US Patent Application 18351244. ARTIFICIAL INTELLIGENT ENHANCED DATA SAMPLING simplified abstract
Contents
ARTIFICIAL INTELLIGENT ENHANCED DATA SAMPLING
Organization Name
Inventor(s)
Katherine Zhao of Mountain View CA (US)
ARTIFICIAL INTELLIGENT ENHANCED DATA SAMPLING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18351244 titled 'ARTIFICIAL INTELLIGENT ENHANCED DATA SAMPLING
Simplified Explanation
- The patent application describes a method for monitoring the operational characteristic of a data communication device within a network. - The method involves sampling the operational characteristic of the device at a fine-grain sample rate over a first sampling interval to produce fine-grain samples. - A machine learning algorithm is then trained using the fine-grain samples, the fine-grain sample rate, and a coarse-grain sample rate that is lower than the fine-grain sample rate. - The operational characteristic of the device is then sampled at the coarse-grain sample rate over a second sampling interval to produce coarse-grain samples. - The machine learning algorithm is used to process the coarse-grain samples and enhance their accuracy, producing accuracy-enhanced samples of the operational characteristic of the device.
Original Abstract Submitted
Monitoring an operational characteristic of a data communication device within a network includes sampling an operational characteristic of the data communication device at a fine-grain sample rate over a first sampling interval to produce fine-grain samples of the operational characteristic of the data communication device, training a machine learning algorithm using the fine-grain samples of the operational characteristic of the data communication device, the fine-grain sample rate, and a coarse-grain sample rate that is less than the fine-grain sample rate, sampling the operational characteristic of the data communication device at the coarse-grain sample rate over a second sampling interval to produce coarse-grain samples of the operational characteristic of the data communication device, and using the machine learning algorithm to process the coarse-grain samples of the operational characteristic of the data communication device to produce accuracy-enhanced samples of the operational characteristic of the data communication device.
