The invention relates to the technical field of
electric energy meters, in particular to an automatic
electric energy meter reading method and
system based on
the Internet of Things, and the method comprises the following steps: based on an electronic
electric energy meter in a distribution box, collecting instantaneous current and
voltage, arranging a time stamp power sequence, comparing continuous sampling power data, and summarizing a change trend; and judging power change direction continuity to identify abnormal segments, screening uncovered sections to judge continuity, and adjusting interval identifiers to generate credible level distribution data. According to the method,
data acquisition and remote real-time communication of
time sequence synchronization are utilized, continuous sampling power change trend
combing is combined, and through dynamic trend comparison and intra-interval direction reversal behavior judgment, short-time fluctuation and power change abnormal sections can be identified, similarity screening and classification are performed on data intervals without
abnormality, and the accuracy of the abnormal data is improved. And after section classification, a credible level identifier is given in combination
with trend characteristics, a periodic distribution structure is obtained, and segmented discrimination of an abnormal
energy consumption interval and the dynamic
perception capability of an
energy consumption state are improved.