Recent Trends in Geospatial AI

Darwish, Dina · Chemingui, Houssem

2024. g. dec. · IGI Global

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Geospatial research is facing both enormous new potential and challenges due to artificial intelligence (AI). Theoretical advances, large data, computer hardware, and high-performance computing platforms that enable the creation, training, and deployment of AI models in a reasonable amount of time are the main drivers of its rapid development. There have been notable developments in the field of geospatial AI, particularly in the areas of machine learning, deep learning, and the most recent advancements in AI technology in both academia. These advancements are transforming how spatial data is analyzed and interpreted, enabling more accurate predictions, real-time mapping, and enhanced decision-making capabilities across various applications.

Recent Trends in Geospatial AI discusses the emerging potentials, challenges, and trends in geospatial AI. It further explores innovative applications of geospatial AI across a variety of sectors. Covering topics such as data processing, internet of things (IoT), and traffic flow optimization, this book is an excellent resource for graduate and postgraduate students, researchers, academicians, practitioners, and more.

Par autoru

|Dina Darwish - Editor|Prof. Dina Darwish , Vice dean, faculty of computer science and information technology, Ahram Canadian university, Egypt. I obtained my Ph.D from Cairo university at 2009, engineering faculty. I am professor since 2020, also my special domain is artificial intelligence and I have many publications in the following topics, including: Artificial intelligence, wireless ad hoc networks, Internet of things, Big data analytics, Blockchain applications, Cloud computing applications, Web 3 technologies, Chatbots development and others. My email is: [email protected]

Houssem Chemingui is a French Assistant Professor of Information Systems at Brest Business School, France. He earned his PhD in Computer Science from Université Paris 1 Panthéon-Sorbonne. His research focuses on artificial intelligence, data analytics, and software configuration. Dr. Chemingui has held teaching positions at Université Paris 1 Panthéon-Sorbonne and various Tunisian institutions. He has significantly contributed to methods for guided configuration of dynamic product lines and AI applications in logistics and marketing. An active participant in scientific events, he bridges the gap between academic research and practical applications. [Editor]

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