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.
Enroll to start learning
You've not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- The significance of IoT data collection from multiple sensors.
- The importance of data processing before transmission to ensure quality.
- Cloud platforms provide critical infrastructure for data analysis and management.
- Edge computing reduces latency by processing data at the source.
- Fog computing enhances scalability and fault tolerance in IoT architectures.
Key Concepts
- -- Data Collection
- The process of gathering raw data from IoT sensors which monitor various environmental parameters.
- -- Data Processing
- Transforming raw data into a usable format by filtering noise and applying logic before transmission.
- -- Cloud Platform
- Infrastructure that supports data storage, analysis, and management for IoT applications.
- -- Edge Computing
- A computing paradigm that processes data at or near the source rather than relying on a centralized cloud.
- -- Fog Computing
- A decentralized approach that extends cloud capabilities to the network edge for better processing and storage.
Additional Learning Materials
Supplementary resources to enhance your learning experience.