Applied AI for Sustainable and Intelligent Systems

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.

Toufik Mzili is a distinguished Assistant Professor in Computer Science at the Faculty of Sciences, Chouaib Doukkali University, Morocco. With a robust academic and professional background, Dr. Mzili has established himself as an expert in the fields of combinatorial optimization, metaheuristics, artificial intelligence, and data science. His contributions to both theoretical and applied research have significantly impacted these domains, earning him recognition at national and international levels. Dr. Mzili completed his Doctorate in Computer Science (2020–2023) at the Faculty of Sciences, Chouaib Doukkali University, where he specialized in combinatorial optimization and metaheuristic algorithms. Prior to this, he earned his Master’s degree in Computer Science from the National School of Applied Sciences (ENSA) in Safi, Cadi Ayyad University (2017–2020), and his Bachelor’s degree in Mathematics and Computer Science from the Faculty of Sciences, Chouaib Doukkali University (2014–2017). His early education culminated with a high school diploma in Mathematical Sciences, which laid the foundation for his subsequent achievements in academia and industry. As an educator, Dr. Mzili has extensive teaching experience spanning various levels of higher education. He currently teaches courses such as “Machine Learning and Data Mining,” “Web Programming,” “Programming in C Language,” and “Semantic Web” to undergraduate and graduate students across multiple institutions, including the Higher Institute of Engineering & Business (ISGA), the Faculty of Sciences, El Jadida, and the National School of Applied Sciences (ENSAJ). His pedagogical approach emphasizes practical application and innovation, preparing students for real-world challenges in computer science and related disciplines. In addition to his teaching responsibilities, Dr. Mzili actively contributes to the scientific community through editorial roles, conference organization, and peer review activities. He serves as an Associate Editor for prestigious journals such as PloSOne (SCIE, Q1) and Computers, Materials & Continua (SCIE, Q2), and acts as Editor-in-Chief for the Journal of Optimization and Artificial Intelligence . Furthermore, he has guest-edited special issues for renowned publications, including International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Springer, SCIE, Q3) and Statistics, Optimization & Information Computing (Scopus, Q3). As a testament to his commitment to advancing knowledge, Dr. Mzili has also edited several books published by IGI Global and CRC Press, focusing on topics like machine learning, artificial intelligence, and sustainable development. Dr. Mzili's research portfolio reflects his dedication to solving complex problems using cutting-edge methodologies. His work primarily revolves around optimization techniques, metaheuristic algorithms, and their applications in diverse fields such as logistics, healthcare, and urban planning. Notable publications include groundbreaking studies on hybrid genetic and penguin search optimization algorithms, discrete rat swarm optimization for quadratic assignment problems, and innovative approaches to production scheduling and traffic control. These contributions have been featured in top-tier journals, including FACTA UNIVERSITATIS Series: Mechanical Engineering (Q1, IF=10.1), Informatics in Medicine Unlocked (Elsevier, Q1), and Decision Making: Applications in Management and Engineering (Q1). Professionally, Dr. Mzili brings valuable industry experience to his academic pursuits. From 2020 to 2023, he worked as a Software Engineer and Coordinator at the General Secretariat of the Ministry of Health and Social Protection in Rabat, where he designed and implemented web and mobile applications tailored to meet specific ministry needs. Earlier in his career, he contributed to projects involving document dematerialization systems and business process management for clients in the tourism sector while working as an IT consultant at Kertys Maroc. This blend of theoretical expertise and practical application enriches his teaching and research endeavors.

Zahra Oughannou an Assistant Professor at Ibn Zohr University. Received her Professional Degree in Mobile Application Engineering from Higher School of Technology, Salé, and her Master's in Information Systems Security from Ibn Tofail University, Kenitra. She completed her Ph.D. in Computer Science at Ibn Tofail University in 2023. Her research focuses on IoT security, real-time data analysis, and smart university systems. Dr. Oughannou has published several papers in international conferences and journals and has served as a reviewer for scientific articles.

Nebojsa Bacanin received his Ph.D. degree from the Faculty of Mathematics, University of Belgrade, in 2015 (study program Computer Science, average grade 10,00). He started his university career in Serbia 18 years ago at the Graduate School of Computer Science in Belgrade. He currently works as Full Professor, Vice-Rector for Scientific Research and Head of Applied Artificial Intelligence study program at Singidunum University, Belgrade, Serbia. He is involved in scientific research in the field of computer science, and his specialty includes stochastic optimization algorithms, swarm intelligence, soft-computing, optimization, and modeling, as well as artificial intelligence algorithms, swarm intelligence, machine learning, image processing, and cloud and distributed computing. He has published more than 430 scientific papers (more than 180 SCIE papers) in high-quality journals and international conferences indexed in Clarivate Analytics JCR, Scopus, WoS, IEEExplore, and other scientific databases. As member of numerous Editorial boards in cutting-edge international journals and Committee boards of international conferences, he regularly edit and perform review activities. He has also been included in the prestigious Stanford University list of the 2% best world researchers, when the whole career is considered, in the field of Artificial Intelligence. Also, according to AD scientific index, he is currently listed as the best researcher from Computer Science area in Serbia.

Mohamed Hanine is an esteemed academic and researcher specializing in computer science, with extensive expertise in big data, database systems, and decision support systems. He is currently an Associate Professor at the National School of Applied Sciences, University of Chouaib doukkali, in El Jadida, Morocco, where he teaches courses on Big Data, Graph Theory, NoSQL Databases, and Advanced Database Systems. Dr. Hanine obtained his Ph.D. in Computer Science from the University of Cadi Ayyad, Marrakech, where he developed a pioneering approach integrating Geographic Information Systems (GIS), multicriteria analysis, and online analytical processing (OLAP) for spatial decision support systems. In addition to his academic role, Dr. Hanine has actively contributed to scientific research, with a prolific record of peer-reviewed publications in high-impact journals. His research interests span artificial intelligence, machine learning, blockchain technology, software engineering, and decision-making methodologies.

Widi Aribowo is an Assistant Professor in the Department of Electrical Engineering at the Faculty of Vocational Studies, Surabaya State University. Known as a leading researcher, he has made significant contributions in the fields of metaheuristics, optimization, artificial intelligence, power systems, and microgrids. His scientific impact is evident through various publications in leading journals. Additionally, Dr. Widi Aribowo has demonstrated his expertise as a peer reviewer for several prestigious Q1 journals, highlighting his commitment to advancing academic discourse in metaheuristics, optimization, artificial intelligence, power systems, and microgrids.