Edge computing is a distributed computing architecture that brings data processing closer to the data source. It aims to reduce latency, bandwidth usage, and power consumption by processing data where it is generated, rather than sending it to a centralized data center.

Key Concepts

  • Data Processing: Edge computing processes data at the edge of the network, reducing the need to send data to a centralized location for processing.
  • Latency: By processing data closer to the source, edge computing can significantly reduce latency.
  • Bandwidth: Edge computing can reduce the amount of data that needs to be sent to a central location, thereby conserving bandwidth.
  • Power Consumption: Processing data at the edge can also reduce power consumption, as data does not need to be transported over long distances.

Use Cases

  • Industrial IoT: Edge computing is ideal for industrial IoT applications, where processing data locally can improve efficiency and reduce downtime.
  • Smart Cities: In smart cities, edge computing can be used to process data from sensors and devices in real-time, enabling better management of city services.
  • Healthcare: In healthcare, edge computing can be used to process patient data at the point of care, improving diagnosis and treatment outcomes.

Edge Computing Diagram

Learn More

For a deeper understanding of edge computing, check out our comprehensive guide on Edge Computing in the Internet of Things.


The edge computing landscape is rapidly evolving, and staying informed is crucial. Keep up with the latest trends and advancements by exploring our extensive technology resources.