IoT System Data Quality Optimization: Research Status and Problem Analysis

The data processing problem is the continuous generation of time series data containing information on faults or anomalies. These pieces of information can be described by physical models. But the means of manual analysis is not enough to solve the problem. Therefore, on the basis of the experience of the IOT communication engineering, it is inevitable to develop a physical model which characterizes the performance and abnormal state of the system and machine learning to automatically analyze and process the data quality optimization problem. The development aims to solve the data quality optimization technology of the IoT system for energy and power services, and take into account the requirements of real-time processing indicators of massive data, laying the foundation for the introduction of service layer machine learning model.