AI and Machine Learning in Optoelectronics for Global Sustainability

Abstract

Abstract—The integration of Artificial Intelligence (AI) and Machine Learning (ML) into optoelectronics presents transfor- mative opportunities to address global sustainability challenges. Optoelectronic systems, with their capability to harness light- matter interactions for sensing, communication, and energy applications, are critical to sustainable technologies. This paper explores how AI and ML techniques can optimize the design, operation, and performance of optoelectronic devices, fostering advancements in energy efficiency, renewable energy harvesting, environmental monitoring, and smart cities. By leveraging AI- driven models for enhanced material discovery, adaptive system control, and predictive maintenance, this study underscores the potential to minimize energy consumption and resource wastage. Furthermore, we discuss AI-empowered applications in ocean optics and photonics, highlighting their role in monitoring marine ecosystems and combating climate change. The paper concludes by identifying key challenges and proposing future directions for research at the intersection of AI, ML, and optoelectronics to ensure a sustainable and resilient future.