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010 a| 2020036554;

020 a| 9781003138884q| (ebook);

020 z| 9780367535803q| (hardback);

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245 00 a| Smart agricultureh| [electronic resource] :b| emerging pedagogies of deep learning, machine learning and Internet of Things /c| edited by Govind Singh Patel, LPU Phagwara, India, Amrita Rai, UPTU, India, Nripendra Narayan Das, Manipal University Jaipur, India, R.P. Singh, Haramaya University, Diredawa, Ethiopia.;

250 a| First edition.;

260 a| Boca Raton :b| CRC Press/Balkema/Taylor & Francis Group,c| [2021];

300 a| 1 online resource;

505 0 a| Machine learning and deep learning in agriculture / Sumit Koul -- Descriptive and predictive analytics of agricultural data using machine learning algorithms / Mrs. R. Suguna, Dr. R. Uma Rani -- Discrimination between weed and crop via image analysis using machine learning algorithm / P Amsin, Dr. R. Ma Rani -- Bio-inspired optimization algorithms for machine learning in agriculture applications / P.R. MahiDar-- Agricultural modernization with forecasting stages and machine learning / A.K. Awasthi and Arun Kumar Garov--Classification of segmented image using increased global contrast for paddy plant disease / Md Abdul Muqueem, G. Raju and Govind Singh Patel -- IoT in agriculture : Survey on technology, challenges and future scope / Seema Nayak -- Role of IoT in sustainable farming / Rajasekhar Manda and P.Rajesh Kumar -- Smart farming : Crop models and decision support systems using IoT / Kanwaljeet Singh and Amandeep Kaur -- Smart irrigation in farming using internet of things / Devesh Kumar Srivastava and Priyanka Nair -- Automation systems in agriculture via IoT / Shylaja Vinay Kumar Karatangi, Reshu Agarwal and Manisha Pant -- A complete automated solution for farm field and garden nurturing using Internet of Things / S. Siva Kumar, A. M. Senthil Kumar, T. Rajesh Kumar, N. Sree Ram, V. Krishna Reddy and P. Sivakumar -- Machine intelligence techniques for agricultural production : Case study with tomato leaf disease detection / Mihir Narayan Mohanty -- Clock signal and its attribute for agriculture / Abhishek Kumar.;

506 a| Available only to authorized users.;

520 a| "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"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

588 a| Description based on print version record and CIP data provided by publisher.;

650 0 a| Artificial intelligencex| Agricultural applications.=| ^A856677;

650 0 a| Agricultural innovations.=| ^A123825;

650 0 a| Machine learning.=| ^A145211;

650 0 a| Internet of things.=| ^A1157117;

650 0 a| Big data.=| ^A1157100;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Patel, Govind Singh.?| UNAUTHORIZED;

776 08 i| Print version:t| Smart agricultureb| First edition.d| Boca Raton : CRC Press/Balkema/Taylor & Francis Group, [2021]z| 9780367535803w| (DLC) 2020036553;

856 40 z| Full text available from eBooks on EBSCOhostu| https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=2701045&scope=site&custid=s5822723&authtype=ip,shib;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003138884;

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Smart agriculture emerging pedagogies of deep learning, machine learning and Internet of Things / edited by Govind Singh Patel, LPU Phagwara, India, Amrita Rai, UPTU, India, Nripendra Narayan Das, Manipal University Jaipur, India, R.P. Singh, Haramaya University, Diredawa, Ethiopia.

Other author	Patel, Govind Singh.
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton : CRC Press/Balkema/Taylor & Francis Group, [2021]
Description	1 online resource
Supplemental Content	Full text available from eBooks on EBSCOhost
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Artificial intelligence--Agricultural applications. Agricultural innovations. Machine learning. Internet of things. Big data.

Contents	Machine learning and deep learning in agriculture / Sumit Koul -- Descriptive and predictive analytics of agricultural data using machine learning algorithms / Mrs. R. Suguna, Dr. R. Uma Rani -- Discrimination between weed and crop via image analysis using machine learning algorithm / P Amsin, Dr. R. Ma Rani -- Bio-inspired optimization algorithms for machine learning in agriculture applications / P.R. MahiDar-- Agricultural modernization with forecasting stages and machine learning / A.K. Awasthi and Arun Kumar Garov--Classification of segmented image using increased global contrast for paddy plant disease / Md Abdul Muqueem, G. Raju and Govind Singh Patel -- IoT in agriculture : Survey on technology, challenges and future scope / Seema Nayak -- Role of IoT in sustainable farming / Rajasekhar Manda and P.Rajesh Kumar -- Smart farming : Crop models and decision support systems using IoT / Kanwaljeet Singh and Amandeep Kaur -- Smart irrigation in farming using internet of things / Devesh Kumar Srivastava and Priyanka Nair -- Automation systems in agriculture via IoT / Shylaja Vinay Kumar Karatangi, Reshu Agarwal and Manisha Pant -- A complete automated solution for farm field and garden nurturing using Internet of Things / S. Siva Kumar, A. M. Senthil Kumar, T. Rajesh Kumar, N. Sree Ram, V. Krishna Reddy and P. Sivakumar -- Machine intelligence techniques for agricultural production : Case study with tomato leaf disease detection / Mihir Narayan Mohanty -- Clock signal and its attribute for agriculture / Abhishek Kumar.
Abstract	"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"-- Provided by publisher.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Source of description	Description based on print version record and CIP data provided by publisher.
Issued in other form	Print version: Smart agriculture First edition. Boca Raton : CRC Press/Balkema/Taylor & Francis Group, [2021] 9780367535803
Genre/form	Electronic books.
LCCN	2020036554
ISBN	9781003138884 (ebook)
ISBN	(hardback)

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Library	Location	Call Number	Status	Item Actions
	Electronic Resources	Online Content Full text available from eBooks on EBSCOhost Full text available from Taylor & Francis eBooks	✔ Available

Smart agriculture emerging pedagogies of deep learning, machine learning and Internet of Things / edited by Govind Singh Patel, LPU Phagwara, India, Amrita Rai, UPTU, India, Nripendra Narayan Das, Manipal University Jaipur, India, R.P. Singh, Haramaya University, Diredawa, Ethiopia.

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