Recycling and sorting are essential processes in managing waste and promoting a circular economy, where materials are reused and repurposed rather than discarded. Photonic technologies are increasingly playing a transformative role in these processes by enabling rapid, precise, and non-invasive identification of materials in complex waste streams. They offer scalable, smart, and environmentally friendly solutions that are essential to modernizing the recycling industry and achieving European Green Deal objectives. Techniques such as hyperspectral imaging, laser-induced breakdown spectroscopy (LIBS), near-infrared (NIR) spectroscopy, and Raman spectroscopy allow for the real-time detection and classification of a wide variety of materials, including plastics, metals, glass, and composites. or detection of hazardous contaminants in e-waste. Integrated into automated sorting systems with machine learning and robotic handling, photonic sensors significantly reduce human labor, improve throughput, and lower contamination rates.
In this online meeting, we will bring the whole supply chain to the room, and we will discover the latest developments in this field and the remaining challenges to be solved to ensure the efficient operation of the recycling and sorting systems.
Studied ICT engineering, IA master degree and Industry 4.0, working in Picvisa for about 6 years as product developer, also done classes of master degree in university as a teacher.
Lars Gidskehaug (PhD) has over 15 years of experience working with spectroscopy-based industrial solutions. He previously held roles at a leading software company before joining HySpex, NEO in 2024, where he now serves as Industrial Solutions Manager. In this role, he works closely with partners and end-users across different industries to develop value-adding, turnkey solutions based on hyperspectral imaging technology.
Pedro Jorge is Assistant Professor at the University of Porto and Senior Researcher at INESC TEC. He develops LIBS, hyperspectral imaging and optical sensing solutions for industrial analytics, sorting and process monitoring.
