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IoT and AI in Agriculture, Ahamed


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Цена: 25155.00р.
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Автор: Ahamed
Название:  IoT and AI in Agriculture
ISBN: 9789811981128
Издательство: Springer
Классификация:


ISBN-10: 9811981124
Обложка/Формат: Hardback
Страницы: 461
Вес: 0.97 кг.
Дата издания: 11.04.2023
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 60 tables, color; 1 illustrations, black and white; xvii, 461 p. 1 illus.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Life Sciences
Подзаголовок: Self- sufficiency in food production to achieve society 5.0 and sdg`s globally
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book reviews recent innovations in the smart agriculture space that use the Internet of Things (IoT) and sensing to deliver Artificial Intelligence (AI) solutionsto agricultural productivity in the agricultural production hubs. In this regard, South and Southeast Asia are one of the major agricultural hubs of the world, facing challenges of climate change and feeding the fast-growing population. To address such challenges, a transboundary approach along with AI and BIG data for bioinformatics are required to increase yield and minimize pre- and post-harvest losses in intangible climates to drive the sustainable development goal (SDG) for feeding a major part of the 9 billion population by 2050 (Society 5.0 SDG 1 & 2). Therefore, this book focuses on the solution through smart IoT and AI-based agriculture including pest infestation and minimizing agricultural inputs for in-house and fields production such as light, water, fertilizer and pesticides to ensure food security aligns with environmental sustainability. It provides a sound understanding for creating new knowledge in line with comprehensive research and education orientation on how the deployment of tiny sensors, AI/Machine Learning (ML), controlled UAVs, and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms for nurturing and driving the pace of smart agriculture in this current time. The book will appeal to several audiences and the contents are designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science disciplines. Utmost care has been taken to present a varied range of resource areas along with immense insights into the impact and scope of IoT, AI and ML in the growth of intelligent digital farming and smart agriculture which will give comprehensive information to the targeted readers.
Дополнительное описание: Chapter 1. IoT x AI: Introducing Agricultural Innovation for Global Food Production.- Chapter 2. Transforming Controlled Environment Plant Production toward Circular Bioeconomy Systems.- Chapter 3. Artificial Lighting Systems for Plant Growth and Developm



Economics of Agricultural Commodities Series: Fruits and Nuts, 2 Vol. Set

Автор: Bansil
Название: Economics of Agricultural Commodities Series: Fruits and Nuts, 2 Vol. Set
ISBN: 8123928831 ISBN-13(EAN): 9788123928838
Издательство: CBS India
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Цена: 29224.00 р. 41748.00 -30%
Наличие на складе: Есть (1 шт.)

Economics of Agricultural Commodities: Vegetables

Автор: Bansil
Название: Economics of Agricultural Commodities: Vegetables
ISBN: 8123928920 ISBN-13(EAN): 9788123928920
Издательство: CBS India
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Цена: 18251.00 р. 26073.00 -30%
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Compendium of Bioenergy Plants

Автор: Eric Lam
Название: Compendium of Bioenergy Plants
ISBN: 1498743382 ISBN-13(EAN): 9781498743389
Издательство: Taylor&Francis
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Цена: 27562.00 р.
Наличие на складе: Поставка под заказ.

Описание:

This volume of the Bioenergy Plants compendium contains a collection of chapters that focus on the history, economics, and practical sciences related to sugarcane. As one of the key biofuel crops in the world that is under large-scale cultivation, sugarcane is attracting interests for its adoption and emulation worldwide. With a high ratio of energy output to input for its production, sugarcane-derived bioethanol currently has the lowest carbon footprint as a renewable fuel product. Comprehensive chapters explore all the essential aspects of sugarcane's origin as a crop, its limitations, and current efforts for its improvement through traditional breeding, and biochemical and molecular approaches. Importantly, experts in the economic and social science areas also provide key insights as to how forces in the policy and human dimensions intimately interact with geographic factors to help shape the sugarcane crop's potential for deployment as well as its future impact on the energy sector.

Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation

Автор: Prasad S. Thenkabail, John G. Lyon, Alfredo Huete
Название: Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation
ISBN: 1138364762 ISBN-13(EAN): 9781138364769
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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Описание: This volume discusses the use of hyperspectral data in numerous applications such as forest management, precision farming, monitoring invasive species, local to global land cover change detection, crop yield modeling and crop moisture assessment. Also emphasizes the importance of hyperspectral remote sensing tools for studying vegetation.

Biophysical and Biochemical Characterization and Plant Species Studies

Автор: Prasad S. Thenkabail, John G. Lyon, Alfredo Huete
Название: Biophysical and Biochemical Characterization and Plant Species Studies
ISBN: 1138364711 ISBN-13(EAN): 9781138364714
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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Описание: This volume reviews existing "state-of-art" knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral data in applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessment. Includes extensive discussions on data processing mechanisms.

Hyperspectral Indices and Image Classifications for Agriculture and Vegetation

Автор: Prasad S. Thenkabail, John G. Lyon, Alfredo Huete
Название: Hyperspectral Indices and Image Classifications for Agriculture and Vegetation
ISBN: 1138066036 ISBN-13(EAN): 9781138066038
Издательство: Taylor&Francis
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Цена: 23734.00 р.
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Описание: Evaluating the performance of various types of hyperspectral vegetation indices in characterizing agricultural crops, this volume discusses non-invasive quantification of foliar pigments, leaf nitrogen concentration of cereal crop, the estimation of nitrogen content in crops and pastures, forest leaf chlorophyll content, among other applications.

IoT and Analytics for Agriculture

Автор: Prasant Kumar Pattnaik; Raghvendra Kumar; Souvik P
Название: IoT and Analytics for Agriculture
ISBN: 9811391769 ISBN-13(EAN): 9789811391767
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book presents recent findings on virtually every aspect of wireless IoT and analytics for agriculture. 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. In turn, it addresses the latest innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of IoT and analytics for agriculture. In closing, it 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.

Agriculture 5.0: Artificial Intelligence, Iot and Machine Learning

Автор: Ahmad Latief, Nabi Firasath
Название: Agriculture 5.0: Artificial Intelligence, Iot and Machine Learning
ISBN: 0367646080 ISBN-13(EAN): 9780367646080
Издательство: Taylor&Francis
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Цена: 26796.00 р.
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Описание: Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming.

Beneficial Plant-microbial Interactions

Автор: M Bele?n Rodelas Gonza?lez; Jesus Gonzalez-Lopez
Название: Beneficial Plant-microbial Interactions
ISBN: 1466587172 ISBN-13(EAN): 9781466587175
Издательство: Taylor&Francis
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Цена: 29093.00 р.
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Описание:

Beneficial Plant-microbial Interactions: Ecology and Applications provides insight into the mechanisms underlying the interactions of plants and microbes, the ecological relevance and roles of these symbioses, the adaptive mechanisms of plant-associated microorganisms to abiotic stress and their contribution to plant stress tolerance, and the potential of these interactions as tools in agrobiotechnology. A team of authors with wide experience in the area contribute up-to-date reviews in nineteen chapters devoted to different ecological and applied aspects of the rhizobia-legume symbiosis, ecto- and endomycorrhizas, and plant associations with diazotrophic or adiazotrophic plant-growth promoting rhizobacteria. The book is intended for students, researchers and academic faculty members in the field of agrobiotechnology.

Hyperspectral remote sensing of vegetation /

Автор: Prasad S. Thenkabail
Название: Hyperspectral remote sensing of vegetation /
ISBN: 1138066257 ISBN-13(EAN): 9781138066250
Издательство: Taylor&Francis
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Цена: 76560.00 р.
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Описание: The second edition includes extensive discussions on data processing and how to implement data processing mechanisms in a standard, fast, and efficient manner. Written by global experts, each chapter focuses on specific applications, reviews existing "state-of-art" knowledge, highlights the advances made, and provides guidance for data usage.

IoT and WSN Applications for Modern Agricultural Advancements: Emerging Research and Opportunities

Автор: Mukherjee Proshikshya, Pattnaik Prasant Kumar, Panda Surya Narayan
Название: IoT and WSN Applications for Modern Agricultural Advancements: Emerging Research and Opportunities
ISBN: 1522590048 ISBN-13(EAN): 9781522590040
Издательство: Mare Nostrum (Eurospan)
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Цена: 25641.00 р.
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Описание: Currently, the demand by consumption of agricultural products may be predicted quantitatively; moreover, the variation of harvest and production by the change of a farm's cultivated area, weather change, disease, insect damage, etc. is a challenge that has led to improper control of the supply and demand of agricultural products. Advancements in IoT and wireless sensor networks in precision agriculture and the cloud computing technology needed to deploy them can be used to address and solve these issues. IoT and WSN Applications for Modern Agricultural Advancements: Emerging Research and Opportunities is an essential research book that focuses on the development of effective data-computing operations on agricultural advancements that are fully supported by IoT, cloud computing, and wireless sensor network systems and explores prospective applications of computing, analytics, and networking in various interdisciplinary domains of engineering. Featuring a range of topics such as power monitoring, healthcare, and GIS, this book is ideal for IT practitioners, farmers, network analysts, researchers, professionals, academicians, industry experts, and students.

Iot Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python

Автор: Mathur Puneet
Название: Iot Machine Learning Applications in Telecom, Energy, and Agriculture: With Raspberry Pi and Arduino Using Python
ISBN: 1484255488 ISBN-13(EAN): 9781484255483
Издательство: Springer
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Цена: 8384.00 р.
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Описание:

IoT Machine Learning Applications in Telecom, Energy, and Agriculture

CHAPTER 1: Getting Started: Software and Hardware Needed

CHAPTER 2: Overview of IoT and IIoT

CHAPTER 3: Using Machine Learning with IoT and IIoT in Python

CHAPTER 4: Using Machine Learning and IoT in Telecom, Energy, and Agriculture

CHAPTER 5: Preparing for the Case Studies

CHAPTER 6: Configuring IIoT Energy Meter

CHAPTER 7: Telecom Industry Case Study: Solving the Problem of Call Drops with IoT

CHAPTER 8: Energy Industry Case Study: Predictive Maintenance for an Industrial Machine

CHAPTER 9: Agriculture Industry Case Study: Predicting a Cash Crop Yield


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