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
Agricultural Informatics: Automation Using the IoT and Machine Learning
β Scribed by Amitava Choudhury, Arindam Biswas, Manish Prateek, Amlan Chakrabarti (editors)
- Publisher
- Wiley-Scrivener
- Year
- 2021
- Tongue
- English
- Leaves
- 304
- Series
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
π SIMILAR VOLUMES
<p><span>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 agricult
Automate data and model pipelines for faster machine learning applications Key Features Build automated modules for different machine learning components Understand each component of a machine learning pipeline in depth Learn to use different open source AutoML and feature engineering platforms Bo
<p><span>Healthcare Solutions Using Machine Learning and Informatics</span><span> covers novel and innovative solutions for healthcare that apply machine learning and biomedical informatics technology. The healthcare sector is one of the most critical in society. This book presents a series of artif
<p><i>Machine Learning, Big Data, and IoT for Medical Informatics</i> focuses on the latest techniques adopted in the field of medical informatics.</p> <p>In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In
<p><strong>Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning</strong> provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduc