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Author: Hamidah Ibrahim Publisher: Bentham Science Publishers ISBN: 9789815196191 Category : Technology & Engineering Languages : en Pages : 0
Book Description
Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features:
Author: Hamidah Ibrahim Publisher: Bentham Science Publishers ISBN: 9789815196191 Category : Technology & Engineering Languages : en Pages : 0
Book Description
Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features:
Author: S. Gowrishankar, Hamidah Ibrahim, A. Veena, K.P. Asha Rani, A.H. Srinivasa Publisher: Bentham Science Publishers ISBN: 9815196189 Category : Technology & Engineering Languages : en Pages : 229
Book Description
Data Science for Agricultural Innovation and Productivity explores the transformation of agriculture through data-driven practices. This comprehensive book delves into the intersection of data science and farming, offering insights into the potential of big data analytics, machine learning, and IoT integration. Readers will find a wide range of topics covered in 10 chapters, including smart farming, AI applications, hydroponics, and robotics. Expert contributors, including researchers, practitioners, and academics in the fields of data science and agriculture, share their knowledge to provide readers with up-to-date insights and practical applications. The interdisciplinary emphasis of the book gives a well-rounded view of the subject. With real-world examples and case studies, this book demonstrates how data science is being successfully applied in agriculture, inspiring readers to explore new possibilities and contribute to the ongoing transformation of the agricultural sector. Sustainability and future outlook are the key themes, as the book explores how data science can promote environmentally conscious agricultural practices while addressing global food security concerns. Key Features: - Focus on data-driven agricultural practices - Comprehensive coverage of modern farming topics with an interdisciplinary perspective - Expert insights - Sustainability and future outlook -Highlights practical applications Data Science for Agricultural Innovation and Productivity is an essential resource for researchers, data scientists, farmers, agricultural technologists, students, educators, and anyone with an interest in the future of farming through data-driven agriculture.
Author: Feras A. Batarseh Publisher: Academic Press ISBN: 012812444X Category : Computers Languages : en Pages : 256
Book Description
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. Offers a range of data science models, engineering tools, and federal use-cases Provides foundational observations into government data resources and requirements Introduces experiences and examples of data openness from the US and other countries A step-by-step guide for the conversion of government towards data-driven policy making Focuses on presenting data models that work within the constraints of the US government Presents the why, the what, and the how of injecting AI into federal culture and software systems
Author: Sanjay Chaudhary Publisher: Springer Nature ISBN: 981990577X Category : Technology & Engineering Languages : en Pages : 280
Book Description
This book presents the latest findings in the areas of digital ecosystem for innovation in agriculture. The book is organized into two sections with thirteen chapters dealing with specialized areas. It provides the reader with an overview of the frameworks and technologies involved in the digitalization of agriculture, as well as the data processing methods, decision-making processes, and innovative services/applications for enabling digital transformations in agriculture. The chapters are written by experts sharing their experiences in lucid language through case studies, suitable illustrations, and tables. The contents have been designed to fulfill the needs of geospatial, data science, agricultural, and environmental sciences of universities, agricultural universities, technological universities, research institutes, and academic colleges worldwide. It helps the planners, policymakers, and extension scientists plan and sustainably manage agriculture and natural resources.
Author: G. P. Obi Reddy Publisher: Springer Nature ISBN: 9811658471 Category : Technology & Engineering Languages : en Pages : 326
Book Description
This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.
Author: Chandrasekar Vuppalapati Publisher: CRC Press ISBN: 1000919153 Category : Technology & Engineering Languages : en Pages : 548
Book Description
Climate change, increasing population, food-versus-fuel economics, pandemics, etc. pose a threat to food security to unprecedented levels. It has fallen upon the practitioners of agriculture and technologists of the world to innovate and become more productive to address the multi-pronged food security challenges. Agricultural innovation is key to managing food security concerns. The infusion of data science, artificial intelligence (AI), advanced analytics, satellites data, geospatial data, climatology, sensor technologies, and climate modeling with traditional agricultural practices such as soil engineering, fertilizers use, and agronomy are some of the best ways to achieve this. Data science helps farmers to unravel patterns in fertilizer pricing, equipment usage, transportation and storage costs, yield per hectare, and weather trends to better plan and spend resources. AI enables farmers to learn from fellow farmers to apply best techniques that are transferred learning from AI to improve agricultural productivity and to achieve financial sustainability. Sensor technologies play an important role in getting real-time farm field data and provide feedback loops to improve overall agricultural practices and can yield huge productivity gains. Advanced Analytics modeling is essential software technique that codifies farmers’ tacit knowledge such as better seed per soil, better feed for dairy cattle breed, or production practices to match weather pattern that was acquired over years of their hard work to share with worldwide farmers to improve overall production efficiencies, the best antidote to food security issue. In addition to the paradigm shift, economic sustainability of small farms is a major enabler of food security. The book reviews all these technological advances and proposes macroeconomic pricing models that data mines macroeconomic signals and the influence of global economic trends on small farm sustainability to provide actionable insights to farmers to avert any financial disasters due to recurrent economic crises.
Author: Ali Emrouznejad Publisher: Springer ISBN: 3319930613 Category : Technology & Engineering Languages : en Pages : 204
Book Description
This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes.
Author: Amitava Choudhury Publisher: Springer Nature ISBN: 9811661243 Category : Computers Languages : en Pages : 236
Book Description
This book addresses the challenges for developing and emerging trends in Internet-of-Things (IoT) for smart agriculture platforms. It also describes data analytics & machine learning, cloud architecture, automation & robotics and aims to overcome existing barriers for smart agriculture with commercial viability. 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. The book 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. This volume will be helpful for engineering and technology experts and researchers, as well as for policy-makers.
Author: Hugo Campos Publisher: Springer Nature ISBN: 3030509915 Category : Technology & Engineering Languages : en Pages : 234
Book Description
This open access book is an important reframing of the role of innovation in agriculture. Dr. Campos and his distinguished coauthors address the need for agriculture to feed a growing global population with a reduced environmental footprint while adapting to and mitigating the effects of changing climate. The authors expand the customary discussion of innovation in terms of supply driven R&D to focus on the returns to investors and most importantly, the value to end-users. This is brought to life by exploring effective business models and many cases from agricultural systems across the globe. The focus on converting the results of innovation in R&D into adoption by farmers and other end-users is its greatest contribution. Many lessons from the book can be applied to private and public sectors across an array of agricultural systems. This book will be of enormous value to agri-business professionals, NGO leaders, agricultural and development researchers and those funding innovation and agriculture across the private and public sectors. Tony Cavalieri, Senior Program Officer, Bill & Melinda Gates Foundation Hugo Campos, Ph.D., MBA, has 20+ years of international corporate and development experience. His distinguished coauthors represent a rich collection of successful innovation practice in industry, consultancy, international development and academy, in both developed and developing countries.”
Author: Petra Moser Publisher: University of Chicago Press ISBN: 022677919X Category : Business & Economics Languages : en Pages : 270
Book Description
Feeding the world’s growing population is a critical policy challenge for the twenty-first century. With constraints on water, arable land, and other natural resources, agricultural innovation is a promising path to meeting the nutrient needs for future generations. At the same time, potential increases in the variability of the world’s climate may intensify the need for developing new crops that can tolerate extreme weather. Despite the key role for scientific breakthroughs, there is an active discussion on the returns to public and private spending in agricultural R&D, and many of the world’s wealthier countries have scaled back the share of GDP that they devote to agricultural R&D. Dwindling public support leaves universities, which historically have been a major source of agricultural innovation, increasingly dependent on industry funding, with uncertain effects on the nature and direction of agricultural research. All of these factors create an urgent need for systematic empirical evidence on the forces that drive research and innovation in agriculture. This book aims to provide such evidence through economic analyses of the sources of agricultural innovation, the challenges of measuring agricultural productivity, the role of universities and their interactions with industry, and emerging mechanisms that can fund agricultural R&D.
Author: Hamidah Ibrahim
Author: Hamidah Ibrahim
Author: S. Gowrishankar, Hamidah Ibrahim, A. Veena, K.P. Asha Rani, A.H. Srinivasa
Author: Feras A. Batarseh
Author: Sanjay Chaudhary
Author: G. P. Obi Reddy
Author: Chandrasekar Vuppalapati
Author: Ali Emrouznejad
Author: Amitava Choudhury
Author: Hugo Campos
Author: Petra Moser