Internet of Things and Big Data Analytics for a Green Environment

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Internet of Things and Big Data Analytics for a Green Environment

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  • 製本 Hardcover:ハードカバー版/ページ数 338 p.
  • 言語 ENG
  • 商品コード 9781032649825
  • DDC分類 307.1416

Full Description

This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field.

Key Features:

• Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics.

• Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment.

• Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment.

• Provides a systematic overview of the state-of-the-art research efforts.

• Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment.

This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.

Contents

Chapter 1: IoT-Enabled Sustainable Urban Growth Management. Chapter 2: Enhancing IoT Data Quality Validation in Medical Field through Big Data. Analytics. Chapter 3: Machine Learning based Driver Assistance System Ensuring Road Safety for Smart Cities. Chapter 4: Privacy and Security Issues in Big Data and Internet of Things. Chapter 5: Big Mart Sales Forecasting: A case Study of Big Data Analytics and Machine Learning. Chapter 6: Challenges and Opportunities for Cleaner Energy and Green Environment. Chapter 7: A Text-based Approach for Product Clustering and Recommendation in E-Commerce using Machine Learning. Chapter 8: How Multimodal AI and IoT are Shaping the Future of Intelligence. Chapter 9: Digitally-Enabled Labor Market: The Dark Side of Digital Transformation. Chapter 10: Artificial Intelligence Capability for Auditing. Chapter 11: Smart Green Cities Using IoT-Based Deep Reinforcement Learning Energy Management. Chapter 12: Technology Driven Learning System in Higher Education: A Bibliometric Analysis. Chapter 13: A Time-varying JSON Data Model and its Query Language for the Management of Evolving Green Things in IoGT-based Systems. Chapter 14: Enhancing Financial Transaction Security: A Deep Learning Approach for E-Payment Fraud Detection. Chapter 15: Efficient Solar Radiation Prediction through Adaptive Neighborhood Rough Set-Based Feature Selection in Meteorological Streaming Data in Errachidia, Morocco. Chapter 16: Artificial Intelligence-Empowered Date Palm Disease and Pest Management: Current Status, Challenges, and Future Perspectives. Chapter 17: Trends in Green Technology for Clean Energy. Chapter 18: Enhancing Wireless Network Performance Through High-Quality Fiber Optic Deployment in Highway Environments.

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