N. L. Kushwaha – författare

This book explains the challenges for efficient sustainable surface and groundwater development and management with the focus on India and other countries, providing a stable output presentation by using machine learning data mining methods, and modeling. It is a combination of machine learning, modeling, google earth engine, climate data modeling, remote sensing and GIS techniques, surface water modeling, AHP modeling, groundwater quality analysis, aquifer mapping, land use and land cover analysis, forecasting of water and rainfall and so on, its use to sustainable development, planning, and management of groundwater purposes in India and other countries. The main purpose of this book will develop better outlines for the development of surface and groundwater and management in the semi-arid region climate, which supports the Sustainable Development Goals (SDGs) in India, especially on sustainable surface water and groundwater resources management.This book provides amultidisciplinary overview for the faculty members, administrators scientists, policymakers, social science, and professionals involved in the various aspects of sustainable groundwater development, planning, and management.

This book explains the challenges for efficient sustainable surface and groundwater development and management with the focus on India and other countries, providing a stable output presentation by using machine learning data mining methods, and modeling. It is a combination of machine learning, modeling, google earth engine, climate data modeling, remote sensing and GIS techniques, surface water modeling, AHP modeling, groundwater quality analysis, aquifer mapping, land use and land cover analysis, forecasting of water and rainfall and so on, its use to sustainable development, planning, and management of groundwater purposes in India and other countries. The main purpose of this book will develop better outlines for the development of surface and groundwater and management in the semi-arid region climate, which supports the Sustainable Development Goals (SDGs) in India, especially on sustainable surface water and groundwater resources management.This book provides amultidisciplinary overview for the faculty members, administrators scientists, policymakers, social science, and professionals involved in the various aspects of sustainable groundwater development, planning, and management.

As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is required to understand these technological developments. This book explores the applications of various artificial intelligence techniques by identifying and describing technical, functional, and non-functional future technologies for smart farming and agriculture. The book also presents practical application opportunities for the resolution of real-world problems, including contributions from precision irrigation, greenhouse data, livestock monitoring, automation, IoT ecosystems for agriculture, cloud computing, mobile robots for precision agriculture, remote sensing applications, anddata mining. In addition, this book provides summary information about different soilless techniques such as hydroponics, aeroponics, and aquaponics, among others. This book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.

As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is required to understand these technological developments. This book explores the applications of various artificial intelligence techniques by identifying and describing technical, functional, and non-functional future technologies for smart farming and agriculture. The book also presents practical application opportunities for the resolution of real-world problems, including contributions from precision irrigation, greenhouse data, livestock monitoring, automation, IoT ecosystems for agriculture, cloud computing, mobile robots for precision agriculture, remote sensing applications, anddata mining. In addition, this book provides summary information about different soilless techniques such as hydroponics, aeroponics, and aquaponics, among others. This book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.