Skip to main content
Elsevier

Books in Information technology in agriculture

  • Machine Learning and AI Technology for Agricultural Applications

    • 1st Edition
    • Kishore Chandra Swain + 5 more
    • English
    Feeding a growing global population with a changing climate, shrinking arable land, and increasingly strained water resources is a challenge with no single solution. Machine Learning and AI Technology in Agricultural Applications recasts agriculture as fundamentally a problem of data acquisition, integration, and analysis. Drawing on concrete methods and case studies, the book shows how advanced technologies turn scattered sensor readings, satellite imagery, and field records into decision-making tools that enable more precise, more resilient, and more sustainable farming practices.The chapters cover the full agricultural cycle: crop and weather indicators feeding models that predict yield before harvest; satellites and drones replacing manual field-monitoring surveys across the growing season; and image-based algorithms supporting targeted interventions, from detecting a diseased plant to directing a sprayer to apply treatment only where it is required. The same reliance on remote sensing and predictive modeling carries into aquaculture and water management, where artificial intelligence (AI) and machine learning (ML) are used to estimate groundwater recharge, track fish growth, and monitor water quality. A dedicated set of chapters also examines the economic dimensions of this shift, assessing the viability, market impact, and costs of adopting these innovations, and clarifying where they are most likely to reshape how these sectors operate.Together, these technical perspectives make the book a valuable resource for students building a foundation in this field, as well as for researchers and practitioners looking to apply its findings and insights to their own work.

  • 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.

  • 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.