Augmented PhOtovoltaic ceLLs-based Optical Neural networks for environmental monitoring

APOLLON aims to develop a novel solar-cell-based optical neural network (ONN) designed for real-time, energy-efficient environmental monitoring and object recognition. By leveraging solar cells as both sensors and network nodes, the ONN eliminates the need for conventional cameras and external power sources, significantly reducing energy consumption and system complexity. The integration of metasurfaces enhances the system’s optical sensitivity and spectral selectivity, enabling more accurate detection and classification of objects based on light patterns and colours. This innovative approach allows for scalable, self-powered sensor networks capable of continuous operation in remote and hard-to-reach locations. By addressing the challenges of energy consumption, scalability, and real-time data processing, this project aims to deliver a transformative solution that meets the growing demand for sustainable, cost-effective environmental monitoring and establishes a foundation for future commercialization and global deployment.