Infrared sensors have a long history, going back to the discovery of infrared radiation in 1800. In 1830, Leopoldo Nobili built the first thermopile, a device to detect infrared radiation and convert it into an electrical signal.
It wasn’t until the 1930s that a lead sulphide IR detector was created for military use and more advanced versions followed in the 1940s.
Today, IR sensors are used in myriad applications to detect motion for use in communications, security and energy and temperature in industrial settings. They usually work by emitting infrared light and detecting the reflection of that light to sense an object’s presence or even to measure its heat signature. They can be used in air conditioners, in just one example, to detect heat emitted from people in a room.
IR sensors have traditionally been held back by high cost because the sensors are elaborate and rely on uncooled or cooled focal plane arrays-- much more expensive than sensors found in a standard camera. High speed sensors can go for more than $6,000 for use in scientific or industrial settings, according to analysts, but a typical motion detector that is wireless might run $40 to $100.
One startup founded in 2013, Stratio Inc., has staked a claim as being able to lower that cost by one-hundredth by commercializing germanium-based short wavelength infrared (SWIR) sensors using a standard CMOS process. (CMOS is a Complementary Metal Oxide Semiconductor, a field effect transistor.) Statio’s sensors are marketed as highly sensitive, mass-producible and allow for AI-integration—what’s become the table stakes for modern sensors.
Its sensors have been incorporated in products such as the LinkSquare smart handheld spectrometer, making it useful in checking food freshness or even plastic sorting in a recycling process. Also, BeyonSense is a germanium-based SWIR camera buit on Stratio’s CMOS-compatible platform for high resolution infrared imaging. It offers potential for autonomous vehicles and consumer electronics.
Stratio also operates an in-house nanofabrication facility, STNF, opened in 2020 in Silicon Valley to prototype sensor devices, and Stratio keeps headquarters out of both San Jose, CA, and Pangyo, near Seoul in South Korea. It was founded by three PhD graduates from Stanford University, including CEO Jaehyung James Lee, who recently described a vision for a Stratio strategy to integrate infrared data with AI, speaking at the 2025 Pangyo Global Media Meet-up organized by a business and science accelerator.
The company is building an “Infrared AI” domain to combine unique spectral data collected by its sensors with AI algorithms. In the recycling sector, its technology can accurately distinguish black plastics and composite materials that conventional AI cannot identify, which will help break the limits of resource-recycling technologies. The technology is being applied to agriculture, food, consumer electronics, robotics and healthcare to measure such things as crop growth conditions, sugar and moisture levels and to analyze fabrics and skin. “By integrating AI-based analytical capabilities into products that previously relied on traditional equipment and software, Stratio enhances product value across industries,” the company said in a statement.
A company representative told Aving news network that infrared tech is becoming a “core tool for decoding unseen layers of industries. Based on our development capabilities and global customer network built in Pangyo, we will continue supporting the AI transformation of all industries.” On LinkedIn, the company added, “By combining sensors, spectral data and AI, we are showing how infrared technology can unlock unseen insights and drive innovation across industries worldwide.”
Stratio said in a press release Nov. 10 it is actively pursuing global expansion with pilot programs in Vancouver, Canada, and Seongnam City, collaborating with global textile recycling firms on a proof of concept program. The company is in Series B funding and is developing a 1.3 MP high-res multispectral camera, aiming to expand infrared AI into autonomous driving, security and medical applications.