Living state detection method based on electricity consumption behavior

Abstract

The invention relates to a living state detection method based on power consumption behaviors. The life state detection method based on the electricity consumption behavior comprises the following steps: S1, acquiring historical electricity consumption data of a target time period; s2, constructing a total power consumption model, an equipment load identification model and an equipment power consumption habit model according to the historical power consumption data; s3, reading the current power consumption data of the target time period; s4, comparing the current power consumption data with the total power consumption model; s5, judging whether the current total electricity consumption of the target time period is abnormal or not; s6, constructing a current electricity utilization diagram structure according to the current electricity utilization data, and performing load identification on the current electricity utilization diagram structure through an equipment load identification model to generate a current load identification result; s7, comparing the current load identification result with the equipment power utilization habit model; s8, judging whether the current power consumption behavior in the target time period is abnormal or not; and S9, performing exception report. The method has the advantages of high identification accuracy, high detection speed and low data scheduling difficulty.

Description

technical field [0001] The present invention relates to the technical field of power monitoring, in particular to a method for detecting living conditions based on power consumption behavior. Background technique [0002] With the continuous development of society, the problem of population aging is gradually aggravating, and the number of empty-nesters is increasing. Elderly people who are alone at home are often difficult to inform the outside world if an accident occurs, resulting in more serious consequences. Therefore, paying attention to the living conditions of the elderly and reporting their abnormal conditions as soon as possible is an effective measure to ensure the safety of the elderly living alone. [0003] In the existing monitoring technologies for the living conditions of the elderly, the commonly used methods are mainly based on the comprehensive consideration of data from multiple meters such as water meters, electricity meters, and gas meters. , and compa...

AI Technical Summary

Problems solved by technology

This method has certain limitations: first, different data come from different tables and different companies, and it is difficult to carry out comprehensive scheduling of various data in daily life; It is built based on the overall category of data, the data granularity is relatively rough, and the false positive rate is high

It is obvious that this method as a whole is based on coarse-grained electricity consumption data for life status detection, which is prone to abnormal false alarms, and the detection process is cumbersome, time-consuming and expensive

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