“…According to the reconstruction error between the original data and the reconstructed data, the power consumption abnormal data points are detected. Liu et al [5] proposed an optimization scheme for energy consumption and life of smart watt-hour meters based on edge computing. The edge server is used to receive and upload smart watt-hour meter data, and the influence factors of energy consumption and life are extracted by convolutional neural network (CNN) at the edge, and the K-means clustering algorithm is used to predict the change of electricity consumption, so as to obtain the optimization model of energy consumption and life.…”