System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, a plurality of time-series image data frames captured by an imaging sensor mounted on a moving body and transmitted from a terminal device, and acquire positioning coordinates from a positioning module substantially simultaneously with the image data frames, synchronize the image data frames with the positioning coordinates based on temporal identifiers, and store position-tagged visual data records in a storage device in association with region-classification metadata;
• apply a convolutional neural network model comprising a plurality of convolutional layers, normalization layers, and detection heads to the position-tagged visual data records to extract multidimensional feature tensors representing environmental characteristics including road-shape information, traffic-control information, pedestrian-space information, obstacle information, and illumination information;
• execute inference processing using a trained machine learning model on the multidimensional feature tensors to perform comparative analysis between data records classified as a first region type and data records classified as a second region type, and derive structural anomaly candidates and structural safety-contributing candidates for each geographic segment;
• generate analysis-context data structures comprising explanatory-text information and comparison information based on the structural anomaly candidates, the structural safety-contributing candidates, the positioning coordinates, and the multidimensional feature tensors, and construct a natural-language prompt sentence by encoding the analysis-context data structures into a formatted text input for a transformer-based generative neural network model;
• transmit the natural-language prompt sentence to the transformer-based generative neural network model, receive response data comprising generated natural-language output, parse the response data to extract explanation information and structured remediation-plan records, and associate each remediation-plan record with corresponding positioning coordinates and analysis-context data structures;
• execute prioritization processing and category-classification processing on the remediation-plan records based on a computed severity index, an occurrence-frequency value, and stored user-evaluation feedback data, and generate ranked output data mapped to geographic coordinate positions;
• and
• transmit the ranked output data to the terminal device via the communication interface for rendering in a geospatial visualization format overlaid on a digital map display.

A method performed by circuitry of a server coupled to a packet-switched network via a communication interface, the method comprising:

• receiving, via the communication interface, a plurality of image data frames transmitted from a terminal device over the packet-switched network, each image data frame being associated with positioning data;
• associating the plurality of image data frames with the positioning data to generate position-tagged data records, and storing the position-tagged data records in a storage device in association with region-classification metadata indicating a category of a geographic area corresponding to each image data frame;
• applying a trained inference model to the position-tagged data records to extract feature data representing characteristics of environments depicted in the image data frames;
• executing comparative analysis processing on the extracted feature data between data records having a first region classification and data records having a second region classification to derive a set of indicator values for each geographic segment;
• generating a natural-language prompt sentence based on the indicator values and the feature data, and transmitting the natural-language prompt sentence to a generative neural network model to obtain response data comprising generated natural-language output;
• parsing the response data to extract structured output records, and executing prioritization processing on the structured output records based on at least one of a severity value, a frequency value, and stored feedback data to generate ranked output data;
• and
• transmitting the ranked output data to the terminal device via the communication interface.