An ai recognition-based explosion-proof lifting column control system and a use method thereof

Abstract

This invention discloses an AI-based explosion-proof rising bollard control system, comprising an AI multi-dimensional sensing unit, a control unit, a rising bollard execution unit, and a linkage interlocking unit. The control unit is electrically connected to the AI ​​multi-dimensional sensing unit, the rising bollard execution unit, and the linkage interlocking unit. The AI ​​multi-dimensional sensing unit detects vehicle speed, identifies vehicle type, and determines a dangerous vehicle. The control unit acquires the dangerous vehicle determination signal, controls the rising bollard execution unit to forcibly and rapidly rise, and simultaneously controls the linkage interlocking unit to close the vehicle and allow passage. The advantages of this invention compared to existing technologies are: it provides an AI-based explosion-proof rising bollard control system and its usage method that can intelligently identify hazards, respond quickly, and lock the vehicle for passage.

Description

Technical Field

[0001] This invention relates to the field of intelligent security control technology, specifically to an explosion-proof lifting column control system based on AI recognition and its usage method. Background Technology

[0002] In public places such as schools, pedestrian streets, squares, and government offices, malicious vehicle collisions have become a major safety hazard. Existing protective equipment is mainly divided into two categories:

[0003] One type is fixed stone blocks, crash barriers, and other roadblocks. Although they have basic protective capabilities, they completely block passage and seriously affect the rapid passage of emergency vehicles such as fire trucks and ambulances.

[0004] Another type is the traditional electric lifting bollard, which relies on manual remote control or automatic release via ground loop coils and license plate recognition systems, and has obvious drawbacks:

[0005] It cannot actively identify the dangerous intent and speed of vehicles, has no ability to predict high-speed collisions, and responds slowly. When danger occurs, it cannot quickly force the vehicle to rise, and the ground loop and license plate recognition system will still allow passage according to normal logic, thus failing to block dangerous vehicles from passing.

[0006] This makes it difficult for existing protective equipment to meet the needs of proactive, rapid, and reliable security interception in public places. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to overcome the above-mentioned technical defects and provide an explosion-proof lifting column control system based on AI recognition and its usage method, which can intelligently identify dangers, respond quickly, and lock and release the system.

[0008] To solve the above-mentioned technical problems, the technical solution provided by the present invention is: an explosion-proof lifting column control system based on AI recognition, including an AI multi-dimensional perception unit, a control unit, a lifting column execution unit, and a linkage interlocking unit;

[0009] The control unit is electrically connected to the AI ​​multidimensional perception unit, the lifting column execution unit, and the linkage locking unit, respectively.

[0010] The AI ​​multi-dimensional perception unit detects vehicle speed, identifies vehicle type and determines dangerous vehicles. The control unit obtains the dangerous vehicle determination signal, controls the lifting column execution unit to force it to rise quickly, and simultaneously controls the linkage locking unit to close the vehicle and allow it to pass.

[0011] Preferably, the AI ​​multidimensional perception unit includes a radar module and an AI smart camera module;

[0012] The radar module detects the vehicle's speed, and the AI ​​intelligent camera module identifies the vehicle and outputs the vehicle type.

[0013] Preferably, the vehicle type includes motor vehicles and non-motor vehicles.

[0014] Preferably, the AI ​​multidimensional perception unit also integrates a storage unit;

[0015] The storage unit stores vehicle speed data and identification records.

[0016] Preferably, the interlocking unit includes a ground induction coil and a license plate recognition system;

[0017] The control unit is connected to the lifting column actuator, the ground induction coil, and the license plate recognition system via relays.

[0018] Preferably, the lifting column execution module is an explosion-proof lifting column.

[0019] Another aspect of this invention discloses a control method for explosion-proof lifting columns based on AI recognition, comprising the following steps:

[0020] S1: Detect and identify the speed and type of passing vehicles;

[0021] S2: Determine whether it is a speeding dangerous motor vehicle;

[0022] S3: When a speeding dangerous motor vehicle is identified, the explosion-proof lifting column is triggered to rise rapidly.

[0023] S4: Synchronous interlocking of the ground loop coil and the license plate recognition system for release function.

[0024] Preferably, in step S2, when identifying vehicle type, non-motorized vehicles are excluded, and only motorized vehicles are subjected to speed detection and hazard assessment.

[0025] Preferably, it also includes storing vehicle speed and identification records.

[0026] The advantages of this invention compared with the prior art are as follows: This invention can actively and accurately identify the type and speed of passing vehicles, effectively distinguish between motor vehicles and non-motor vehicles, accurately determine speeding dangerous vehicles, and avoid false triggering; after detecting danger, it can respond quickly and directly control the explosion-proof lifting column to raise it quickly through the relay without manual intervention, while simultaneously locking the release logic of the ground induction coil and the license plate recognition system, blocking the passage of dangerous vehicles from the root.

[0027] This invention effectively solves the shortcomings of traditional roadblocks and rising bollards, such as slow response, weak recognition ability, unreliable protection, lack of interlocking protection, and lack of data recording, and greatly improves the security protection level of public places. Attached Figure Description

[0028] Figure 1This is a structural diagram of an explosion-proof lifting column control system based on AI recognition. Detailed Implementation

[0029] The present invention will now be described in further detail with reference to the accompanying drawings.

[0030] Combined with appendix Figure 1 As shown, an explosion-proof lifting column control system based on AI recognition includes an AI multi-dimensional detection module, a control module, a lifting column execution module, and an access interlock module.

[0031] The AI ​​multidimensional detection module consists of a radar module, an AI smart camera module, and a built-in storage chip. The radar module detects the vehicle speed in real time, while the AI ​​smart camera module identifies the vehicle type through AI algorithms, automatically eliminating non-motorized vehicles such as electric bicycles and only judging the speed of motorized vehicles. When the speed of a motorized vehicle exceeds a preset threshold, a dangerous vehicle signal is output to the control module. The storage chip stores data such as vehicle speed, recognition time, and vehicle type in real time, supporting subsequent retrieval.

[0032] The control module uses an industrial control motherboard, which is electrically connected to the radar module and the AI ​​smart camera module respectively. The control module is connected to the lifting column execution module through a relay. After receiving the signal from the control module, the relay switches between the normally closed and normally open terminals and outputs a forced rapid lifting command to the explosion-proof lifting column. At the same time, the control module is connected to the ground loop coil and the license plate recognition system through another relay. When a danger signal is received, the power supply of the ground loop coil and the license plate recognition system is immediately cut off, and their automatic release function is locked.

[0033] The lifting column execution module uses an explosion-proof lifting column with an impact-resistant and damage-resistant structure, which can withstand the impact of high-speed vehicles and ensure the interception effect.

[0034] In a specific implementation of this invention, the specific steps are as follows:

[0035] S1, the AI ​​multi-dimensional detection module collects vehicle information in real time, detects driving speed through radar, identifies vehicle type through AI camera, automatically isolates non-motorized vehicles, and only compares the speed of motorized vehicles;

[0036] S2. When the speed of a motor vehicle exceeds the preset safety threshold, it is determined to be a speeding dangerous motor vehicle, and the AI ​​multi-dimensional detection module sends a danger signal to the control module.

[0037] S3. After receiving a danger signal, the control module immediately triggers the relay to control the explosion-proof lifting column to rise rapidly.

[0038] S4. The control module synchronously cuts off the working circuit between the ground loop coil and the license plate recognition system, and locks its automatic release logic to prevent dangerous vehicles from being released.

[0039] The S5 AI multidimensional detection module writes data such as vehicle speed, recognition results, and trigger time into the storage chip to form a traceable record.

[0040] This invention combines AI multidimensional perception with rapid control to achieve integrated active identification, rapid interception, release and locking of dangerous vehicles, and data recording. It is suitable for security protection in public places such as schools, squares, and government agencies, and solves the defects of traditional rising bollards, such as slow response, lack of intelligent identification, and lack of locking protection, thereby improving the security level of public areas.

[0041] Working principle:

[0042] The AI ​​multidimensional detection module works continuously: the millimeter-wave radar transmits frequency-modulated continuous waves and receives vehicle reflected echoes, and calculates vehicle speed in real time based on the Doppler effect;

[0043] AI cameras use deep learning models to identify vehicle types frame by frame, automatically eliminating non-motorized vehicles. Radar and cameras achieve data fusion through spatiotemporal coordinate mapping, accurately binding vehicle speed with vehicle type.

[0044] After confirming the danger, the detection module sends a coded danger signal to the control module. One relay drives the explosion-proof lifting column to rise forcibly, while another relay simultaneously cuts off the power supply to the ground loop coil and the communication link with the license plate recognition system, locking the passage function. The locked state is maintained for a preset time and needs to be manually reset to be released.

[0045] During the interception process, the system writes data such as vehicle speed and recognition results into the storage chip in real time and uploads them to the cloud in an encrypted manner, forming a complete and traceable security record.

[0046] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

[0047] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0048] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An AI recognition-based anti-explosion lifting column control system, characterized in that: It includes an AI multi-dimensional perception unit, a control unit, a lifting column execution unit, and a linkage locking unit; The control unit is electrically connected to the AI ​​multidimensional perception unit, the lifting column execution unit, and the linkage locking unit, respectively. The AI ​​multi-dimensional perception unit detects vehicle speed, identifies vehicle type and determines dangerous vehicles. The control unit obtains the dangerous vehicle determination signal, controls the lifting column execution unit to force it to rise quickly, and simultaneously controls the linkage locking unit to close the vehicle and allow it to pass.

2. The AI recognition-based anti-explosion lifting column control system according to claim 1, characterized in that: The AI ​​multidimensional perception unit includes a radar module and an AI smart camera module; The radar module detects the vehicle's speed, and the AI ​​intelligent camera module identifies the vehicle and outputs the vehicle type.

3. The AI recognition-based anti-explosion lifting column control system according to claim 2, characterized in that: The vehicle types include motor vehicles and non-motor vehicles.

4. The explosion-proof lifting column control system based on AI recognition according to claim 1, characterized in that: The AI ​​multidimensional perception unit also integrates a storage unit; The storage unit stores vehicle speed data and identification records.

5. The AI recognition-based anti-explosion lifting column control system according to claim 1, characterized in that: The interlocking unit includes a ground induction coil and a license plate recognition system; The control unit is connected to the lifting column actuator, the ground induction coil, and the license plate recognition system via relays.

6. The AI recognition-based anti-explosion lifting column control system according to claim 1, characterized in that: The lifting column execution module is an explosion-proof lifting column.

7. An AI recognition-based explosion-proof lifting column control method for the control system of any one of claims 1-6, characterized in that: Includes the following steps: S1: Detect and identify the speed and type of passing vehicles; S2: Determine whether it is a speeding dangerous motor vehicle; S3: When a speeding dangerous motor vehicle is identified, the explosion-proof lifting column is triggered to rise rapidly. S4: Synchronous interlocking of the ground loop coil and the license plate recognition system for release function.

8. The AI recognition-based explosion-proof lifting column control method according to claim 7, characterized in that: When identifying vehicle types in S2, non-motorized vehicles are excluded, and only motorized vehicles are subjected to speed detection and hazard assessment.

9. The AI recognition-based anti-explosion lifting column control method according to claim 7, characterized in that: It also includes storing vehicle speed and identification records.

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