Abstract: To provide an information processing apparatus, an information processing system, and a trained model that perform analysis using information that is difficult to handle deductively with human reasoning. An information processing apparatus includes: a first acquisition unit that acquires a-posteriori information related to a predetermined target; an extraction unit that extracts a feature from the a-posteriori information; and an analysis unit that analyzes the target based on the feature.

Abstract: This learning device is provided with: a simulation execution unit that, by using electromagnetic field analysis simulation, determines a reflected wave spectrum obtained when electromagnetic waves are emitted from a reader to an identification target; and a machine learning unit that, by using training data in which the reflected wave spectrum calculated by the simulation execution unit and an attribute thereof are defined as a set, performs a training process on a learning model by machine learning. The simulation execution unit generates a plurality of the reflected wave spectra belonging to the same attribute by variously changing various parameters related to the identification target from reference parameters. The machine learning unit performs a training process on the learning model by machine learning by using, as training data, the plurality of reflected wave spectra obtained for each attribute.

Abstract: This learning device is provided with: a simulation execution unit that, by using electromagnetic field analysis simulation, determines a reflected wave spectrum obtained when electromagnetic waves are emitted from a reader to an identification target; and a machine learning unit that, by using training data in which the reflected wave spectrum calculated by the simulation execution unit and an attribute thereof are defined as a set, performs a training process on a learning model by machine learning. The simulation execution unit generates a plurality of the reflected wave spectra belonging to the same attribute by variously changing various parameters related to the identification target from reference parameters. The machine learning unit performs a training process on the learning model by machine learning by using, as training data, the plurality of reflected wave spectra obtained for each attribute.

Abstract: A state detection system includes a sensor (10) that includes an electromagnetic wave reflecting material (13) and a resonator (11) disposed adjacent to or integrally with the electromagnetic wave reflecting material (13), and that detects a state change of a surrounding object or surrounding environment as a change in its own electromagnetic wave reflection characteristic, a reader (20) that transmits an electromagnetic wave to the sensor (10), that receives a reflected wave of the electromagnetic wave, and that acquires reflected wave spectrum information of the sensor (10), and an analysis device (30) that estimates a current state of a detection target of the sensor (10) by applying information regarding reflected wave intensities at a plurality of frequency positions of the reflected wave spectrum to a learning model (30D) generated in advance on a basis of training data of a reflected wave spectrum for each state of the sensor (10).

Abstract: A chipless RFID tag can be scanned with high accuracy and robustness. A tag reader includes: a processing part configured to output information calculated from an emergent wave having an incident wave, as a radio wave irradiated to a tag (an object to be identified) emerged by way of the tag; and a determining part configured to identify attributes of the tag, using the information.