Smart Agricultural Services Using Deep Learning Big Data And Iot
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Smart Agricultural Services Using Deep Learning, Big Data, and IoT
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.
Smart Agriculture
This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.
Disruptive Technologies and Eco-Innovation for Sustainable Development
The rise of technology in human culture has changed almost every facet of society. Technology is especially useful regarding sustainable development. These technologies can cause significant greenhouse gas reductions and other benefits in terms of logistics and smart cities. New technology applied in this way can greatly help the human effort to restore the environment. Disruptive Technologies and Eco-Innovation for Sustainable Development provides an in-depth look into the new techniques, strategies, and technologies for achieving environmental sustainability through best business and technology practices. The book covers topics such as eco-innovation, green criteria, Agriculture 4.0, and topics related to logic, philosophy, and history of science and technology from the green/sustainable point of view. It is essential for managers, academicians, scientists, students, and researchers in various government, public, and private sectors.