Internet of things (IoT) is a new type of network that combines communication technology, expanded applications, and physical devices. Among them, agriculture is one of the most important areas in the application of the IoT technology, which has its unique requirements and integration features. Compared to the information technology in traditional agriculture, the agricultural IoT mainly refers to industrialized production and sustainable development under relatively controllable conditions. Agricultural IoT applies sensors, RFID, visual capture terminals and other types of sensing devices to detect and collect site information, and with broad applications in field planting, facility horticulture, livestock and poultry breeding, aquaculture and agricultural product logistics. It utilizes multiple information transmission channels such as wireless sensor networks, telecommunications networks and the internet to achieve reliable transmission of agricultural information at multiple scales and intelligently processes the acquired, massive information. The goals are to achieve (i) optimal control of agricultural production process, (ii) intelligent electronic trading of agricultural products circulation, and (iii) management of systematic logistics, quality and safety traceability. This book focuses on three levels of agricultural IoT network: information perception technology, information transmission technology and application technology.

Agricultural Internet of Things and Decision Support for Smart Farming reveals how a set of key enabling technologies (KET) related to agronomic management, remote and proximal sensing, data mining, decision-making and automation can be efficiently integrated in one system. Chapters cover how KETs enable real-time monitoring of soil conditions, determine real-time, site-specific requirements of crop systems, help develop a decision support system (DSS) aimed at maximizing the efficient use of resources, and provide planning for agronomic inputs differentiated in time and space. This book is ideal for researchers, academics, post-graduate students and practitioners who want to embrace new agricultural technologies. - Presents the science behind smart technologies for agricultural management - Reveals the power of data science and how to extract meaningful insights from big data on what is most suitable based on individual time and space - Proves how advanced technologies used in agriculture practices can become site-specific, locally adaptive, operationally feasible and economically affordable

This new book provides an insightful look at the varied and exciting uses and applications of Wi-Fi and the Internet of Things in agriculture. With internet-enabled communications becoming more widely available, farms and agricultural establishments can take advantage of these new technologies for a wide range of farm operations, such as crop management, farm vehicle tracking, livestock monitoring, storage monitoring, and more. The collected data from these devices can be stored in the cloud system or server and accessed by the farmers via the internet or mobile phones. This book shows the many benefits to farmers from applying IoT, including better utilizing information for monitoring crops, optimizing water use, planning effective fertilization strategies, and saving time and reducing the operation expenses. Topics include using IoT for vertical farming, IoT-based smart irrigation system, landslide susceptibility assessment, automated aeroponics systems, crop survival analysis, and more. The volume also considers the challenges of IoT in agriculture, such as the requirements of applications of wireless sensor networks, the threat of attacks and the detection of vulnerabilities in wireless sensor networks, and more. Internet of Things for Agriculture 4.0: Impact and Challenges provides a better understanding of the time- and resourcing-saving benefits of wireless sensors and remote monitoring devices in agriculture. The volume will be useful for those involved in agricultural operations as well as scientists and researchers, and faculty and students in agriculture and computer and information science engineering.

Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.

In order to meet food needs, farmers need to integrate the latest technologies enabling them to make more informed decisions. Smart Farming Technologies for Sustainable Agricultural Development provides innovative insights into the latest farming advancements in terms of informatics and communication. The content within this publication represents the work of topics such as sensor systems, wireless communication, and the integration of the Internet of Things in agriculture-related processes. It is a vital reference source for farmers, academicians, researchers, government agencies, technology developers, and graduate-level students seeking current research on smart farming technologies.

A comprehensive overview of the Internet of Things’ core concepts, technologies, and applications Internet of Things A to Z offers a holistic approach to the Internet of Things (IoT) model. The Internet of Things refers to uniquely identifiable objects and their virtual representations in an Internet-like structure. Recently, there has been a rapid growth in research on IoT communications and networks, that confirms the scalability and broad reach of the core concepts. With contributions from a panel of international experts, the text offers insight into the ideas, technologies, and applications of this subject. The authors discuss recent developments in the field and the most current and emerging trends in IoT. In addition, the text is filled with examples of innovative applications and real-world case studies. Internet of Things A to Z fills the need for an up-to-date volume on the topic. This important book: Covers in great detail the core concepts, enabling technologies, and implications of the Internet of Things Addresses the business, social, and legal aspects of the Internet of Things Explores the critical topic of security and privacy challenges for both individuals and organizations Includes a discussion of advanced topics such as the need for standards and interoperability Contains contributions from an international group of experts in academia, industry, and research Written for ICT researchers, industry professionals, and lifetime IT learners as well as academics and students, Internet of Things A to Z provides a much-needed and comprehensive resource to this burgeoning field.

This book presents recent findings on virtually every aspect of wireless IoT and analytics for agriculture. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. In turn, it addresses the latest innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of IoT and analytics for agriculture. In closing, it explores a range of applications, including: intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systems.

The book discusses one of the major challenges in agriculture which is delivery of cultivate produce to the end consumers with best possible price and quality. Currently all over the world, it is found that around 50% of the farm produce never reaches the end consumer due to wastage and suboptimal prices. The authors present solutions to reduce the transport cost, predictability of prices on the past data analytics and the current market conditions, and number of middle hops and agents between the farmer and the end consumer using IoT-based solutions. Again, the demand by consumption of agricultural products could be predicted quantitatively; however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage, etc., could be difficult to be predicted, so that the supply and demand of agricultural products has not been controlled properly. To overcome, this edited book designed the IoT-based monitoring system to analyze crop environment and the method to improve the efficiency of decision making by analyzing harvest statistics. The book is also useful for academicians working in the areas of climate changes.

This book examines different innovations in worldwide agricultural-systems including the applications of artificial intelligence (AI), internet of things (IoT) and features of machine learning (ML) for the benefits of the farm-community. Specifically, it examines the use of agricultural equipment and IoT to reduce physical stress; innovative equipment that measure and reduce mental work load; and innovative techniques to help with employee safety. Featuring case studies and future implications, this book is an excellent guide for academics and researchers in the agri-sector.

The agricultural sector can benefit immensely from developments in the field of smart farming. However, this research area focuses on providing specific fixes to particular situations and falls short on implementing data-driven frameworks that provide large-scale benefits to the industry as a whole. Using deep learning can bring immense data and improve our understanding of various earth sciences and improve farm services to yield better crop production and profit. Smart Agricultural Services Using Deep Learning, Big Data, and IoT is an essential publication that focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is ideally designed for engineers, programmers, software developers, agriculturalists, farmers, policymakers, researchers, academicians, and students.