Abstract: A moving target tracking device includes a position information creation unit that creates camera position information indicating adjacency relationships of a plurality of reference cameras and a plurality of pivoting cameras, a tracking target analysis unit that detects traveling information indicating a speed and a traveling direction of a moving target, a tracking score calculation unit that calculates a tracking score indicating a proportion at which the moving target has been able to be captured in the entire tracking section, a machine learning unit that creates, as record information, a control result obtained by a learning device that has learned a control value of each pivoting device corresponding to the traveling information such that the tracking score becomes higher, and a control information creation unit that creates control information by using the control value acquired with reference to the record information.

Abstract: This device control value generation device comprises: a control value generation unit that generates a device control value for a plurality of control target devices; a learning data management unit that acquires items of learning data represented by the device control values and scores, and stores the same in a learning data DB for each device control factor pattern, which represent the device control values in accordance with the division range of external factors; a situation classification unit that extracts the external factor influencing a reward fluctuation and defines classifications; and a learning model management unit that uses learning data for each defined classification and generates a learning model of each classification by means of carrying out reinforcement learning such that a prescribed reward is fulfilled.

Abstract: A tracking device includes a recognition model storage unit, which stores a recognition model containing one or more feature quantities of a tracking target on a tracking target basis, a candidate detection unit, which extracts the tracking target from images captured by a monitoring camera associated with the tracking device by using the recognition model, a model creation unit, which updates the recognition model in the recognition model storage unit by adding a new feature quantity detected from the extracted tracking target to the recognition model used by the candidate detection unit to extract the tracking target, and a communication unit, which distributes the recognition model updated by the tracking device to another device that performs monitoring based on another monitoring camera located within a predetermined range from the monitoring camera associated with the tracking device.

Abstract: A control target device selection apparatus (1) includes: a situation classification unit (122) for extracting an external factor affecting a reward as a component and defining a situation for controlling a control target device (5) as a classification for each divided range; a learning data management unit (123) for storing learning data for each device control factor pattern in a learning data DB; a learning model management unit (124) for generating a learning model for each classification, a non-involved device specification unit (1271) for determining non-involved devices and a range of classification of non-involved devices; and, with respect to the range of the non-involved classification, a device control unit (130) for transmitting a device control value to each control target device (5) excluding the non-involved device.

Abstract: A moving target tracking device includes a position information creation unit that creates camera position information indicating adjacency relationships of a plurality of reference cameras and a plurality of pivoting cameras, a tracking target analysis unit that detects traveling information indicating a speed and a traveling direction of a moving target, a tracking score calculation unit that calculates a tracking score indicating a proportion at which the moving target has been able to be captured in the entire tracking section, a machine learning unit that creates, as record information, a control result obtained by a learning device that has learned a control value of each pivoting device corresponding to the traveling information such that the tracking score becomes higher, and a control information creation unit that creates control information by using the control value acquired with reference to the record information.

Abstract: A data collection apparatus (10) in a traffic transfer system (100) collects and transfers low-bit-rate traffic data from an IoT device, and transfers high-bit-rate traffic data in an identified area. A traffic transfer apparatus (20) performs determination as to whether or not a service-supported event occurs, by inputting the low-bit-rate traffic data into a learner (200) and, when occurrence is determined, acquires and transfers the high-bit-rate traffic data in the identified area. The traffic transfer apparatus (20) causes the learner (200) to relearn a result of analysis of the transferred high-bit-rate traffic data and the low-bit-rate traffic data used in the determination.