System

A system comprising:

• circuitry configured to:
• acquire, via sensor devices coupled to a communication interface, acoustic data, image data, and environmental data related to an organism on a continuous or periodic basis;
• preprocess the acoustic data by performing sampling, normalization, noise reduction, and frequency-domain conversion to generate acoustic feature sequences, and preprocess the image data by performing decoding, resolution conversion, color-space conversion, and background separation to generate image feature sequences;
• input the acoustic feature sequences and the image feature sequences into an identification model comprising a machine learning model for time-series data analysis, and classify or cluster behavior patterns of the organism based on the feature sequences;
• construct and update, in a storage device, language system data encoding correspondence relationships between the behavior patterns and state data indicative of internal states of the organism;
• receive, from a terminal device, a prompt sentence comprising an interrogative sentence regarding a state of the organism, parse the prompt sentence to extract at least a target identifier, a time range, and a question intention;
• acquire, from the storage device, one or more behavior patterns and corresponding portions of the language system data matching the extracted target identifier and time range, and generate context data describing a current or past state of the target;
• generate a composite prompt data structure by combining the context data with the prompt sentence according to a predetermined prompt template;
• and
• transmit the composite prompt data structure to a generative neural network model to cause the generative neural network model to estimate the state of the organism based on the language system data and generate an answer sentence in natural language, and output the answer sentence to the terminal device.