Governments all around the globe are using artificial intelligence (AI) to help fight against the ongoing COVID-19 pandemic. The technology is being used for various different things, including speeding up the development of testing kits and treatments, giving citizens access to real-time data, and tracking the spread of the virus.
Here are some of the different countries.
South Korea’s government, one that is being touted as an example for how to combat the virus, pushed their private sector to start developing testing kits right away, immediately after the reports began to arrive out of China.
One of those companies was Seoul-based molecular biotech company Seegene, which used AI to help quicken the process of developing testing kits. The company was able to submit its solution to the Korea Centers for Disease Control and Prevention (KCDC) just three weeks after the scientists began their work. According to Chun Jong-Yoon, founder and chief executive of the company, the process would have taken at least two to three months without the use of AI.
Since the testing kits are such a crucial part of getting the virus under control, this proves that AI technology can play a huge role in the fight.
Traditionally, the approval process for new medical equipment, including testing kits, takes around 18 months. The KCDC decided to move the process ahead and approved the tests in one week. The government’s own patient samples were able to be used for evaluation.
Telecoms firm KT has also partnered with South Korea government ministries in order to use AI-based healthcare services to track the spread of the virus.
The research project was led by the ICT Ministry and Ministry of Interior and Safety, along with universities and research institutes. KT will be responsible for providing mobile data, who can help create maps. These maps can then provide insight into how the populations are moving and the virus spreading.
Scientists in China used AI in order to speed up scientific processes. Through the use of the technology, they were able to recreate the genome sequence of the virus in a month. Comparing that to the months it took scientists to create the sequence of the SARS virus in 2003, it is a big step up.
In Taiwan, the technology has been used as well. Audrey Tang, Taiwan’s digital minister, relied on AI to develop real-time digital updates. These updates could alert citizens of certain hazardous locations, where infections had been previously detected. They were also able to use it to create a live map of local face mask supplies.
In the United States, the White House Office of Science and Technology Policy called for the development of the COVID-19 Open Research Dataset (CORD-19). This dataset is a collection of thousands of different machine-readable COVID-19 literature. There are over 44,000 scholarly articles that can be used by the research community.
“It’s all-hands on deck as we face the COVID-19 pandemic,” Microsoft’s chief scientific officer, Dr. Eric Horvitz said. “We need to come together as companies, governments, and scientists and work to bring our best technologies to bear across biomedicine, epidemiology, AI, and other sciences. The COVID-19 literature resource and challenge will stimulate efforts that can accelerate the path to solutions on COVID-19.”
While there is still a lot more that can be accomplished with artificial intelligence (AI), these are some of the current examples from around the globe. If governments are convinced by the results, the use of AI during a pandemic could become one the first defense options in the future.
Intel AI Powered Virtual Assistant Mobilized to Assist Reopening of Military Museum
A Canadian museum is safely reopening from its pandemic closure with the help of a virtual
The Ontario Regiment Museum houses North America’s largest collection of operational military vehicles, many dating back to the 1940s. The collection allows the public to experience a piece of history, both at the museum and through the historical films in which the vehicles often appear.
At the start of the pandemic in early 2020, CloudConstable began working with the museum to design Master Corporal Lana as an AI virtual assistant who would greet
Before Lana’s deployment, COVID-19 closed the museum to the public. But with over 120 military vehicles that need constant servicing and driving, the museum needed its volunteers to continue their essential maintenance and operations work at the site.
“The Ontario Regiment Museum is one of the few museums in the world with such a large and diverse collection of operating military vehicles, which help people experience history in a very real way. Regular maintenance is crucial, even during the worst of the pandemic, which is why we turned to CloudConstable and Intel to help build an autonomous solution,” said Jeremy Blowers, executive director of the Ontario Regiment Museum.
CloudConstable relied on the Intel RealSense team’s insight that Lana’s existing and unique capabilities — already built on the Intel RealSense Depth Camera and using the Intel® Distribution of OpenVINO™ toolkit for accelerated machine vision inferences — could be extended for a more comprehensive and safer COVID-19 screening solution. Adding an Intel® NUC 9 Pro with Intel Active Management Technology, as part of the Intel vPro® platform, the team reworked Lana to take temperatures via thermal scans and ask a series of questions to assess COVID-19 risk and exposure. Since June, Lana has provided an enhanced, fully automated and touchless screening process so volunteers can continue to do their important work with the vehicles.
“Intel RealSense technology is used to develop products that enrich people’s lives by enabling machines and devices to perceive the world in 3D. CloudConstable leverages Intel’s technology to help create a state-of-the-art natural voice and vision interface with touchless, self-service COVID-19 screening,” said Joel Hagberg, head of product management and marketing, Intel’s RealSense group.
With the Ontario Regiment Museum now preparing to reopen to the public, CloudConstable, along with Intel, is now working to bring the new COVID-19 protection capabilities into the original concept for Lana as a greeter for visitors. Lana will greet visitors, provide contactless check-in, scan temperatures and ensure the museum adheres to visitor limits and other COVID-19 health protection protocols. Eventually, she’ll even thank them for coming and help visitors keep in touch with all the latest activities at the museum.
U.S. National Institutes of Health Turns to AI for Fight Against COVID-19
The National Institutes of Health has turned to artificial intelligence (AI) for diagnosis, treatment, and monitoring of COVID-19 through the creation of the Medical Imaging and Data Resource Center (MIDRC).
What is the MIDRC?
The MIDRC consists of multiple institutions working together, led by the National Institute of Biomedical Imaging and Bioengineering (NIBIB), which is part of NIH. The collaboration aims to develop new technologies that will help physicians detect the virus early and create personalized therapies for patients.
Bruce J. Tromberg, Ph.D., is Director of the NIBIB.
“This program is particularly exciting because it will give us new ways to rapidly turn scientific findings into practical imaging tools that benefit COVID-19 patients,” Tromberg said. “It unites leaders in medical imaging and artificial intelligence from academia, professional societies, industry, and government to take on this important challenge.”
One of the ways experts assess the severity of a COVID-19 case is by looking at the features of infected lungs and hearts on medical images. This can also help predict how a patient will respond to treatment and improve the overall outcomes.
The big challenge surrounding this method is that it’s difficult to rapidly and accurately identify these signatures and evaluate the information, especially when there are other clinical symptoms and tests.
Machine Learning Algorithms
The MIDRC aims to develop and implement new and effective diagnostics. One of these will be machine learning algorithms, which solve some of those issues. Machine learning algorithms can help physicians optimize treatment after accurately and rapidly assessing the disease.
Guoying Liu, Ph.D., is the NIBIB scientific program lead on the new approach.
“This effort will gather a large repository of COVID-19 chest images,” Liu explained, “allowing researchers to evaluate both lung and cardiac tissue data, ask critical research questions, and develop predictive COVID-19 imagining signatures that can be delivered to healthcare providers.”
Krishna Kandarpa, M.D., Ph.D., is director of research sciences and strategic directions at NIBIB.
“This major initiative responds to the international imagining community’s expressed unmet need for a secure technological network to enable the development and ethical application of artificial intelligence to make the best medical decisions for COVID-19 patients,” Kandarpa said. “Eventually, the approaches developed could benefit other conditions as well.”
Some of the other major names on this project include Maryellen L. Giger, Ph.D., who is taking the lead. She is Professor of Radiology, Committee on Medical Physics at the University of Chicago. Co-investigators include Etta Pisano, MD, and Michael Tikin, MS, from the American College of Radiology (ACR), Curtis Langlotz, MD, Ph.D., and Adam Flanders, MD, from the Radiological Society of North America (RSNA), and Paul Kinahan, Ph.D., from the American Association of Physicists in Medicine (AAPM).
Through collaborations between the ACR, RSNA, and AAPM, the MIDRC will work toward rapid collection, analysis, and dissemination of imagining and other clinical data.
While many believe that the adoption of AI for pandemic-related solutions is long overdue, the National Institutes of Health’s new MIDRC is a step in that direction. It is only a matter of time before AI plays a major role in the detection, response, and eventual prevention of global pandemic causing viruses.
Supply Chains after Covid-19: How Autonomous Solutions are Changing the Game
Early measures by the material handling industry to curb the coronavirus pandemic saw border and plant closures all over the world. While for machine and vehicle manufacturers in eastern Europe and China production is in full swing again, the rest of Europe, North America and other western countries are struggling to get back to their pre-Covid-19 production strength.
Restrictions in freight transport across Europe are still very noticeable and are causing bottlenecks in supply chains. The strict stay-at-home-orders imposed in most European countries to contain the pandemic have had and are having a major impact on industrial production as the personnel are simply missing on site.
Security measures like keeping minimum distance or wearing masks are proving to be an organizational challenge for many production facilities around the world. In order to be able to comply with the safety requirements, in many premises only half of the workforce is allowed on-site, or the production line is divided into shifts. This in turn is restricting the flow of goods. Even when components exist, they stockpile, and cannot be integrated due to a lack of staff or time for those on reduced activity.
After the crisis, the industry will face new challenges. There is already speculation about a trend moving away from globalization towards regionalization. It is not necessarily the sourcing of production that could be affected by a possible regionalization, but rather warehouse management. Regardless of restricted supply chains, access to material inventory is essential for every production line. As a lesson-learned from the Covid-19 crisis, we could see a move from large central warehouses to smaller regional warehouses.
The automotive industry, for instance, was hit hard by supply shortages due to restrictions stemming from the pandemic. Automotive OEMs and their suppliers have long and complex supply chains with many steps in the production process. After the experienced bottlenecks, their follow-up measures might include a diversification of suppliers, as well as the decentralization of inventories in order to maintain agility in case of a crisis.
This presupposes digitalization of warehouse management: if existing stockpiling data is used rationally, transparency in the entire supply chain can easily be created. This would mean everyone involved could use existing data to optimize their processes. This requires intelligent warehouse management systems (WMS) and intelligent solutions for material handling to work hand-in-hand.
Automated guided vehicles (AGVs) are not a novelty in in-house material handling processes but their evolution could hold the key to the industry’s future. Since their introduction, technologies in autonomous vehicles have developed rapidly, enabling the transport of people in complex environments. Bringing this level of intelligence to industrial vehicles hails the next era of logistics automation: new AGV generations accessing complex outdoor environments are a real game changer and could potentially become more attractive after the Covid-19 crisis. As these vehicles become increasingly deployed in dynamic environments without infrastructure, these technologies have quickly migrated from manufacturing applications to supporting warehousing for manufacturing and distribution.
The process automation in supply chains – part of the so-called Industry 4.0 – will play a significant role. It could allow companies to keep or even reduce overall logistics operational costs, and eventually maintain a minimal operational flow even in times of crisis.
Rethinking the industrial supply chain: intelligence is key
The autonomous tow tractor TractEasy by autonomous technology leader EasyMile is a perfect example of this new generation. It masters the automation of outdoor and intralogistics processes on factory premises, logistics centers and airports. The company is currently demonstrating the maturity of these autonomous tow tractors at automotive supplier Peugeot Société Anonyme (PSA)’s manufacturing plant in Sochaux, France. Operated by GEODIS, PSA is using the tractor to find opportunities to optimize costs in the flows on its site.
The impact of the ongoing crisis has revealed the fragility of existing supply chains. Companies are reassessing large and complex procurement networks. Ultimately, the Covid -19 pandemic is putting supply chains to the test, but global supply chains should be prepared for crises as part of risk management anyway. The sheer number of natural disasters in recent years has meant that the international supply chains have been repeatedly overhauled. From this point of view, the Covid-19 crisis is an example of unpredictability that supply chains have to adapt to in order to develop.
What is certain is that the industry is on an upward trend toward more sustainable and stable industrial ecosystems. Automation is a concept that will play a major role in these future considerations, from manufacturers to logistic operators across the globe.
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