Computational Intelligence Techniques for Green Smart Cities

Recent trends of  Artificial Intelligence Techniques.- An Overview of Smart Green Cities Based on XAI
Machine Learning for Green Smart Health.- Deep Learning Models for Green Smart Health.- On natural language processing to attack COVID-19 pandemic.- Evolutionary Algorithms for Smart Green Transportation.- Analysis and design of the Bus Transport Network.- Traffic sign detection system for Smart City Transportation.- Green Smart Transportation solutions for combating Covid-19.- The Utilization of Forecasting Methods of Solar Radiation.- Machine learning for Green Smart Environment.- Deep learning for green smart environment.- Machine Learning & Fuzzy Technique for Environmental Time Series.- A new Fuzzy Clustering Algorithm based on Maximum Likelihood Estimation.- Optimal Environmental-Economic Scheduling of a smart home.- Smart Home Application based on Evolutionary Algorithm: a Transfer Learning Approach.- Machine learning for Green Home.- Machine learning for green smart video surveillance.- Green Learning Solutions for Human Trafficking Victims in Rural Communities During the COVID-19.- A comparative analysis on object detection accuracy of cloud-based image processing services.

Mohamed Lahby is an Associate Professor at the Higher Normal School (ENS) University Hassan II of Casablanca, Morocco. His PhD in Computer Science from the Faculty of Sciences and Technology of Mohammedia, University Hassan II of Casablanca, in 2013. His research interests are wireless communication and network, mobility management, QoS/QoE, Internet of things, Smart cities, Optimization and Machine learning. He has published more than 35 papers (book chapters, international journals, and conferences), 3 edited books, and 2 authored books. He has served and continues to serve on executive and technical program committees of numerous international conferences such as IEEE PIMRC, ICC, NTMS, IWCMC, WINCOM, ISNCC. He also serves as a referee of many prestigious Elsevier journals : Ad Hoc Networks, Applied Computing and Informatics and International journal of disaster risk reduction. He organized and participated in more than 40 conferences and workshops. He is the chair of manyinternational workshops and special sessions such as MLNGSN'19, CSPSC'19, MLNGSN'20, AI2SC '20, WCTCP'20, CIOT'2022.

Ala Al-Fuqaha is a professor at the Computer Science department, Hamad Bin Khalifa University, Qatar. His research interests include the use of machine learning in general and deep learning in particular in support of the data-driven and self-driven management of large-scale deployments of Internet of Things and smart city infrastructure and services, Wireless Vehicular Networks, cooperation and spectrum access etiquette in cognitive radio networks, and management and planning of software defined networks. He is a senior member of the IEEE and an ABET commissioner. He serves on editorial boards of multiple journals including IEEE Communications Letter, IEEE Network Magazine, and Springer AJSE. He also served as chair, co-chair, and technical program committee member of multiple international conferences including IEEE VTC, IEEE Globecom, IEEE ICC, and