Applied AI transforms the design, management, and optimization of sustainable and intelligent systems across industries. By integrating advanced data analytics, machine learning, and automation, applied AI enables more efficient use of resources, reduces environmental impact, and supports smarter decision-making in areas like energy, transportation, agriculture, and urban development. These systems can adapt to dynamic conditions in real time while predicting future challenges, effectively addressing global sustainability goals. As the demand for eco-friendly solutions grows, applied AI stands at the forefront of innovation, bridging the gap between technological advancement and environmental responsibility. Applied AI for Sustainable and Intelligent Systems explores how applied AI techniques can be used to design and optimize systems that are intelligent and environmentally sustainable. It examines the role of data-driven models, automation, and predictive analytics in improving efficiency, reducing resource consumption, and supporting long-term ecological and economic resilience. This book covers topics such as data science, cybersecurity, and sustainable development, and is a useful resource for business owners, engineers, academicians, researchers, and scientists.
