Y. Chen
Georgia Institute of Technology,
United States
Keywords: AI/machine learning, wastewater treatment, resource recovery, circular economy, decentralized precision agriculture, digital agriculture, hydroponics
Summary:
In response to the growing challenges of urban supply and demand mismatches, we propose a comprehensive strategy that integrates resource recovery, decentralized urban precision farming, and artificial intelligence (AI) through digitalization to enhance urban sustainability and resilience. This holistic approach addresses critical environmental issues, resource limitations, and food security concerns. AI serves as a transformative enabler, providing real-time insights and optimizing resource recovery processes to facilitate efficient resource management and promote recycling within a circular economy. In decentralized urban farming, AI-driven technologies enhance precision and productivity by optimizing resource utilization, minimizing greenhouse gas emissions, and boosting local food production—contributing to improved human well-being. Our solution emphasizes the transformative potential of this approach through detailed case studies and thorough analysis. By merging advanced AI technologies with resource recovery and urban digital farming, cities can redefine their ecological footprint and build adaptive, sustainable, and resilient ecosystems. This integrated framework lays the foundation for urban environments to thrive in harmony with nature, fostering a more sustainable future.