Imagine giving a machine eyes that can see things humans can't, like the exact health of a grape leaf or a tiny tumor during surgery. This project builds special light-sensing chips and pairs them with a smart brain that learns to recognize patterns. It's like upgrading a standard camera to a super-sensor that understands the chemistry and depth of everything it looks at.
Current high-precision sensors are often too expensive or bulky for wide use in surgery, driving, and farming. There is a gap between raw sensor hardware and the AI needed to make sense of the data in real-time.
A PIC-based LIDAR system and spectral imagers (CMOS, InGaAs, QD) paired with a cloud-edge ML platform for data labeling and model training.
If you are a surgical equipment manufacturer dealing with the difficulty of identifying cancerous tissue in real-time — this project developed spectral imagers that enable tumorous cell identification and blood perfusion monitoring.
If you are an autonomous vehicle OEM dealing with collision risks in complex environments — this project developed a PIC-based LIDAR solution that improves advanced ADAS vehicle collision detection systems.
If you are a precision farming tech provider dealing with crop disease and water waste — this project developed snapshot spectral imagers that manage hydric status and predict pathogen infections in viticulture.
The project focuses on creating cost-efficient CMOS, InGaAs, and QD spectral imagers to make these high-end sensing solutions more affordable for industrial use.
Based on available project data, the project aims for scalable and adaptable solutions by using photonic integrated circuits (PIC) and a cloud-edge platform for deployment.
Based on available project data, the consortium includes 15 partners across 7 countries, but specific licensing terms are not provided in the report.
The project uses a digital infrastructure for ML-based perception algorithms that works with a cloud-edge platform for efficient processing.
The project period runs from 2023-12-01 to 2027-11-30, with the first 18 months focused on specifications and initial fabrication.
The consortium is heavily weighted toward commercialization, with a 53% industry ratio consisting of 8 industrial partners and 9 SMEs. This strong private-sector presence, combined with 5 research-focused entities across 7 countries, suggests a high priority on transferring the photonic hardware from the lab to real-world operational environments.
Contact ASOCIACION DE INVESTIGACION METALURGICA DEL NOROESTE in Spain
Contact us to connect with the RETINA consortium for early adoption of PIC-LIDAR technology.
