《计算机科学导论》课件Unit 16Internet of Things, Cloud Computing and Data Science教学讲义.pptVIP

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《计算机科学导论》课件Unit 16Internet of Things, Cloud Computing and Data Science教学讲义.ppt

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《计算机科学导论》课件Unit 16Internet of Things, Cloud Computing and Data Science教学讲义.ppt

Unit 16 Internet of Things, Cloud Computing and Data Science * 16-1 Introduction 16-2 Opportunities in IoT, Cloud, and Data Science 16-3 Challenges and Research Directions 16-4 IoT Applications 16-5 Cloud Application Service Models 16-6 Cloud Application Deployment Models 16-7 Big Data Tools and Techniques 16-8 Integration of IoT, Cloud Computing, and Big Data 16-9 References and Recommended Reading 16-10 Key Terms 16-11 Summary 16-12 Practice Set OUTLINE * Understand the concepts of Internet of Things (IoT), cloud computing, and data science. After reading this chapter, you are supposed tobe able to: OBJECTIVES Show how the integration of IoT, cloud, and big data leads to the emerging smart ecosystem. Recognize opportunities, challenges, and research directions in IoT, cloud computing, and data science. Describe the tools and techniques to design, develop, and Implement big data applications in clouds. Describe IoT applications. Describe cloud service models: SaaS, PaaS, and IaaS, and deployment models: private, community, public, and hybrid. * 5-1 Introduction Internet of Things (IoT), cloud computing, and data science: Creation of new technological breakthroughs Transformation from digital to real-time intelligence Revolution of our globe Figure 16.1 Pilotless plane * Internet of Things Figure 16.2 Enabling technologies of IoT * Data science Data scientists: Visualize and interpret rich data sets; Manage large big data sets; Ensure consistency of datasets; Build mathematical models of datasets. Interdisciplinary field that incorporates theories and methods from many fields within the broad areas of statistics, mathematics, information science, and computer science. * Data science Data science and big data sometimes used interchangeably. Primary difference is their perspective. Data science begins with the data use, whereas big data begins with the data characteristics. Data science is intricately intertwined with big data technologies, and data-d