IoT (Internet of Things) Basic | Chapter 5: Data Handling and Cloud Integration by Prakhar Chauhan | Learn Smarter
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Chapter 5: Data Handling and Cloud Integration

Handling data efficiently is vital for successful IoT deployments. The chapter covers data collection, processing, transmission, and the role of cloud platforms in managing IoT data. It also discusses edge and fog computing, highlighting their benefits in reducing latency and improving the overall responsiveness of IoT systems.

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Sections

  • 5

    Data Handling And Cloud Integration

    This section discusses the importance of efficient data handling in IoT systems, covering data collection, processing, cloud platforms, and edge and fog computing.

    Learning Practice

  • 5.1

    Data Collection, Processing, And Transmission

    This section covers the processes of data collection, processing, and transmission within IoT systems, highlighting the role of edge and fog computing.

    Learning Practice

  • 5.1.1

    Data Collection

    This section covers how data is collected from IoT devices, processed, and transmitted to cloud platforms for analysis.

    Learning Practice

  • 5.1.2

    Data Processing

    Data processing in IoT encompasses the collection, processing, transmission, and integration of massive data generated by devices and sensors.

    Learning Practice

  • 5.1.3

    Data Transmission

    This section discusses the transmission of data in IoT systems from sensors to cloud platforms, focusing on collection, processing, and the impact of various factors on transmission.

    Learning Practice

  • 5.2

    Introduction To Iot Cloud Platforms

    This section introduces IoT cloud platforms, highlighting their role in data storage, analysis, and device management.

    Learning Practice

  • 5.2.1

    Aws Iot Core

    AWS IoT Core is a crucial platform providing secure cloud connectivity for IoT devices, enabling integration with various AWS services.

    Learning Practice

  • 5.2.2

    Microsoft Azure Iot Hub

    The Microsoft Azure IoT Hub enables efficient bidirectional communication and device management for IoT systems.

    Learning Practice

  • 5.2.3

    Google Cloud Iot Core

    Google Cloud IoT Core provides secure management of IoT devices and analytics capabilities to handle large volumes of data efficiently.

    Learning Practice

  • 5.3

    Data Storage And Analytics

    This section explores how IoT data is stored and analyzed, highlighting the roles of cloud platforms and computing paradigms.

    Learning Practice

  • 5.3.1

    Data Storage

    Data storage in IoT systems is essential for managing and analyzing the massive influx of sensor data efficiently.

    Learning Practice

  • 5.3.2

    Data Analytics

    This section covers the essential processes involved in collecting, processing, and analyzing data in IoT systems, as well as the role of cloud platforms in data management.

    Learning Practice

  • 5.4

    Fog And Edge Computing Concepts

    This section introduces the concepts of edge and fog computing, highlighting their benefits and use cases in IoT systems.

    Learning Practice

  • 5.4.1

    Edge Computing

    Edge computing processes data closer to where it is generated, enhancing speed, privacy, and bandwidth efficiency.

    Learning Practice

  • 5.4.2

    Fog Computing

    Fog computing extends cloud capabilities closer to the network edge, facilitating efficient data processing and dissemination in IoT systems.

    Learning Practice

  • 5.5

    Summary

    This section explores the critical processes of data handling in IoT systems, including collection, processing, transmission, and storage, emphasizing the role of cloud platforms.

    Learning Practice

References

Untitled document (18).pdf

Class Notes

Memorization

What we have learnt

  • The significance of IoT dat...
  • The importance of data proc...
  • Cloud platforms provide cri...

Final Test

Revision Tests