The coronavirus pandemic quickly overwhelmed the healthcare infrastructure of countries around the world. In the United States, for instance, the situation was exacerbated by the initial release of faulty test kits, which subsequently resulted in an inability to accurately screen potential patients for the disease.
However, there were also missed opportunities to pre-screen potential coronavirus carriers at ports of entry. Rather than surveying unsuspecting carriers about their recent travels, authorities like the Transportation Security Administration could have benefited greatly from the use of AI-enabled computer vision technologies capable of detecting symptoms associated with COVID-19 – such as fevers and abnormal respiratory patterns – with high precision and in real time.
Industrial GPU computers are now available with the performance and expandability to execute these neural network algorithms at the edge, enabling large-scale, contactless screening that will help mitigate the spread of coronavirus and other potentially-lethal infectious diseases.
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TAIWAN: A CASE STUDY IN DISEASE PREVENTION AND MITIGATION
Despite its proximity to the epicenter of the coronavirus outbreak, as of March 30th Taiwan has reported fewer than 300 cases of the coronavirus and just two deaths. The country’s ability to curb the spread of the disease is attributed to measures put in place after the SARS epidemic, which include the use of temperature monitoring in airports to screen travelers for fever.
Of course, using airport or medical workers to physically take the temperature of each individual passenger in these high-density environments is unrealistic if not dangerous. First, it would provide a platform for exponential transmission of contagions between passengers and healthcare staff, especially given the shortage of protective surgical masks and gloves. Second, it would lead to bottlenecks that have recently resulted in seven-hour wait times at U.S. airports.
Instead, major airports in Taiwan use high-resolution thermal cameras and deep learning. Once the cameras capture infrared images of passengers, the imaging data is passed into systems like the Premio VCO-6020-1050TI or VCO-6022C-2PWR industrial GPU computers. Captured pixels are then processed by on-chip Intel® or NVIDIA® graphics engines, while multicore CPUs execute computer vision algorithms.