Smart agriculture : emerging pedagogies of deep learning, machine learning and Internet of things
著者
書誌事項
Smart agriculture : emerging pedagogies of deep learning, machine learning and Internet of things
CRC Press, c2021
- : hardback
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注記
Includes bibliographical references
収録内容
- Machine learning and deep learning in agriculture / Sumit Koul
- Descriptive and predictive analytics of agricultural data using machine learning algorithms / R. Suguna and R. Uma Rani
- Discrimination between weed and crop via image analysis using machine learning algorithm / P. Amsini and R. Uma Rani
- Bio-inspired optimization algorithms for machine learning in agriculture applications / P.R. Mahidar and Deepika Ghai
- 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 Muqueen, G. Raju, Govind Singh Patel and Seema Nayak
- IoT in agriculture : survey on technology, challenges and future scope / Seema Nayak, Manoj Nayak and Govind Singh Patel
- 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 nurture using Internet of things / S. Siva Kumar ... [et al.]
- 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
内容説明・目次
内容説明
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.
目次
Machine learning and deep learning in agriculture, Descriptive and predictive analytics of agricultural data using machine learning algorithms, Discrimination between weed and crop via image analysis using machine learning algorithm, Bio-inspired optimization algorithms for machine learning in agriculture applications, Agricultural modernization with forecasting stages and machine learning, Classification of segmented image using increased global contrast for Paddy plant disease, IOT in agriculture: Survey on technology, challenges and future scope, Role of IoT in sustainable farming, Smart farming: Crop models and decision support systems using IOT, Smart irrigation in farming using internet of things, Automation systems in agriculture via IOT, A complete automated solution for farm field and garden nurture using internet of things, Machine intelligence techniques for agricultural production: Case study with tomato leaf disease detection, Clock signal and its attribute for agriculture.
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