Advances in Deep Learning Applications for Smart Cities

Smart cities of the future must aspire to accommodate increasing technology and expectations of modern living, integrated societies, knowledge-based workforce, factory automation, and virtual-real social behaviors. This complex concoction of challenges requires new thinking of the synergistic utilization of reinforcement learning methods and data-driven decision making with automation infrastructure, autonomous transportation, connected buildings, smart homes, and embedded communities.

Industrial informatics lies at this strategic intersection of multiple disciplines that can comprehensively realize a learning vision of smart cities. This book is ideal for academicians, researchers, authors, industry experts, software engineers, and students.