and specific populations, in addition to containment measures. Data has also been mixed with information about human movements to analyze how mobility and control measures affected the virus spread in China.

HealthMap ever since has been tracking the coronavirus spread, while visualizing it across the world according to location and time.

Forecast how the Cases and Deaths Spread Across Cities

A Google-owned machine-learning community, Kaggle has been setting up a number of coronavirus challenges for its members, including a forecast of cases and deaths by city, and a mode for identifying why some places are more heavily hit than others.

“The goal here isn’t to build another epidemiological model… there are lots of good epidemiological models out there. Actually, the reason we have launched this challenge is to encourage our community to play with the data and try and pick apart the factors that are driving difference in transmission rates across cities,” Kaggle’s CEO Anthony Goldbloom told in the Stanford conference.

Presently, Kaggle is working with a dataset of 163 countries’ infection rates within the past several months for developing models and predicting the spread. The majority of these models are producing feature-rich plots for showcasing the elements that may be leading the difference in fatalities and cases.

What is the Role of IoT in Curbing the Rise of COVID-19?

Like AI, the use cases of IoT in healthcare have also now come out of their shells and have been playing an active role in slowing the pandemic.

Here’s how.

Dissecting the Outbreak

With a number of diverse datasets being collected on mobile devices, the Internet of Things can play alongside a number of applications during this pandemic.

IoT technology can be used for tracing the outbreak origin. During the Singapore 2013 and 2014 dengue fever spread, a MIT research study demonstrated this concept by using aggregated phone data for tracing granular details along short periods and distances. By overlaying the GIS (geographic information system) on the IoT mobile data from the infected patients, two important things could be accomplished:

  • Assisting the epidemiologists with the search for patient zero
  • Identifying the people who came in contact with the infected person, and in turn may have been infected

Ensuring Quarantine Compliance

IoT technology can be proven useful for ensuring that a patient meets quarantine compliance, and a public health department can track which patients have remained quarantined as well as those who broke the rules. It would, in turn, help them with tracking who else might have been infected because of a breach.

Managing Patient Care

The scalability functionality present in IoT comes in very handy when you have to monitor the high-risk patients who should be in quarantine, but not necessarily in hospital care.

With the help of IoT and advancements in telemedicine, patients will be able to take their temperature and upload data from their mobile devices to the cloud for analysing. The healthcare workers, this way, could not only collect data in less time than when meeting in-person, but also lower the probability of cross-infection among their patients.

Now that we have looked into the applications of IoT and AI in fighting coronavirus rise, it is time to make the coronavirus impact on healthcare sector minimal.

By Bhupinder Kour