Overview

The Earth Sciences industry faces a new challenge - the need for accurate, efficient, and reliable methods to monitor and predict geological phenomena and environmental changes. As climate change, earthquakes, and other natural disasters become more frequent and severe, the necessity for advanced tools and techniques is paramount. Traditional methods often fall short in providing the precision and speed required to address these critical issues. Geologists and earth scientists who are grappling with the urgent problem of utilizing artificial intelligence (AI) to revolutionize their field, will find the solution within the pages of Novel AI Applications for Advancing Earth Sciences. This book offers the research community concepts expanding upon the fusion of AI technology with earth sciences. By leveraging advanced AI tools, such as convolutional neural networks, support vector machines, artificial neural networks, and the potential of remote sensing satellites, this book transforms the identification of geological features, geological mapping, soil classification, and gas detection. Scientists can now predict earthquakes and assess the probability of climate change with unprecedented accuracy. Additionally, the book explains how the optimization of algorithms for specific tasks substantially reduces the time complexity of earth observations, leading to an unprecedented leap in accuracy and efficiency. The book goes beyond academic insights, and extends its reach to real-world applications. It empowers scholars, researchers, students, and practitioners to monitor climate change, evaluate carbon footprints, and adapt to changes in land use. Furthermore, it plays a pivotal role in optimizing renewable energy production, ensuring the world's transition to clean, reliable energy sources. The data obtained from Earth observation satellites can be harnessed for a multitude of on-ground applications, ranging from agriculture and forestry to mining, water management, rural and urban development, and more. In a world where AI meets earth sciences, this book provides many innovative solutions to the challenges faced by academicians and researchers, illuminating the path toward a more informed future.

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Sudesh Yadav is Assistant Professor (Computer Science) in Dept. of Higher Education Haryana. She is currently working at Govt. College, Ateli, Indira Gandhi University Meerpur, Rewari, Haryana. She has completed her M.Tech. (Information Security) from NSUT East Campus Delhi (formerly AIACTR) and Ph. D. in Computer Science from Guru Gobind Singh Indraprastha University Delhi. She has published many research paper in referred international journals and conferences and reviewed many research papers of international journals and conferences. Her area of interest is artificial intelligence, IoT, digital image processing, soft computing and pattern recognition, natural language processing. Satya Prakash Yadav is currently the Associate Professor of the Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management (GLBITM), Greater Noida (India) and has completed his Postdoctoral under the supervision Prof. (Dr.) Victor Hugo C. de Albuquerque, from Federal Institute of Education, Science and Technology of Ceará, Brazil. He has awarded his PhD degree from Dr. A.P.J. Abdul Kalam Technical University (AKTU) (formerly UPTU). Currently, 4 students are working for Ph.D. under my guidance. A seasoned academician having more than 17 years of experience, he has published four books (Programming in C, Programming in C++ and Blockchain and Cryptocurrency) under I.K. International Publishing House Pvt. Ltd. Including Distributed Artificial Intelligence: A Modern Approach, Published December 18, 2020 by CRC Press. He has undergone industrial training programs during which he was involved in live projects with companies in the areas of SAP, Railway Traffic Management Systems, and Visual Vehicles Counter and Classification (used in the Metro rail network design). He is an alumnus of Netaji Subhas Institute of Technology (NSIT), Delhi Universit Pethuru. Raj Chelliah has been working in the Site Reliability Engineering (SRE) Center of Excellence, Reliance Jio Infocomm Ltd. (RJIL), Bangalore. My previous stints are in IBM Cloud center of Excellence (CoE), Wipro consulting services (WCS), and Robert Bosch Corporate Research (CR). In total, I have gained more than 17 years of IT industry experience and 8 years of research experience. Finished the CSIR-sponsored PhD degree at Anna University, Chennai and continued with the UGC-sponsored postdoctoral research in the Department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, I was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. Published more than 40 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc. Have authored and edited 16 books thus far and focus on some of the emerging technologies such as IoT, Cognitive Analytics, Blockchain, Digital Twin, Docker Containerization, Data Science, Microservices Architecture, fog / edge computing, Artificial intelligence (AI), etc. Madan Mohan Malaviya University of Technology, Gorakhpur (U.P.) India | MMMEC · Department of Electrical Engineering, Victor Hugo C. de Albuquerque has a PhD in Mechanical Engineering with emphasis on Materials from the Federal University of Paraíba (2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (2007), and he graduated in Mechatronics Technology at the Federal Center of Technological Education of Ceará (2006). He is currently Assistant VI Professor of the Graduate Program in Applied Informatics at the University of Fortaleza (UNIFOR). He has experience in Computer Systems, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, image segmentation, biomedical circuits and human/brain-machine interaction, NeuroBiofeedback, Neurorehabilitation, Visual Stimulation, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Additionally, he has research at the microstructural characterization field through the combination of non-destructive techniques with signal/image processing and analysis, and pattern recognition.

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