Dr. Anang Amin

Assistant Professor, Higher Colleges of Technology

“I am honoured to receive this prestigious grant from Dubai Future Foundation, supporting our research on AI-enabled digital-twin technology for solar-powered atmospheric water harvesting. This project presents an exciting opportunity to drive sustainable water solutions through innovation and advanced technology. I am eager to contribute to shaping a future where clean and reliable water is accessible to all.”

Water scarcity has become one of the most pressing global challenges due to factors such as climate change, urbanization, and rapid population growth. Conventional sources, including groundwater extraction and surface water collection, are becoming increasingly strained, leading to significant environmental impacts. Atmospheric Water Harvesting (AWH), which directly captures water vapor from the air, has emerged as a promising alternative. This project aims to develop an innovative, AI-enabled, solar-powered AWH system that efficiently captures and condenses water from the atmosphere. By integrating advanced Metal-Organic Frameworks (MOFs) for high-efficiency water adsorption, thermoelectric coolers (TECs) for energy-efficient condensation, AI-driven control systems for real-time optimization, and digital twin implementation for predictive maintenance, this project addresses key limitations of conventional AWH technologies. MOFs are particularly effective sorbents for AWH due to their high surface area, tunable pore structures, and ability to capture moisture even at low humidity levels. TECs leverage the Peltier effect to create temperature gradients, which can drive condensation at a much lower energy cost as compared to traditional cooling systems. The integration of renewable energy sources such as solar power further enhances the feasibility of AWH systems. Solar energy can sustain both the TECs and the heating requirements for MOF regeneration, offering a self-sustaining and environmentally friendly water harvesting approach. The system is designed to operate effectively in low-humidity environments, making it particularly suitable for arid and semi-arid regions where water scarcity is a significant challenge. AI-driven control with digital twin infrastructure dynamically adjusts system parameters based on environmental data, ensuring maximum efficiency and adaptability. The project is set to impact water harvesting technology by delivering a scalable, energy-efficient solution for water production, benefiting both urban and remote areas. Commercialization could drive new partnerships and investments in sustainable water management, promoting economic stability, public health, and global sustainability goals.