AI-Driven Optimization of Food Waste Recycling in Egypt: Enhancing Circular Economy Strategies through Machine Learning and Automation

The increased use of carbon fiber composite (CFC) materials in various industries has stirred environmental worries regarding their disposal, necessitating the development of efficient recycling technologies. The study explores the development of CFC recycling with Egypt as a case study to assess the opportunities and challenges of embracing sustainable waste management. Egypt's growing industrialization and commitment to sustainability highlight the need for cutting-edge recycling approaches aligned with the concepts of circular economy. The article addresses several recycling technologies including pyrolysis, catalyst-supported recovery, and biodegradation, with an emphasis on their applicability in Egypt's environmental and industrial context. It also addresses waste handling attitudes, policy, and the application of artificial intelligence (AI) and machine learning (ML) in optimizing recycling efficiency. Results indicate that while Egypt has made some progress in waste management initiatives, investment in advanced recycling facilities, policy reform, and public awareness-raising campaigns is of the highest priority. The study recommends the adoption of AI-powered waste sorting technologies, increased government-industry collaboration, and the expansion of recycled carbon fiber applications in construction, transportation, and renewable energy industries. By integrating eco-friendly recycling technologies into Egypt's economic and environmental strategies, the country will be in a position to enhance resource efficiency, prevent environmental deterioration, and contribute towards fostering global sustainability.