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There are various factors that influence the quality and quantity
of agricultural products; among them, weather conditions play the
most significant role in agriculture. More reliable weather
forecasting enables farmers to make important planting and
harvesting decisions that can enhance agricultural yield. Thus,
there is a dire need to combine all available modern technologies
and agricultural science for economic and environmentally
sustainable crop production. In this direction, artificial
intelligence (AI) serves as a budding solution in the domain of
agriculture practices. Artificial Intelligence Tools and
Technologies for Smart Farming and Agriculture Practices discusses
various tools and technologies that can be used in smart farming
and agriculture practice and explores the role of different
emerging technologies like the internet of things, big data,
machine learning, deep learning, and AI from agricultural
prospects. Covering key topics such as farming, pests, soil, and
weeds, this premier reference source is ideal for
environmentalists, farmers, agriculturalists, industry
professionals, researchers, academicians, scholars, practitioners,
instructors, and students.
Weather forecasting and climate behavioral analysis have
traditionally been done using complicated physics models and
accompanying atmospheric variables. However, the traditional
approaches lack common tools, which can lead to incomplete
information about the weather and climate conditions, in turn
affecting the prediction accuracy rate. To address these problems,
the advanced technological aspects through the spectrum of
artificial intelligence of things (AIoT) models serve as a budding
solution. Further study on artificial intelligence of things and
how it can be utilized to improve weather forecasting and climatic
behavioral analysis is crucial to appropriately employ the
technology. Artificial Intelligence of Things for Weather
Forecasting and Climatic Behavioral Analysis discusses practical
applications of artificial intelligence of things for
interpretation of weather patterns and how weather information can
be used to make critical decisions about harvesting, aviation, etc.
This book also considers artificial intelligence of things issues
such as managing natural disasters that impact the lives of
millions. Covering topics such as deep learning, remote sensing,
and meteorological applications, this reference work is ideal for
data scientists, industry professionals, researchers, academicians,
scholars, practitioners, instructors, and students.
The sudden outbreak of the COVID-19 pandemic has curbed human
lifestyle by imposing restrictions on regular daily movements that
had been taken for granted. Due to the pandemic, the welfare
segment has received more attention, and every possible effort is
being made to prioritize the services at the top. This can be made
possible while using the latest tools, technologies, and resources
that impact the human culture and welfare of well-being. Novel
methods and devices that make the welfare services more efficient,
adaptive, transparent, and cost-effective need to be explored. The
Handbook of Research on Lifestyle Sustainability and Management
Solutions Using AI, Big Data Analytics, and Visualization offers
extensive research on lifestyle management and services that
contribute towards indication, detection, conduction, protection,
and technological enhancement including machine learning, deep
learning, artificial intelligence, big data analytics, and
visualization. It also provides mechanisms that can improve
lifestyle monitoring and help in increasing the immunity of the
human body. Covering topics such as big data, robot therapy, and
wearable technology, it is ideal for students, researchers,
technologists, IT specialists, computer engineers, systems
engineers, data scientists, doctors, hospital administrators,
engineers, academicians, and technology providers.
Weather forecasting and climate behavioral analysis have
traditionally been done using complicated physics models and
accompanying atmospheric variables. However, the traditional
approaches lack common tools, which can lead to incomplete
information about the weather and climate conditions, in turn
affecting the prediction accuracy rate. To address these problems,
the advanced technological aspects through the spectrum of
artificial intelligence of things (AIoT) models serve as a budding
solution. Further study on artificial intelligence of things and
how it can be utilized to improve weather forecasting and climatic
behavioral analysis is crucial to appropriately employ the
technology. Artificial Intelligence of Things for Weather
Forecasting and Climatic Behavioral Analysis discusses practical
applications of artificial intelligence of things for
interpretation of weather patterns and how weather information can
be used to make critical decisions about harvesting, aviation, etc.
This book also considers artificial intelligence of things issues
such as managing natural disasters that impact the lives of
millions. Covering topics such as deep learning, remote sensing,
and meteorological applications, this reference work is ideal for
data scientists, industry professionals, researchers, academicians,
scholars, practitioners, instructors, and students.
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