Books in Information technology in agriculture

Agricultural Insights from Space

1st Edition
October 1, 2025
Dharmendra Singh + 2 more
English
Paperback
9 7 8 0 4 4 3 3 4 1 1 3 7
eBook
9 7 8 0 4 4 3 3 4 1 1 4 4

Agricultural Insights from Space: Machine Learning Applications in Satellite Data Analysis seamlessly integrates theoretical knowledge with practical applications, presenting cutting-edge research alongside real-world examples. This book leverages geospatial technology and Artificial Intelligence to address various challenges in agriculture. Readers will find practical examples and case studies demonstrating how machine learning and deep learning techniques can extract valuable insights from remote sensing data, optimizing agricultural processes. Highlighting the significance of satellite data, the book explores the benefits of leveraging space-based information for enhancing agricultural practices.The book emphasizes the importance of geospatial intelligence and AI technologies in monitoring and managing agricultural activities. It inspires readers to envision a future where these innovative approaches lead to more productive agricultural environments and healthier growth for future generations.

Unmanned Aerial Systems in Agriculture

1st Edition
August 11, 2023
Dionysis Bochtis + 2 more
English
Paperback
9 7 8 0 3 2 3 9 1 9 4 0 1
eBook
9 7 8 0 3 2 3 9 1 4 0 1 7

Unmanned Aerial Systems in Agriculture: Eyes Above Fields bridges the gap between knowledge of concept and real-world use and operations of UASs in agri-production. Based on a valuable combination of themes presented at the 13th European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) and supplemented by targeted invited articles of key-scientists, this book presents a full-spectrum view of the use of unmanned aerial systems (UAS) for agricultural applications. It integrates dispersed knowledge in the field, providing a holistic approach regarding UAVs and other UAS and their use in sustainable decisions. The integrated approach of the book provides a fresh look on contemporary agriculture-related issues, following precision farming approaches, by educating on a range of different issues of remote sensing and its use in agriculture. Furthermore, the operational planning aspects for UAS in agriculture focus part of the book provides information that is missing from other resources.

Application of Machine Learning in Agriculture

1st Edition
May 14, 2022
Mohammad Ayoub Khan + 2 more
English
Paperback
9 7 8 0 3 2 3 9 0 5 5 0 3
eBook
9 7 8 0 3 2 3 9 0 6 6 8 5

Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics.

Intelligent Data Mining and Fusion Systems in Agriculture

1st Edition
October 8, 2019
Xanthoula-Eirini Pantazi + 2 more
English
Paperback
9 7 8 0 1 2 8 1 4 3 9 1 9
eBook
9 7 8 0 1 2 8 1 4 3 9 2 6

Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms.

Federal Data Science

1st Edition
September 21, 2017
Feras A. Batarseh + 1 more
English
Paperback
9 7 8 0 1 2 8 1 2 4 4 3 7
eBook
9 7 8 0 1 2 8 1 2 4 4 4 4

Federal Data Science serves as a guide for federal software engineers, government analysts, economists, researchers, data scientists, and engineering managers in deploying data analytics methods to governmental processes. Driven by open government (2009) and big data (2012) initiatives, federal agencies have a serious need to implement intelligent data management methods, share their data, and deploy advanced analytics to their processes. Using federal data for reactive decision making is not sufficient anymore, intelligent data systems allow for proactive activities that lead to benefits such as: improved citizen services, higher accountability, reduced delivery inefficiencies, lower costs, enhanced national insights, and better policy making. No other government-dedicated work has been found in literature that addresses this broad topic. This book provides multiple use-cases, describes federal data science benefits, and fills the gap in this critical and timely area. Written and reviewed by academics, industry experts, and federal analysts, the problems and challenges of developing data systems for government agencies is presented by actual developers, designers, and users of those systems, providing a unique and valuable real-world perspective.

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