A method for estimating one or more loads by an energy meter including a load estimation model based on a neural network, comprising steps of: [a] the energy meter sequentially generating multiple pieces of sampled supply electric power information by sampling information on electric power, supplied to a customer through one or more input lines of a distribution board, based on a predetermined sampling rate; [b] the energy meter sequentially inputting the multiple pieces of the sampled supply electric power information to the load estimation model and instructing the load estimation model to output load information which is a result of distinguishing each of the loads, being operated by the customer at a t-th time, wherein t is an integer bigger than or equal to 2, based on [t-k]-th sampled supply electric power information to t-th sampled supply electric power information, wherein k is an integer bigger than or equal to 1 and less than t, respectively corresponding to a [t-k]-th time to the t-th time, among the multiple pieces of the sampled supply electric power information; and [c] the energy meter [i] transmitting the load information and information on an amount of the electric energy to a data management server, wherein the information on the amount of the electric energy is acquired by integrating the electric power supplied to the customer during a time period including a specific period between the [t-k]-th time and the t-th time through the input lines, and [ii] instructing the data management server to monitor at least part of the information on the amount of the electric energy consumed by the customer, information on each sub-electric power for each of the loads, and information on each amount of sub-electric energy for each of the loads. [a] the energy meter sequentially generating multiple pieces of sampled supply electric power information by sampling information on electric power, supplied to a customer through one or more input lines of a distribution board, based on a predetermined sampling rate; [b] the energy meter sequentially inputting the multiple pieces of the sampled supply electric power information to the load estimation model and instructing the load estimation model to output load information which is a result of distinguishing each of the loads, being operated by the customer at a t-th time, wherein t is an integer bigger than or equal to 2, based on [t-k]-th sampled supply electric power information to t-th sampled supply electric power information, wherein k is an integer bigger than or equal to 1 and less than t, respectively corresponding to a [t-k]-th time to the t-th time, among the multiple pieces of the sampled supply electric power information; and [c] the energy meter [i] transmitting the load information and information on an amount of the electric energy to a data management server, wherein the information on the amount of the electric energy is acquired by integrating the electric power supplied to the customer during a time period including a specific period between the [t-k]-th time and the t-th time through the input lines, and [ii] instructing the data management server to monitor at least part of the information on the amount of the electric energy consumed by the customer, information on each sub-electric power for each of the loads, and information on each amount of sub-electric energy for each of the loads. <EOS>