KR-20260066881-A - Feedback System Based on Shooting Results for Enhancing User Concentration

Abstract

The present invention relates to a shooting result-based feedback provision system for improving user concentration, and more specifically, is characterized by comprising: a display on a metaverse implementing a shooting range; an interface formed in the shape of a firearm and emitting infrared rays; a recording unit that collects shooting result data by recognizing the infrared rays emitted from the interface by a camera at the bottom of the display; and a learning unit that preprocesses result data values stored in the recording unit, learns the shooting results, and provides feedback to the user. In addition, according to the present invention, a system for increasing concentration and improving shooting skills is provided by training shooting result data in the learning unit using a Graph Convolutional Network (GCN) model, determining the size and number of clusters of the bullet impact points, assigning grade criteria based on the size, and then providing feedback on concentration based on the shooting results.

Inventors

• 박승민
• 전영미
• 문성균
• 허동녕
• 이장훈

Assignees

• 동서대학교 산학협력단

Dates

Publication Date

20260512

Application Date

20241105

Claims (5)

1. A display showing a metaverse virtual space implementing a shooting range; An interface formed in the shape of a gun that emits infrared rays; A recording unit that collects shooting result data by recognizing infrared rays emitted from the above interface by a camera at the bottom of the display; and A shooting result feedback providing system comprising: a learning unit that preprocesses shooting result data stored in the above-mentioned record unit, learns the shooting result, and provides feedback to the user.
2. In Article 1, The above interface is It includes a motion controller that enables the user to move and manipulate within the metaverse space, and A shooting result feedback providing system comprising a function controller that enables the user to manipulate functions that can be performed in the metaverse space, and a shooting and reloading controller that enables the operation of aiming and reloading functions by means of a sensor when aiming at a shot.
3. In Paragraph 2, The above operation controller is The front includes field vision goggles, jump, and crouch functions, and It includes a joystick on the rear for controlling player movement, and The above function controller is Includes buttons for firing, leaning, running, and melee attack functions, The aiming and reloading controller is A sensor that recognizes the position of the head and, A shooting result feedback system including a touch sensor at the bottom of the magazine
4. In Article 1, The above record book Input impact point data fired via the interface's infrared; By converting the input impact point data into coordinate data; A shooting result feedback provision system including generating the above shooting result data.
5. In Article 1, The learning unit that learns the above shooting results and provides feedback to the user A data collection unit that collects fired impact point data from a data recording unit; Data preprocessing unit for generating feature vectors; GNC Model Building Department designing GNC layers; A learning progress unit that performs learning using a loss function; Evaluation and tuning unit for evaluating and tuning a trained model; and A shooting result feedback provision system including a result analysis unit that provides feedback.

Description

Feedback System Based on Shooting Results for Enhancing User Concentration Feedback System Based on Shooting Results for Enhancing User Concentration The present invention relates to a shooting result-based feedback provision system that combines a GCN algorithm with a shooting training simulation conducted in a metaverse-based, realistic environment to learn the user's shooting results and suggest the user's concentration and directions for improvement. In general, modern society provides people with a more convenient life thanks to rapidly developing technology. However, this convenience is producing side effects that lead to the deterioration of users' memory and concentration. In particular, a survey conducted among the 25-30 age group, where mobile phones were not yet widespread, revealed that over 70% responded that their memory and concentration seem to have declined compared to the past because they rely on mobile phones to take notes on all important matters and easily look up unknown information through internet searches. To address these issues, the present invention aims to develop a system that quantifies the user's concentration level and provides feedback by combining the GCN algorithm with a metaverse-based shooting training simulation. Figure 1 is a configuration diagram of a shooting result-based feedback provision system for improving user concentration according to the present invention. FIG. 2 is a drawing illustrating the components of an interface according to an embodiment of the present invention. FIG. 3 is a flowchart illustrating the flowchart of the shooting score grade being fed back through the GCN (Graph Convolutional Network) model of the learning unit according to an embodiment of the present invention. FIG. 4 is a drawing showing the results of a shooting with a concentration rating assigned according to the size of the impact point according to an embodiment of the present invention. Hereinafter, preferred embodiments are described in detail with reference to the attached drawings so that those skilled in the art can easily practice the present invention. However, in describing the preferred embodiments of the present invention in detail, specific descriptions of related known functions or configurations are omitted if it is determined that such detailed descriptions may unnecessarily obscure the essence of the present invention. Additionally, the same reference numerals are used throughout the drawings for parts having similar functions and operations. Additionally, throughout the specification, when a part is described as being ‘connected’ to another part, this includes not only cases where they are ‘directly connected,’ but also cases where they are ‘indirectly connected’ with other elements in between. Furthermore, the description of a component as ‘including’ means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. The term "part" as used in this embodiment refers to a software or hardware component such as a field-programmable gate array (FPGA) or an ASIC, and the "part" may perform certain roles. However, the meaning of "part" is not limited to software or hardware. The "part" may be configured to reside in an addressable storage medium or configured to run one or more processors. Thus, as an example, the "part" may include components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts." In addition, the components and '~parts' may be implemented to play one or more CPUs within the device or secure multimedia card. FIG. 1 is a diagram illustrating the configuration of a shooting result-based feedback provision system for improving user concentration according to an embodiment of the present invention. As shown in FIG. 1, the shooting result-based feedback provision system for improving user concentration according to an embodiment of the present invention comprises: a display (100) that displays a metaverse virtual space implementing a shooting range; an interface (200) formed in the shape of a gun and emitting infrared rays; a recording unit (300) that collects shooting result data by recognizing the infrared rays emitted from the interface by a camera at the bottom of the display; and a learning unit (400) that preprocesses the shooting result data stored in the recording unit, learns the shooting results, and provides feedback to the user. The display (100) on the above metaverse is configured to output video, and can be implemented as a screen in the form of a shootin