Agricultural Internet of Things and Decision Support for Precision Smart Farming
Language: English
Published by Elsevier Inc, 2020
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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US$ 396.79
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nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
Seller Inventory # 9780128183731
- Title
- Agricultural Internet of Things and Decision Support for Precision Smart Farming
- Author
- Raj Khosla
- Publisher
- Elsevier Inc
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 012818373X
- ISBN 13
- 9780128183731
- Item weight
- 806 grams
- Dimensions
- 235x191x24 mm
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
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About the Author
Annamaria Castrignanò, formerly director of research at Council for Agricultural Research and Economics in Bari (Italy) and full professor of geostatistics at the G. D'Annunzio University of Chieti-Pescara (Italy). She is currently a senior researcher at the IREA Center of the National Research Council (CNR). She has been actively involved in the discipline of pedometrics and digital soil mapping for many years. Her knowledge and expertise in geostatistics and statistics has been exemplified in several oral presentations in International conferences and peer-refereed journal articles (she has published more than 300 papers). She has published also as co-editor of books of Elsevier, Springer, CRC Press regarding the application of geostatistics to pedology, environmental monitoring and smart farming. She has been the scientific leader of national and international projects aimed at the application of precision farming to the cultivation of durum wheat and tomato in Southern Italy and at the use of proximal and remote sensing in agriculture. She has been giving several basic and advanced courses on geostatistics to national and international PhD students and researchers in Italy and abroad. She is currently involved in the implementation of multivariate geostatistical techniques of data fusion with change of support using proximal and remote sensors.
Gabriele Buttafuoco is senior researcher in the National Research Council of Italy. His research focuses on the application of statistical and geostatistical methods for the purpose of analysing soil properties variability, modelling soil processes, delineating management zones for precision agriculture, hydrology and water resource management. He is also involved in proximal soil sensing, chemometrics, and data fusion. On these topics, he has published several articles in international journals and conference proceedings. He is Associate Editor for Environmental Earth Sciences and member of the Editorial Board of the journal Archives of Agronomy and Soil Science. He is member of International Society of Precision Agriculture, International Union of Soil Science, Italian Soil Science Society, and European Water Resources Association.
Prof. Raj Khosla, former Head of the Agronomy Department at Kansas State University, is a globally recognized authority on Precision Agriculture. He has been engaged in precision agriculture since inception and has made significant contributions in the development and spread of Precision Agriculture worldwide. He is the Founder and Past-President of the International Society of Precision Agriculture. Prof. Khosla’s research specializes in harnessing spatial and temporal heterogeneity in managed agro-ecosystems and translating those into better decision models. His group has extensively used remote sensing and other geo-spatial tools to enhance production, resource use efficiency, profitability, and sustainability of managed agro-ecosystems. He has co-authored over 100 refereed publications and has been invited globally to over 30 countries.
Prof. Khosla is the Fellow of American Association for Advancement of Science; Fellow of American Society of Agronomy; Fellow of Soil Science Society of America; Fellow of Crop Science Society of America, Fellow of Soil and Water Conservation Society and Honorary Life Fellow of International Society of Precision Agriculture.
Abdul Mouazen, specializing in proximal soil sensing for precision agriculture and environmental applications, is a patent holder of a mobile soil sensor that can analyse the composition of the soil by means of infrared spectroscopy. During his past 9 years employment at Cranfield University (UK), several pioneering precision agriculture applications of this innovative sensor were achieved.
In the start of 2017 he started his new position at the faculty of Bioscience Engineering at Ghent University, where he will carry out a project titled: Towards Establishing a Centre of Site-specific Technology for Soil and Crop Management (SiTeMan). The aim of the project is to establish a research platform combining cutting-edge soil and crop sensors, modelling and system control technology for managing farm resources site-specifically, with the final goal of establishing a precision agriculture centre in Flanders.
Dr. Dimitrios Moshou is an associate professor at AUTH and has a PhD from the Departments of Electrical Engineering and Biosystems, Faculty of Engineering, K.U. Leuven, Belgium, an MSc in control systems from the University of Manchester, and an MSc in electrical engineering. His research interests include the theory and applications of bio-inspired information processing, neuroscience, self-organisation, and computational intelligence and their use in intelligent control, pattern recognition, data fusion, and cognitive robotics. Application areas include mechatronics and non-destructive quality control and monitoring of bio-products and crops. He co-authroed the research monograph “Artificial Neural Maps on self-organizing networks and learning schemes and has written more than 180 papers in peer-reviewed journals, book chapters, and reviewed international conference proceedings, resulting in over 1500 citations. He has contributed in research and management tasks of 24 local and EU research projects. He has been involved in the proposal preparation, management, and research of several EU projects involving smart optical sensors, data fusion, and computational intelligence techniques. He was co-recipient of the Phytofare Prize 2001 for “Development of a weed activated spraying machine for targeted application of herbicides.
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