big data intelligence smart (26 Ergebnisse)

Zustand: New. In.

Zustand: New. In.

Zustand: New. Dr. Neelu Nagpal (Senior Member, IEEE), an Associate Professor at GGSIP University, has been working for the last 16 years in the EEE Department of Maharaja Agrasen Institute of Technology, Delhi, India. Her Ph.D. in Electrical Engineeri.

Zustand: New. In.

Paperback. Zustand: Brand New. 260 pages. 9.00x7.55x1.00 inches. In Stock.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In the dynamic realm of digital agriculture, the integration of big data acquisition platforms has sparked both curiosity and enthusiasm among researchers and agricultural practitioners. This book embarks on a journey to explore the intersection of artificial intelligence and agriculture, focusing on small-unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), edge-AI sensors and the profound impact they have on digital agriculture, particularly in the context of heterogeneous crops, such as walnuts, pomegranates, cotton, etc. For example, lightweight sensors mounted on UAVs, including multispectral and thermal infrared cameras, serve as invaluable tools for capturing high-resolution images. Their enhanced temporal and spatial resolutions, coupled with cost effectiveness and near-real-time data acquisition, position UAVs as an optimal platform for mapping and monitoring crop variability in vast expanses. This combination of data acquisition platforms and advanced analytics generates substantial datasets, necessitating a deep understanding of fractional-order thinking, which is imperative due to the inherent 'complexity' and consequent variability within the agricultural process. Much optimism is vested in the field of artificial intelligence, such as machine learning (ML) and computer vision (CV), where the efficient utilization of big data to make it 'smart' is of paramount importance in agricultural research. Central to this learning process lies the intricate relationship between plant physiology and optimization methods. The key to the learning process is the plant physiology and optimization method. Crafting an efficient optimization method raises three pivotal questions: 1.) What represents the best approach to optimization 2.) How can we achieve a more optimal optimization 3.) Is it possible to demand 'more optimal machine learning,' exemplified by deep learning, while minimizing the need for extensive labeled data for digital agriculture This book details the foundations of the plant physiology-informed machine learning (PPIML) and the principle of tail matching (POTM) framework. It is the 9th title of the 'Agriculture Automation and Control' book series published by Springer.

Zustand: New. In English.

Zustand: New. In.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity.This book presents the latest advances in big data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity.This book presents the latest advances in big data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Zustand: New. In.

Zustand: New. In.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the systemic scientific-methodological and practical exploration of organizational-technical and socio-economic issues related to the automation of decision-making in the smart economy under Industry 4.0 using big data and artificial intelligence (AI). The scientific novelty of the results presented in the book lies in uncovering the 'black box' of decision-making automation in the smart economy through these technologies. The book clarifies the role and significance of big data and AI in decision-making within the smart economy, highlighting its fundamental importance. Additionally, the book thoroughly discusses international experiences in decision-making automation in the smart economy, with examples from Armenia, Kyrgyzstan, and other Central Asian countries, demonstrating its empirical value.The book reveals advanced organizational-economic models for decision-making based on big data and AI. It also presents the latest trends in the development of the smart economy using big data and AI. Moreover, the book explains the socio-ecological and legal aspects of the ethics in applying big data and AI technologies. Additionally, the book proposes prospective applied solutions for decision-making in the smart economy based on big data and AI. The target audience of the book includes scientists studying big data and AI.