Cloud computing is in the core network of the data center, collect terminal data through layer by layer network equipment, rely on powerful storage and computing ability to carry on big data analysis. Edge computing refers to the ability of computing in devices close to the data source to analyze the real time and short period data, so that the local data can be processed and executed intelligently in real time and efficiently.
At the same time can alleviate the network data flow and cloud workload. Cloud computing is more appropriate when huge amounts of data need to be stored and analyzed. For example, artificial intelligence (AI) which requires a large amount of data input is trained offline, and these data should be validated and perfected by appropriate training methods.
Edge computing can be said to be a supplement and optimization to cloud computing. In many industries, where conditions are poor and equipment is scattered, it is difficult to transmit large amounts of data in real time, which is more suitable for edge computing. Taking wind farm as an example, the field equipment with edge computing ability can collect and analyze the data in real time, make judgment in time and adjust the fan to collect more energy. Because the whole process is done locally, processing speed is much faster than using cloud computing.
At present, only about 3% of the data in the industrial production line are useful. After filtering and processing by edge equipment, the value of the data reaching the cloud is higher, and the corresponding calculation and analysis process will be more efficient.
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