Case Study
Ansysは、シミュレーションエンジニアリングソフトウェアを学生に無償で提供することで、未来を拓く学生たちの助けとなることを目指しています。
Ansysは、シミュレーションエンジニアリングソフトウェアを学生に無償で提供することで、未来を拓く学生たちの助けとなることを目指しています。
Ansysは、シミュレーションエンジニアリングソフトウェアを学生に無償で提供することで、未来を拓く学生たちの助けとなることを目指しています。
Case Study
During the COVID-19 pandemic, Jorge de Jesus Alvarado-Martinez, a doctoral candidate at the Instituto Nacional de Astrofísica, Óptica, y Electrónica (INAOE) studying optical instrumentation and metrology, and some of his colleagues grew interested in the ways thermal imaging could be adapted to help with syndromic surveillance, which is the systematic collection, analysis, and interpretation of health data for the purposes of reducing exposure to infectious diseases. Syndromic surveillance helps public health officials detect, monitor, and understand health events in ways that enable timely response and intervention to protect populations from exposure.
For Alvarado and his team, improving thermal imaging technology for syndromic surveillance was a matter of finding an alternative optical design that assesses whole groups of people in a public setting, as well as speeds up the detection process by only identifying people with elevated temperatures. To meet this challenge, Alvarado’s team designed an optical system that differentiates members of a crowd based on bioclinical signals, such as cough and temperature, directly related to the physical symptoms of COVID-19.
Elevated body temperature is a key indicator of many serious infections, including COVID-19. In recent years, airports, hospitals, schools, work centers, and other public and private facilities have begun deploying thermal cameras in their waiting areas to help identify potentially infected persons so that health and security authorities can intervene and isolate them as needed. This approach, while being a step in the right direction for public health, has a few severe limitations, starting with its unsuitability for monitoring large crowds.<
> Wide-angle lenses can be used to image crowds, but for syndromic surveillance, thermal technology must be precise enough to detect which people in the image have elevated temperatures. Meanwhile, traditional thermal cameras have a long reporting delay, but in this case the data must travel fast so that infected individuals can be separated immediately from the crowd.
For Alvarado and his team, improving thermal imaging technology for syndromic surveillance was a matter of finding an alternative optical design that assesses whole groups of people in a public setting, as well as speeds up the detection process by only identifying people with elevated temperatures. To meet this challenge, Alvarado’s team designed an optical system that differentiates members of a crowd based on bioclinical signals, such as cough and temperature, directly related to the physical symptoms of COVID-19.
Off-axis mirrors were ideal for this solution because they eliminate obscuration in the light path while reducing alignment complexity by providing a wide field of vision (FOV) with no intermediate image required. Using mirrors also helps reduce materials cost during manufacturing.
The team started their design with a coaxial system, then introduced decentered parameters to remove obscuration and tilting parameters to move the system off-axis. The resulting system achieves the team’s aim of more effectively and efficiently reporting on discrete anomalies within a wide-angle thermal image using only off-axis mirrors.
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