Dynamic gesture recognition intelligent access control device based on deep learning

Abstract

The utility model discloses a dynamic gesture recognition intelligent access control device based on deep learning. The dynamic gesture recognition intelligent access control device comprises a guardrail, a sliding rail is installed in the guardrail, a first motor is installed on one side of the sliding rail, a lead screw is installed in the sliding rail, a sliding block is arranged on the outer side of the lead screw in a sleeved mode, and a movable base is fixed to the upper portion of the sliding block. According to the dynamic gesture recognition intelligent access control device based on deep learning, the stand column, the rotating shaft, the supporting rod, the gesture recognition module, the hydraulic cylinder and the hydraulic rod are used in cooperation, the hydraulic cylinder can drive the hydraulic rod to stretch out and draw back, the supporting rod is driven to rotate around the rotating shaft, and the angle of the gesture recognition module is conveniently adjusted; the device can be conveniently used for different crowds, the angle of the gesture recognition module can be adjusted downwards when the device is used by children, the angle of the gesture recognition module can be adjusted upwards when the device is used by adults, and therefore gesture recognition and deep learning can be conveniently carried out on different crowds.

Description

Technical Field

[0001] The utility model relates to the technical field related to intelligent access control devices, and in particular to a dynamic gesture recognition intelligent access control device based on deep learning. Background Art

[0002] Smart access control devices are an indispensable part of the modern security field. They combine advanced technology and intelligent management to provide users with a more convenient, efficient and secure access control experience. With the continuous development and application of deep learning technology, gesture recognition, as an important research direction in the field of human-computer interaction, has made significant progress. Gesture recognition technology based on deep learning can effectively process complex gesture data and realize accurate recognition and interpretation of gestures, which provides new ideas and methods for the development of smart access control systems.

[0003] However, the angle of the gesture recognition system of the existing intelligent access control device is not easy to adjust, and it is not easy to use for different groups of people. Therefore, the present application provides a dynamic gesture recognition intelligent access control device based on deep learning to meet the needs. Utility Model Content

[0004] The purpose of the utility model is to provide a dynamic gesture recognition intelligent access control device based on deep learning to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned objectives, the utility model provides the following technical solutions: a dynamic gesture recognition intelligent access control device based on deep learning, comprising a guardrail, a slide rail is installed inside the guardrail, a first motor is installed on one side of the slide rail, a screw rod is installed inside the slide rail, a slider is sleeved on the outer side of the screw rod, a moving seat is fixed above the slider, a column is fixed above the guardrail, a rotating shaft is installed above the column, a support rod is movably connected inside the rotating shaft, a gesture recognition module is installed on one end of the support rod, a hydraulic cylinder is movably connected to one side of the column, and a hydraulic rod is installed above the hydraulic cylinder.

[0006] Preferably, the movable seat forms a sliding structure through a slider and a slide rail, and the slider and the slide rail have the same shape.

[0007] Preferably, a fixed seat is fixed on one side of the movable seat, a second motor is installed below the fixed seat, a transmission shaft is installed at the upper output end of the second motor, a blocking door is installed on one side of the transmission shaft, and a control module is installed on one side of the second motor.

[0008] Preferably, the blocking door forms a rotating structure through a transmission shaft and a fixing seat, and the input end of the control module is electrically connected to the output end of the gesture recognition module.

[0009] Preferably, the support rod forms a rotating structure with the column through a rotating shaft, and a lower part of one side of the support rod is movably connected to the hydraulic rod.

[0010] Preferably, one end of the support rod forms a telescopic structure through a hydraulic rod and a hydraulic cylinder, and the hydraulic cylinder and the hydraulic rod are used in coordination.

[0011] Compared with the prior art, the beneficial effects of the utility model are:

[0012] 1. This dynamic gesture recognition intelligent access control device based on deep learning, through the coordinated use of a column, a rotating shaft, a support rod, a gesture recognition module, a hydraulic cylinder and a hydraulic rod, can drive the hydraulic rod to extend and retract through the hydraulic cylinder, and drive the support rod to rotate around the rotating shaft, so as to facilitate the adjustment of the angle of the gesture recognition module, and facilitate the use of the device for different groups of people. When used by children, the angle of the gesture recognition module can be adjusted downward, and when used by adults, the angle of the gesture recognition module can be adjusted upward, so as to facilitate gesture recognition and deep learning for different groups of people;

[0013] 2. This dynamic gesture recognition intelligent access control device based on deep learning, through the setting of the slide rail, the first motor, the screw rod, the slider, the moving seat and the blocking door, the first motor drives the slider to slide, and then drives the blocking door to move. The position of the blocking door inside the guardrail can be adjusted according to actual usage. When the device is installed in a narrow passage or doorway, the position of the blocking door can be appropriately adjusted to ensure that the device can work normally and avoid blocking the passage. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the overall structure of the utility model;

[0015] Figure 2 It is a cross-sectional structural schematic diagram of the slide rail of the utility model;

[0016] Figure 3 This is a schematic diagram of the structure of the barrier door of the utility model;

[0017] Figure 4 This is a structural diagram of a gesture recognition module of the present utility model.

[0018] In the figure: 1. guardrail; 2. slide rail; 3. first motor; 4. screw rod; 5. slider; 6. moving seat; 7. fixed seat; 8. second motor; 9. transmission shaft; 10. blocking door; 11. column; 12. rotating shaft; 13. support rod; 14. gesture recognition module; 15. hydraulic cylinder; 16. hydraulic rod; 17. control module. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the utility model to clearly and completely describe the technical solutions in the embodiments of the utility model. Obviously, the described embodiments are only part of the embodiments of the utility model, not all of the embodiments. Based on the embodiments in the utility model, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the utility model.

[0020] See also Figure 1-3 The utility model provides a technical solution: a dynamic gesture recognition intelligent access control device based on deep learning, including a guardrail 1, a slide rail 2 is installed inside the guardrail 1, a first motor 3 is installed on one side of the slide rail 2, a screw rod 4 is installed inside the slide rail 2, a slider 5 is sleeved on the outer side of the screw rod 4, a moving seat 6 is fixed above the slider 5, and the moving seat 6 forms a sliding structure with the slide rail 2 through the slider 5. The slider 5 has the same shape as the slide rail 2, and the position of the blocking door 10 inside the guardrail 1 can be adjusted according to actual use. When the device is installed in a narrow passage or doorway, the position of the blocking door 10 can be properly adjusted to ensure that the device can be normally To work and avoid blocking the passage, a fixed seat 7 is fixed on one side of the movable seat 6, a second motor 8 is installed below the fixed seat 7, a transmission shaft 9 is installed on the upper output end of the second motor 8, a blocking door 10 is installed on one side of the transmission shaft 9, and a control module 17 is installed on one side of the second motor 8 to facilitate the control of the switch of the blocking door 10. The blocking door 10 forms a rotating structure with the fixed seat 7 through the transmission shaft 9. The input end of the control module 17 is electrically connected to the output end of the gesture recognition module 14. When a specific gesture is recognized, the control module 17 will turn on the second motor 8, open the blocking door 10 to allow the user to enter, and the degree of automation is high;

[0021] See also Figure 1 and Figure 4 A column 11 is fixed above the guardrail 1, and a rotating shaft 12 is installed above the column 11. A support rod 13 is movably connected inside the rotating shaft 12. The support rod 13 forms a rotating structure with the column 11 through the rotating shaft 12. The lower side of the support rod 13 is movably connected with the hydraulic rod 16. When children use it, the angle of the gesture recognition module 14 can be adjusted downward, and when adults use it, the angle of the gesture recognition module 14 can be adjusted upward, so as to facilitate gesture recognition and deep learning for different groups of people. A gesture recognition module 14 is installed at one end of the support rod 13, and a hydraulic cylinder 15 is movably connected to one side of the column 11. A hydraulic rod 16 is installed above the hydraulic cylinder 15. One end of the support rod 13 forms a telescopic structure with the hydraulic cylinder 15 through the hydraulic rod 16. The hydraulic cylinder 15 and the hydraulic rod 16 are used together to facilitate the adjustment of the angle of the gesture recognition module 14, so that the device can be used for different groups of people.

[0022] Working principle: When using the dynamic gesture recognition intelligent access control device based on deep learning, first turn on the external power supply, then turn on the first motor 3 to drive the slider 5 to slide, and then drive the blocking door 10 to move, and adjust the position of the blocking door 10 inside the guardrail 1 to ensure that the device can work normally when installed in a narrow passage or doorway and avoid blocking the passage. Secondly, when in use, the gesture recognition module 14 learns and recognizes the human gesture image. According to the recognition result, the control module 17 will issue a corresponding instruction. If a specific gesture is recognized, the control module 17 will turn on the second motor 8. Open the blocking door 10 to allow the user to enter. Finally, the hydraulic cylinder 15 can drive the hydraulic rod 16 to extend and retract, and drive the support rod 13 to rotate around the rotating shaft 12, so as to adjust the angle of the gesture recognition module 14 and facilitate the use of the device for different groups of people. When the device is not in use, the external power supply of the device is cut off. The model of the first motor 3 is ZD-2HD542, the model of the second motor 8 is 6IK200RGU-CF, and the model of the hydraulic cylinder 15 is MOB50. In this way, the use process of the dynamic gesture recognition intelligent access control device based on deep learning is completed.

[0023] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic gesture recognition intelligent access control device based on deep learning, comprising a guardrail (1), characterized in that: A slide rail (2) is installed inside the guardrail (1), a first motor (3) is installed on one side of the slide rail (2), a screw rod (4) is installed inside the slide rail (2), a slider (5) is sleeved on the outer side of the slider (4), a movable seat (6) is fixed above the slider (5), a column (11) is fixed above the guardrail (1), a rotating shaft (12) is installed above the column (11), a support rod (13) is movably connected inside the rotating shaft (12), a gesture recognition module (14) is installed at one end of the support rod (13), a hydraulic cylinder (15) is movably connected to one side of the column (11), and a hydraulic rod (16) is installed above the hydraulic cylinder (15).

2. According to claim 1, a dynamic gesture recognition intelligent access control device based on deep learning is characterized in that: The movable seat (6) forms a sliding structure through a slider (5) and a slide rail (2), and the slider (5) and the slide rail (2) have the same shape.

3. According to claim 1, a dynamic gesture recognition intelligent access control device based on deep learning is characterized in that: A fixed seat (7) is fixed on one side of the movable seat (6), a second motor (8) is installed below the fixed seat (7), a transmission shaft (9) is installed at the upper output end of the second motor (8), a blocking door (10) is installed on one side of the transmission shaft (9), and a control module (17) is installed on one side of the second motor (8).

4. According to claim 3, a dynamic gesture recognition intelligent access control device based on deep learning is characterized in that: The blocking door (10) forms a rotating structure through a transmission shaft (9) and a fixing seat (7), and the input end of the control module (17) is electrically connected to the output end of the gesture recognition module (14).

5. According to claim 1, a dynamic gesture recognition intelligent access control device based on deep learning is characterized in that: The support rod (13) forms a rotating structure with the column (11) via a rotating shaft (12), and a lower side of the support rod (13) is movably connected to a hydraulic rod (16).

6. According to claim 1, a dynamic gesture recognition intelligent access control device based on deep learning is characterized in that: One end of the support rod (13) forms a telescopic structure with a hydraulic rod (16) and a hydraulic cylinder (15), and the hydraulic cylinder (15) and the hydraulic rod (16) are used in coordination.

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