MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS
As companies globally realize the revolutionary potential of the Io T, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the Io T’s potential and this book brings clarity to the issue.
Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation Io T devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.
Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an Io T environment. The most common use cases for machine learning and Io T data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with Io T in these various application domains.
As companies globally realize the revolutionary potential of the Io T, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the Io T’s potential and this book brings clarity to the issue.
Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation Io T devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.
Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an Io T environment. The most common use cases for machine learning and Io T data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with Io T in these various application domains.
€164.99
عن المؤلف
AudienceScholars and scientists working in artificial intelligence and electronic engineering, industry engineers, software and computer hardware specialists.
Shalli Rani, Ph D is an associate professor in the Department of CSE, Chitkara University, Punjab, India.
R. Maheswar, Ph D is the Dean and associate professor, School of EEE, VIT Bhopal University, Madya Pradesh, India.
G. R. Kanagachidambaresan, Ph D associate professor, Department of CSE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Tamil Nadu, India.
Sachin Ahuja, Ph D is a professor in the Department of CSE, Chitkara University, Punjab, India.
Deepali Gupta, Ph D is a professor, Department of CSE, Chitkara University, Punjab, India.
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لغة الإنجليزية ● شكل EPUB ● صفحات 304 ● ISBN 9781119763475 ● حجم الملف 10.2 MB ● محرر Shalli Rani & R. Maheswar ● الناشر John Wiley & Sons ● نشرت 2022 ● الإصدار 1 ● للتحميل 24 الشهور ● دقة EUR ● هوية شخصية 8317260 ● حماية النسخ Adobe DRM
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