What does edge computing primarily do with data captured by sensors?

Edge computing is designed to analyze data at or near the source of data generation, which in this case involves the sensors. By processing data locally, it reduces the latency and bandwidth needed for sending vast amounts of data to a central server or cloud. Analyzing the data before it is sent to a backhaul network allows for timely decisions and actions based on real-time insights, optimizing the use of network resources.

In scenarios where immediate feedback is vital, such as in industrial settings or smart cities, edge computing ensures that only the relevant data is transmitted, typically reducing the volume of data that needs to be sent. This localized processing helps in minimizing response times and enhancing the efficiency of applications involved in the Internet of Things (IoT). This approach is particularly beneficial for applications requiring fast reaction times, like predictive maintenance or real-time monitoring.