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.
Author(s): Govind Singh Patel, Amrita Rai, Nripendra Narayan Das, R.P. Singh
Publisher: CRC Press
Year: 2021
Language: English
Pages: 244
City: Boca Raton
Cover
Half Title
Title Page
Copyright Page
Table of Contents
List of Abbreviations
List of Symbols
1 Machine Learning and Deep Learning in Agriculture
2 Descriptive and Predictive Analytics of Agricultural Data Using Machine Learning Algorithms
3 Discrimination Between Weed and Crop Via Image Analysis Using Machine Learning Algorithm
4 Bio-Inspired Optimization Algorithms for Machine Learning in Agriculture Applications
5 Agricultural Modernization with Forecasting Stages and Machine Learning
6 Classification of Segmented Image Using Increased Global Contrast for Paddy Plant Disease
7 Iot in Agriculture: Survey on Technology, Challenges and Future Scope
8 Role of Iot in Sustainable Farming
9 Smart Farming: Crop Models and Decision Support Systems Using Iot
10 Smart Irrigation in Farming Using Internet of Things
11 Automation Systems in Agriculture Via Iot
12 A Complete Automated Solution for Farm Field and Garden Nurturing Using Internet of Things
13 Machine Intelligence Techniques for Agricultural Production: Case Study with Tomato Leaf Disease Detection
14 Clock Signal and Its Attribute For Agriculture