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.

"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"--

"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.

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.

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

This book addresses the challenges for developing and emerging trends in Internet-of-Things (IoT) for smart agriculture platforms. It also describes data analytics & machine learning, cloud architecture, automation & robotics and aims to overcome existing barriers for smart agriculture with commercial viability. 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. The book 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. This volume will be helpful for engineering and technology experts and researchers, as well as for policy-makers.

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.