DRESDEN / Germany, 20 January 2026: A Fraunhofer-led research initiative is developing a compact, energy-efficient hyperspectral camera that could significantly expand the use of advanced imaging across industrial and agricultural applications, according to project officials.
The innovation is part of the OASYS project, which focuses on optoelectronic sensor systems for application-driven use cases. Within subproject A1, researchers and industry partners are engineering an ultra-compact hyperspectral camera that integrates artificial intelligence (AI) to conduct real-time material and quality analysis. Unlike conventional cameras, the device captures spectral information that reveals chemical properties invisible to the human eye, enabling rapid detection of defects and material composition.
The system operates through a hybrid approach that combines traditional 2D imaging with AI-powered spectral analysis. First, a standard high-resolution camera captures a conventional image of the object. AI algorithms then analyse the image in real time to identify specific regions of interest. The integrated spectrometer subsequently conducts spectral measurements only at these targeted locations, rather than scanning the entire image.
Project leaders say this selective measurement approach dramatically improves efficiency. By limiting spectral analysis to relevant points, the system reduces data volumes, lowers energy consumption and shortens processing times compared with traditional hyperspectral imaging methods, which are computationally intensive.
The technology has wide-ranging applications across multiple sectors. In recycling and manufacturing, it can reliably sort textiles and plastics based on chemical composition, improving material recovery rates. In brand protection, it supports more accurate detection of counterfeit products. For food processors, the camera can identify pressure marks, contamination and quality defects in real time, strengthening quality assurance processes.
In agriculture, the device enables precise assessment of plant health and nutrient requirements, supporting data-driven decisions in crop management. Automated evaluation allows farmers and agribusiness operators to respond faster to crop stress and optimize input usage, enhancing sustainability and productivity.
“With the compact hyperspectral camera from OASYS A1, we are developing technology that can be used directly in production lines, sorting facilities or in the field,” said Heinrich Engelke, project manager at Fraunhofer Institute for Photonic Microsystems IPMS. “The combination of miniaturisation, energy efficiency and artificial intelligence opens up completely new applications.”
Engelke added that the technology also contributes to resource conservation and process reliability. Components developed under the project are expected to form the foundation for next-generation sensor systems across industry, recycling, agriculture and food processing.
Market observers note that the innovation aligns with growing demand for smart sensors and AI-driven automation, positioning hyperspectral imaging for broader commercial deployment beyond research environments.
By Jagdish Kumar