SCOPE:

In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, healthcare, education, environment, security, etc., thanks to these technological advances Although there are important smart services deployed in cities worldwide and advanced technologies to develop these services, cities are encountering so many challenges linked directly with the environment. Indeed, most of these solutions were conducted without considering some information related to the environment. The green city paradigm becomes a necessity to overcome these limitations. The key objective of this paradigm is promoting a sustainable and livable city to the citizens. This goal can't be achieved without considering three essential elements: reducing energy consumption, improving the quality of citizens' daily life, and making citizens active and proactive actors of green smart city solutions. Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects. This book will comprise many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.

TOPICS:

• Green Smart Education

• Machine learning for green smart education

• Deep learning for green smart education

• Evolutionary algorithms for green smart education

• Green Smart learning solutions for combating Covid-19

• Green Smart Health

• Machine learning for green smart health

• Deep learning for green smart health

• Evolutionary algorithms for green smart health

• Green smart health solutions for combating Covid-19

• Green Smart transportation

• Machine learning for green smart transportation

• Deep learning for green smart transportation

• Evolutionary algorithms for green smart transportation

• Green smart transportation solutions for combating Covid-19

• Green Smart Environment

• Machine learning for green smart environment

• Deep learning for green smart environment

• Evolutionary algorithms for green smart environment

• Green smart environment solutions for combating Covid-19

• Green for Smart Home

• Machine learning for green smart home

• Deep learning for green smart home

• Evolutionary algorithms for green smart home

• Green smart home solutions for combating Covid-19