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Books in Information technology in agriculture

  • Precision Technologies for Digital Agriculture

    Harnessing IoT, Big Data, Crop Modeling, and AI for Agricultural Production
    • 1st Edition
    • Sushil Kumar Himanshu + 2 more
    • English
    Precision Technologies for Digital Agriculture investigates the growing role of computational and connected approaches in contemporary agricultural environments, bringing together recent findings in artificial intelligence, sensing infrastructures, agroecosystem modeling, and data analytics to illustrate decisive shifts toward more accurate, forward-looking, and responsive decision-making.Earl... chapters set out the theoretical and technical context for digital and precision agriculture, addressing automation, data stewardship, privacy, and the development of dependable AI‑based tools. These foundations support a detailed overview of key technological building blocks, including remote and proximal sensing, geospatial platforms, machine vision, digital twins, and the Internet of Living Things, with emphasis on their contribution to integrated system management and optimized resource allocation.Later sections concentrate on applied methods and decision‑support functions across field operations. Topics include climate‑adaptive and smart irrigation, soil and microbial diagnostics, UAV‑enabled monitoring, and algorithmic frameworks to yield estimation and nutrient management. Across these chapters, attention is given to both implementation constraints and enabling conditions, including interoperability, data security, and scalability.The volume concludes with regionally grounded case studies and economic assessments that explore adoption strategies, governance arrangements, and cost–benefit considerations across diverse crops and production settings. Together, these cutting-edge analyses provide a structured assessment of how digital technologies are being translated into transformative agricultural practice, and of the technical and institutional conditions required to support their effective use.

  • From Conventional to Artificial Intelligence-Based Agriculture

    • 1st Edition
    • Vivek Sharma + 2 more
    • English
    From Conventional to Artificial Intelligence-Based Agriculture explores the evolving landscape of agriculture as it transitions from traditional practices to advanced, AI-driven solutions. With AI and machine learning revolutionizing industries worldwide, their impact on agriculture is becoming increasingly significant. These technologies are not only aiding in climate modeling but also opening new possibilities for precision farming, enabling more accurate crop health diagnostics, efficient resource management, and timely intervention strategies.By integrating conventional agricultural knowledge with cutting-edge AI tools, farmers and researchers can better assess soil conditions, predict optimal planting windows, monitor nutrient dynamics, and understand market trends with greater precision. This convergence of tradition and technology supports more resilient, productive, and sustainable agricultural systems, paving the way for a smarter and more food-secure future.

  • Next-Gen Smart Farming

    Integrating AI, IoT, Digital Twin, and Robotics for Cyber-Physical Systems
    • 1st Edition
    • Annamaria Castrignanò + 3 more
    • English
    Next-Gen Smart Farming presents a thorough, evidence-based assessment of using emerging physical and computerized systems designed to enhance agricultural efficiency. It balances demonstrated benefits with a clear articulation of potential risks.The work surveys the entire pipeline, from sensing technologies and data collection to artificial intelligence and machine learning, spatial analysis, decision modeling, and automation. It highlights how these technologies can strengthen crop monitoring, yield forecasting, and farm management, while it also examines governance, equity, and ethical considerations essential for responsible deployment. Economic, environmental, and social impacts are analyzed, providing a comprehensive framework for evaluating trade-offs and outcomes in real-world contexts.Framed as an interdisciplinary resource, the volume equips researchers, industry practitioners, extension specialists, and policymakers with practical methodologies, metrics, and narratives needed to implement scalable digital agriculture solutions that improve productivity, resilience, and sustainability across diverse real-world settings.

  • Agricultural Insights from Space

    Machine Learning Applications in Satellite Data Analysis
    • 1st Edition
    • Dharmendra Singh + 2 more
    • English
    Agricultural Insights from Space offers a comprehensive exploration of how geospatial technology and machine learning are transforming modern agriculture. From satellite data acquisition and soil mapping to crop classification, yield prediction, and irrigation optimization, this volume presents cutting-edge methods for advancing precision and sustainable farming.Key chapters highlight the integration of spatial data with AI to monitor crop health, track pest and disease outbreaks, manage livestock, and map agroforestry systems. The use of climate data and deep learning models illustrates how these innovations strengthen resilience and support informed decision-making in the face of environmental challenges.Through detailed methodologies and real-world case studies, including applications of Lagrange polynomials, deep learning ensembles, and synthetic data generation, the book showcases practical solutions that bridge research and implementation.Wheth... applied in academic research, fieldwork, or technology development, Agricultural Insights from Space offers a multidisciplinary foundation for tackling complex agricultural challenges. It empowers readers to harness emerging technologies not just to improve efficiency, but to reshape agricultural systems for long-term sustainability and impact.

  • Agri 4.0 and the Future of Cyber-Physical Agricultural Systems

    • 1st Edition
    • Seifedine Kadry + 4 more
    • English
    Agri 4.0 and the Future of Cyber-Physical Agricultural Systems is the first book to explore the potential use of technology in agriculture with a focus on technologies that enable the reader to better comprehend the full range of CPS opportunities. From planning to distribution, CPS technologies are available to impact agricultural output, delivery, and consumption. Specific sections explore ways to implement CPS effectively and appropriately and cover digitalization of agriculture, digital computers to assist the processes of agriculture with digitized data and allied technologies, including AI, Computer Vision, Big data, Block chain, and IoT. Other sections cover Agri 4.0 and how it can digitalize, estimate, plan, predict, and produce the optimum agricultural inputs and outputs required for commercial purposes. The global team of authors also presents important insights into promising areas of precision agriculture, autonomous systems, smart farming environment, smart production monitoring, pest detection and recovery, sustainable industrial practices, and government policies in Agri 4.0.

  • Unmanned Aerial Systems in Agriculture

    Eyes Above Fields
    • 1st Edition
    • Dionysis Bochtis + 2 more
    • English
    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.

  • Intelligent Data Mining and Fusion Systems in Agriculture

    • 1st Edition
    • Xanthoula-Eirini Pantazi + 2 more
    • English
    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

    Transforming Government and Agricultural Policy Using Artificial Intelligence
    • 1st Edition
    • Feras A. Batarseh + 1 more
    • English
    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.