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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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.