Agricultural Informatics


Book Description

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world's economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc. Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.




Agricultural Informatics


Book Description

Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world's economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc. Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries.




Agro-Informatics


Book Description

The book will provide the basic and fundamental knowledge of understanding the concepts of Bioinformatics




Agricultural and Environmental Informatics, Governance and Management


Book Description

"This book is a state-of-the-art reference book that explores how rural policymakers and stakeholders can use information and communication technologies to sustainably manage agricultural and natural resources"--Provided by publisher.







Agro-geoinformatics


Book Description

This volume collects and presents the fundamentals, tools, and processes of utilizing geospatial information technologies to process remotely sensed data for use in agricultural monitoring and management. The issues related to handling digital agro-geoinformation, such as collecting (including field visits and remote sensing), processing, storing, archiving, preservation, retrieving, transmitting, accessing, visualization, analyzing, synthesizing, presenting, and disseminating agro-geoinformation have never before been systematically documented in one volume. The book is edited by International Conference on Agro-Geoinformatics organizers Dr. Liping Di (George Mason University), who coined the term “Agro-Geoinformatics” in 2012, and Dr. Berk Üstündağ (Istanbul Technical University) and are uniquely positioned to curate and edit this foundational text. The book is composed of eighteen chapters that can each stand alone but also build on each other to give the reader a comprehensive understanding of agro-geoinformatics and what the tools and processes that compose the field can accomplish. Topics covered include land parcel identification, image processing in agricultural observation systems, databasing and managing agricultural data, crop status monitoring, moisture and evapotranspiration assessment, flood damage monitoring, agricultural decision support systems and more.




Digital FAO – The Year of Excellence


Book Description

Throughout the Year of Excellence 2023, Digital FAO has redoubled its efforts to upscale the Organization's digital capabilities, capacity -building and advisory services needed to enable and accelerate targeted interventions with actionable and concrete results worldwide, leaving no one behind. Digital technology is at the nexus of multiple Sustainable Development Goals (SDGs), including the eradication of poverty, climate action and environmental protection, ending hunger, and improving nutrition and access to healthy diets. In this light, this publication highlights FAO strong digital cooperation, as well as the significant developments in the technology domain, with further acceleration of digital transformation globally, including a strong focus on agrifood systems. It aims to provide further insights into the strategic direction, achievements and efforts of Digital FAO, with the overall objective to achieve FAO four betters and the Sustainable Development Goals at their largest.




Environmental and Agricultural Informatics


Book Description

"This book examines the design, development, and implementation of complex agricultural and environmental information systems to quickly process and access environmental data in order to make informed decisions for the protection of the environment"--




Library of Congress Subject Headings


Book Description




Management of Data in AI Age


Book Description

This book is a compilation of contributed works on management of data in the age of artificial intelligence. The AI technologies have changed the way the businesses do manage themselves in modern times. It becomes much more important to manage the data a business owns when the same can be collated and used by the allied AI technologies for forming business decisions. This book highlights how AI and machine learning can help businesses categorise and manage their organizational data. The book introduces how small businesses can benefit from AI technologies for their data management with limited budgets. The book advocates for making AI processes to be core part of consumer experience and support management within the businesses. As a unique feature, this book also goes to make an awareness as to how human brain can use AI’s deep learning capabilities to make reflective decisions. The book also introduces as to how big data and big data analytics can help agriculture and farm management sector. It is hoped that the readership will find this book useful in the areas of big data management, machine learning and data decisions, AI technologies for small businesses, usage of AI in emerging sectors and those areas where data needs to managed in an environment of automation.