System

A system comprising:

• circuitry configured to
• receive, via a communication interface coupled to a packet-switched network, sensor data acquired by a detection apparatus and converted into digital data representing time-stamped measurements,
• store the digital data as structured records in a storage device, each record comprising an identifier field, a measurement type field, a value field, a unit field, and a timestamp field,
• retrieve, from the storage device, historical records associated with the identifier over a configurable time window,
• preprocess the digital data and the historical records by complementing missing values and removing outlier values,
• extract feature quantities for each predetermined sub-window, the feature quantities comprising statistical quantities and time-variation quantities,
• input the feature quantities into a trained machine learning model to calculate state indices and compare the state indices with threshold values to detect an abnormal state that persists for a predetermined duration,
• construct a prompt sentence that embeds the feature quantities, the state indices, attribute information, baseline values, and trend indicators into a natural-language template,
• transmit the prompt sentence to a generative neural network model comprising a transformer architecture and receive feedback information, and
• transmit output data derived from the feedback information to a terminal device and store, in the storage device, a correspondence record associating the feedback information with the prompt sentence and the state indices.

A method comprising:

• receiving, by circuitry via a communication interface coupled to a packet-switched network, sensor data acquired by a detection apparatus and converted into digital data;
• storing the digital data as structured records in a storage device and retrieving, from the storage device, historical records associated with an identifier of a source of the sensor data;
• executing, by the circuitry, statistical analysis on the digital data and the historical records, the statistical analysis comprising calculation of statistical values, time-series analysis, and anomaly detection, to generate evaluation data;
• constructing a prompt sentence as structured input that includes the evaluation data, attribute information associated with the identifier, and trend indicators derived from the historical records;
• transmitting the prompt sentence to a generative neural network model and receiving, from the generative neural network model, feedback information generated in response to the prompt sentence;
• transmitting output data derived from the feedback information to a terminal device via the communication interface;
• and
• storing, in the storage device, a correspondence record that associates the feedback information with the prompt sentence and the evaluation data.