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The capacity of the edge to process data intelligently as close as possible to its source will result in an IoT that will help large numbers of people all over the world.
Fremont, CA: Edge computing will be vital to the progress of the Internet of Things (IoT). IoT devices produce massive quantities of data which is processed in the cloud, and the required data is sent back to the unit, instructing it on how to respond. However, due to latency, this setup is inefficient for time-critical applications like medical devices, which must process and respond to sensor data almost instantly. The use of the cloud often restricts installing IoT devices in areas with limited or no internet access.
Edge computing addresses these issues by migrating data processing from a central server to a location that is geographically closer to where it was collected, thanks to specialized accelerator chipsets developed by companies like Nvidia and Intel that can run highly advanced machine-learning algorithms far from the powerful centralized servers of the traditional cloud and, in some cases, on the device. This will significantly reduce latency. There are also software and hardware optimization strategies like model quantization to speed up cloud-based processing and minimize latency. These advancements would aid in the global adoption of innovative IoT products.
We will also be able to provide more localized control over our data thanks to edge computing. Federated learning is a technique that allows an algorithm to be taught across multiple servers or edge devices that store local data samples without having to share or exchange that data. This ensures that confidential data, such as medical or proprietary information, can be stored on the computer and held safe.
Expect more breakthroughs in medicine, transportation, industry, agriculture, and the home thanks to edge computing. The capacity of the edge to process data intelligently as close as possible to its source will result in an IoT that will help large numbers of people all over the world.
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