Photovoltaic power station anti-terrorism security system

Abstract

A photovoltaic power station anti-terrorism security system comprises a perimeter protection subsystem used for physical protection and detection and identification of intrusion behaviors, a video monitoring subsystem used for tracking intrusion personnel and collecting information, and an intrusion detection and identification subsystem. The AI intelligent monitoring subsystem is used for collecting and converging sensor data detected by the perimeter protection subsystem and video data collected by the video monitoring subsystem, preprocessing and fusing the collected and converged data, then carrying out AI intelligent analysis and identification on the preprocessed and fused data, generating an alarm according to an analysis and identification result, and sending the alarm to the video monitoring subsystem. The central control and alarm platform is used for receiving the alarm generated by the intrusion detection and identification subsystem and starting an emergency response mechanism according to the alarm, and the emergency response subsystem is used for carrying out alarm response according to a control signal of the central control and alarm platform so as to realize omnibearing monitoring and protection on the periphery of a power station, an equipment area, a key channel and the like. The overall safety protection capability of the power station is improved.

Description

Technical Field

[0001] This invention relates to the field of security protection for photovoltaic power generation facilities, and in particular to an anti-terrorism security system for photovoltaic power plants. Background Technology

[0002] Photovoltaic power plants are typically located in remote areas, covering large areas and with dispersed equipment, making them vulnerable to terrorist attacks or malicious sabotage. Traditional security measures such as walls and surveillance cameras suffer from numerous blind spots, slow response times, and low levels of intelligence, making it difficult to achieve real-time, efficient, and intelligent protection for the entire power plant area. Summary of the Invention

[0003] The purpose of this invention is to solve the problems in the prior art, realize all-round monitoring and protection of the power station perimeter, equipment area, key passages, etc., and improve the overall security protection capability of the power station. Therefore, a photovoltaic power station anti-terrorism security system is proposed.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A photovoltaic power station anti-terrorism security system includes: The perimeter protection subsystem is used for physical protection and to detect and identify intrusion activities; The video surveillance subsystem is used for tracking intruders and collecting information. The intrusion detection and identification subsystem is used to collect and aggregate sensor data from the perimeter protection subsystem and video data from the video surveillance subsystem. It also preprocesses and fuses the collected and aggregated data, performs AI intelligent analysis and identification on the preprocessed and fused data, and generates alarms based on the analysis and identification results. The central control and alarm platform is used to receive alarms generated by the intrusion detection and identification subsystem and to activate the emergency response mechanism based on the alarms. And an emergency response subsystem, used to respond to alarms based on control signals from the central control and alarm platform.

[0005] Furthermore, the perimeter protection subsystem includes: an electronic fence, which is laid along the top of the power station wall; Vibrating optical fiber, which is installed on the power station perimeter wall; Active infrared beam arrays are installed in open areas inside or outside the power plant enclosure.

[0006] Furthermore, the video surveillance subsystem includes: camera modules, which are deployed at preset intervals along the perimeter, at corners, and at entrances and exits; The automatic drone inspection module is installed inside the power station. The drones in the automatic drone inspection module take off automatically according to a preset time, route, or after receiving an alarm.

[0007] Furthermore, the specific steps for preprocessing and fusing the collected and aggregated data in the intrusion detection and identification subsystem include: Step 11: Filter and denoise the collected and aggregated perimeter protection subsystem detection sensor data, and uniformly add timestamps and location tags; Step 12: Decode and enhance the video data acquired by the video surveillance subsystem after acquisition and aggregation; Step 13: Perform spatial and temporal correlation on the data processed in Steps 1 and 2 on a unified electronic map platform.

[0008] Furthermore, the specific steps for performing AI intelligent analysis and recognition on the preprocessed and fused data, and generating alarms based on the analysis and recognition results, include: Step 21: Use deep learning algorithms to perform real-time analysis on the preprocessed and fused video data to accurately outline the targets in the scene, including people, vehicles and animals; Step 22: Analyze the behavior pattern of the target in Step 21 using an AI model. If the behavior pattern includes area intrusion, boundary crossing, loitering, or gathering, it is determined to be a real intrusion, and a structured alarm event is automatically generated.

[0009] Furthermore, the structured alarm event includes alarm time, precise location, event type, threat level, associated snapshots, and video clips.

[0010] Furthermore, the emergency response subsystem includes: a remote communication module, used to receive control signals from the central control and alarm platform and send them out; The audible and visual alarm module is used to receive control signals from the remote communication module and to issue or stop the audible and visual alarm according to the control signals. Defense equipment is used to receive control signals from remote communication modules and drive away intruders based on the control signals.

[0011] Furthermore, the specific steps of the emergency response mechanism include: Step 31: Upon receiving the alarm, a control signal will be sent to the emergency response subsystem. The audible and visual alarm module in the emergency response subsystem will issue an audible and visual alarm and control the high-intensity searchlight to automatically turn and illuminate the intruder's location. At the same time, the voice warning system will be activated to play a pre-recorded warning tone. Step 32: If the attempt to drive away the intruder in Step 31 fails and the intruder continues to penetrate deeper, the central control and alarm platform will send a control signal to the drone automatic inspection module in the video surveillance subsystem, activating the drone to automatically take off and track the intruder from the air, collect evidence by filming, and issue warnings. If the intruder forcibly enters the core area, the central control and alarm platform will send a control signal to the defense equipment in the emergency response subsystem. The defense equipment will drive away the intruder using methods including high-pressure water mist spray and tear gas. Step 33: When an alarm is received and confirmed as a high-level threat, the central control and alarm platform will issue an alarm and simultaneously send a structured alarm event.

[0012] Furthermore, the high-level threat confirmation step in step 33 specifically includes: Step 41: Extract the number of people, machinery information, and human behavior from the associated snapshots and video clips; Step 42: If the number of people exceeds the preset number, there is information about armed personnel or acts of sabotage, and the threat level is high, then it is considered a high-level threat.

[0013] Compared with existing technologies, the advantages of this invention are: This invention utilizes a perimeter protection subsystem and a video surveillance subsystem to form a gradient early warning system from the outside in, based on external invisible light beams, physical wall vibrations, and internal video verification. This ensures overlapping and cross-verification of detection ranges, eliminating blind spots in protection. Furthermore, an intrusion detection and identification subsystem identifies and analyzes the sensor data from the perimeter protection subsystem and the video data collected by the video surveillance subsystem, generating structured alarm events that are fed back to the central control and alarm platform. The central platform then activates an emergency response mechanism for rapid response and deterrence, thereby achieving real-time, efficient, and intelligent protection of the entire power station area and enhancing the overall security capabilities of the power station. Attached Figure Description

[0014] Figure 1 This is a block diagram of the overall architecture of a photovoltaic power station anti-terrorism security system proposed in this invention. Detailed Implementation

[0015] The invention will now be further explained with reference to the accompanying drawings.

[0016] like Figure 1 As shown, this invention discloses a photovoltaic power station anti-terrorism security system, comprising: The perimeter protection subsystem is used for physical protection and to detect and identify intrusion activities.

[0017] The video surveillance subsystem is used for tracking intruders and collecting information.

[0018] The intrusion detection and identification subsystem is used to collect and aggregate sensor data from the perimeter protection subsystem and video data from the video surveillance subsystem. It then preprocesses and fuses the collected and aggregated data, performs AI intelligent analysis and identification on the preprocessed and fused data, and generates alarms based on the analysis and identification results.

[0019] The central control and alarm platform is used to receive alarms generated by the intrusion detection and identification subsystem and to activate the emergency response mechanism based on the alarms.

[0020] And an emergency response subsystem, used to respond to alarms based on control signals from the central control and alarm platform.

[0021] The perimeter protection subsystem includes an electronic fence, which is laid along the top of the power station wall. It not only has a physical blocking function, but is also an important sensor. When it is climbed, cut, or forcibly damaged, it will immediately generate an alarm signal and accurately locate the triggered protection zone.

[0022] Vibrating optical fibers, installed close to the power station perimeter wall, are extremely sensitive to minute vibrations caused by any attempt to climb over, dig, knock, or cut the wall. By analyzing the vibration waveform, they can effectively distinguish between personnel intrusion, weather interference (such as wind and rain), or animal contact, greatly reducing the false alarm rate.

[0023] Active infrared beam arrays are installed inside or in open areas outside the power plant perimeter wall. The active infrared beam array consists of multiple pairs of infrared transmitters and receivers. When activated, it forms one or more invisible infrared beam walls. When any object illegally crosses or blocks the beam, the system will immediately sound an alarm. This layer of protection can be triggered before the intruder touches the physical perimeter wall, providing an earlier warning time.

[0024] The video surveillance subsystem includes camera modules, which are deployed at preset distances along the perimeter, at corners, and at entrances and exits. The camera modules include high-definition intelligent PTZ cameras and thermal imaging cameras. The high-definition intelligent PTZ cameras have 360° horizontal rotation and elevation angle adjustment functions, and support automatic cruise and preset position monitoring. The thermal imaging cameras can clearly detect and track intruders by sensing the thermal radiation of objects in adverse weather conditions such as night, fog, rain, snow, and low light conditions.

[0025] The drone automatic inspection module consists of a drone nest (base station) set up in the station and drones. It can take off automatically according to a preset time, route or after receiving an alarm to conduct three-dimensional aerial inspection of the perimeter and key areas in the station, providing a bird's-eye view, making up for the blind spots of fixed cameras, and tracking and photographing intruders as evidence.

[0026] The intrusion detection and identification subsystem, at its core, is an AI-based artificial intelligence analysis engine that enables real-time processing and intelligent decision-making from massive amounts of sensor information. Its specific steps are as follows: Data acquisition and aggregation involves collecting and aggregating data from the perimeter protection subsystem's detection sensors and the video data collected by the video surveillance subsystem.

[0027] Data preprocessing and fusion: First, the perimeter protection subsystem detection sensor data after acquisition and aggregation is filtered and denoised, and timestamps and location tags are uniformly added. Then, the video data acquired by the video surveillance subsystem after acquisition and aggregation is decoded and image enhanced. Finally, the data processed in steps 1 and 2 are spatially and temporally correlated on a unified electronic map platform.

[0028] AI Intelligent Analysis and Recognition: Using deep learning algorithms, preprocessed and fused video data is analyzed in real time to accurately identify targets in the scene, including people, vehicles and animals. Then, the AI ​​model is used to analyze the behavioral patterns of the targets in step 21. If the behavioral patterns show invasiveness, boundary crossing, loitering or gathering, it is judged as a real intrusion and a structured alarm event is automatically generated.

[0029] In its behavioral patterns, area intrusion refers to a target entering a pre-defined prohibited area (such as inside a wall or equipment area), boundary crossing refers to a target crossing the perimeter from the outside to enter the interior, loitering refers to a target staying and loitering near a sensitive area for a long time, and gathering refers to multiple targets gathering in an abnormal area.

[0030] The structured alarm events include: alarm time, precise location (GPS coordinates / zone number), event type (such as "personnel climbing over"), threat level (high, medium, low), and associated snapshots and video clips.

[0031] The emergency response subsystem includes an audible and visual alarm module, which is distributed throughout the photovoltaic power station. When triggered, it emits a high-decibel siren and flashing bright light to psychologically deter intruders and force them to abandon their actions.

[0032] The defensive equipment, which is set up in or near the restricted area of ​​the photovoltaic power station, consists of a high-pressure water mist spray system and a tear gas device. When an intruder forcibly enters the restricted area, it will trigger the system to forcibly remove the intruder in a non-lethal manner. In extreme cases, the tear gas device will be used to remove the intruder. All of the above defensive equipment is used within the scope clearly permitted by law.

[0033] The photovoltaic power station's anti-terrorism security system will completely archive all videos, operation logs, and communication records from the moment the alarm is triggered to the end of the incident, generating an "Incident Handling Report" for post-incident review and accountability. At the same time, it will add the data from each incident (especially misjudged data) to the AI ​​training set to continuously optimize the AI ​​model and improve future recognition accuracy.

[0034] This invention utilizes a perimeter protection subsystem and a video surveillance subsystem to form a gradient early warning system from the outside in, encompassing external invisible light beams, physical perimeter wall vibrations, and internal video verification. It also collects real-time environmental data from the power station's surroundings and interior. An intrusion detection and recognition subsystem uses AI to intelligently identify and analyze images and behaviors within the perimeter protection subsystem, recognizing abnormal intrusions and generating structured alarm events. The central platform, based on these structured alarm events, activates an emergency response mechanism, issuing control signals to the emergency response subsystem. This first triggers the audible and visual alarm module, emitting a high-decibel siren and flashing bright lights, while controlling the spotlight to automatically turn and illuminate the intruder's location, exposing them and providing supplemental lighting for the camera to obtain a clearer image. Simultaneously, the voice warning system is activated, playing pre-recorded warning sounds. If the intruder does not leave, the system will automatically push alarm information and real-time video of the scene to the mobile terminal of the maintenance personnel and the central control console. This will assist the maintenance personnel in remotely controlling the on-site camera to track the target and confirm the situation via the APP. If the intruder continues to penetrate deeper, the system will automatically launch a drone to track the intruder from the air, take photos for evidence collection, and issue warnings. Further active defense equipment can be remotely activated, using a high-pressure water mist spray system to non-lethally and forcibly drive away the intruder. In extreme cases, tear gas can be used to drive away the intruder. If the central platform confirms a high-level threat (such as multiple people, armed, or equipment damage) based on the structured alarm event, it will activate the one-click alarm function and automatically transmit the scene information (location, nature, and real-time video stream) to the public security department through a dedicated network.

[0035] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

Claims

1. A photovoltaic power station anti-terrorism security system, characterized in that, include: The perimeter protection subsystem is used for physical protection and to detect and identify intrusion activities; The video surveillance subsystem is used for tracking intruders and collecting information. The intrusion detection and identification subsystem is used to collect and aggregate sensor data from the perimeter protection subsystem and video data from the video surveillance subsystem. It also preprocesses and fuses the collected and aggregated data, performs AI intelligent analysis and identification on the preprocessed and fused data, and generates alarms based on the analysis and identification results. The central control and alarm platform is used to receive alarms generated by the intrusion detection and identification subsystem and to activate the emergency response mechanism based on the alarms. And an emergency response subsystem, used to respond to alarms based on control signals from the central control and alarm platform.

2. The photovoltaic power station anti-terrorism security system according to claim 1, characterized in that: The perimeter protection subsystem includes: an electronic fence, which is laid along the top of the power station wall; Vibrating optical fiber, which is installed on the power station perimeter wall; Active infrared beam arrays are installed in open areas inside or outside the power plant enclosure.

3. The photovoltaic power station anti-terrorism security system according to claim 1, characterized in that: The video surveillance subsystem includes: camera modules, which are deployed at preset intervals along the perimeter, at corners, and at entrances and exits; The automatic drone inspection module is installed inside the power station. The drones in the automatic drone inspection module take off automatically according to a preset time, route, or after receiving an alarm.

4. The photovoltaic power station anti-terrorism security system according to claim 1, characterized in that: The specific steps for preprocessing and fusing the collected and aggregated data in the intrusion detection and identification subsystem include: Step 11: Filter and denoise the collected and aggregated perimeter protection subsystem detection sensor data, and uniformly add timestamps and location tags; Step 12: Decode and enhance the video data acquired by the video surveillance subsystem after acquisition and aggregation; Step 13: Perform spatial and temporal correlation on a unified electronic map platform after processing the data in Step 1 and Step 2 [1].

5. The photovoltaic power station anti-terrorism security system according to claim 1, characterized in that: The specific steps for performing AI intelligent analysis and recognition on the preprocessed and fused data, and generating alarms based on the analysis and recognition results, include: Step 21: Use deep learning algorithms to perform real-time analysis on the preprocessed and fused video data to accurately outline the targets in the scene, including people, vehicles and animals; Step 22: Analyze the behavior pattern of the target in Step 21 using an AI model. If the behavior pattern includes area intrusion, boundary crossing, loitering, or gathering, it is determined to be a real intrusion, and a structured alarm event is automatically generated.

6. The photovoltaic power station anti-terrorism security system according to claim 5, characterized in that: The structured alarm events include alarm time, precise location, event type, threat level, associated snapshots, and video clips.

7. The photovoltaic power station anti-terrorism security system according to claim 1, characterized in that: The emergency response subsystem includes: a remote communication module, used to receive control signals from the central control and alarm platform and send them out; The audible and visual alarm module is used to receive control signals from the remote communication module and to issue or stop the audible and visual alarm according to the control signals. Defense equipment is used to receive control signals from remote communication modules and drive away intruders based on the control signals.

8. The photovoltaic power station anti-terrorism security system according to claim 5, characterized in that: The specific steps of the emergency response mechanism include: Step 31: Upon receiving the alarm, a control signal will be sent to the emergency response subsystem. The audible and visual alarm module in the emergency response subsystem will issue an audible and visual alarm and control the high-intensity searchlight to automatically turn and illuminate the intruder's location. At the same time, the voice warning system will be activated to play a pre-recorded warning tone. Step 32: If the attempt to drive away the intruder in Step 31 fails and the intruder continues to penetrate deeper, the central control and alarm platform will send a control signal to the drone automatic inspection module in the video surveillance subsystem, activating the drone to automatically take off and track the intruder from the air, collect evidence by filming, and issue warnings. If the intruder forcibly enters the core area, the central control and alarm platform will send a control signal to the defense equipment in the emergency response subsystem. The defense equipment will drive away the intruder using methods including high-pressure water mist spray and tear gas. Step 33: When an alarm is received and confirmed as a high-level threat, the central control and alarm platform will issue an alarm and simultaneously send a structured alarm event.

9. The photovoltaic power station anti-terrorism security system according to claim 8, characterized in that: The high-level threat confirmation step in step 33 specifically includes: Step 41: Extract the number of people, machinery information, and human behavior from the associated snapshots and video clips; Step 42: If the number of people exceeds the preset number, there is information about armed personnel or acts of sabotage, and the threat level is high, then it is considered a high-level threat.

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