Safety monitoring system for intelligent vehicle transfer and garage transfer

Abstract

The invention discloses a safety monitoring system for intelligent transfer of vehicles and garages. The safety monitoring system comprises a vehicle monitoring module, a personnel monitoring module, a communication module, a central monitoring system and an alarm module, the vehicle monitoring module is used for monitoring whether the vehicle moving direction, the vehicle moving speed and the vehicle parking state exceed the limit or not. The personnel monitoring module is combined with the vehicle monitoring module to divide a dangerous area and a risk area, and monitors whether personnel invade the dangerous area and the risk area; the communication module is used for realizing communication among all devices; the central monitoring system is used for processing information provided by each module, and controlling the alarm module to give an alarm when monitoring personnel invasion and vehicle parking and departure state overrun; the GPS positioning device and the vehicle positioning camera are used for positioning the position of the vehicle at the same time, the risk area is divided, whether people invade the currently-defined risk area or not is monitored in real time, and floating people are warned.

Description

Technical Field

[0001] The present invention relates to the field of safety monitoring technology, in particular to image feature extraction technology, two-dimensional plane-based dynamic trajectory prediction technology and real-time communication technology, and in particular to a safety monitoring system for intelligent vehicle and warehouse relocation. Background Art

[0002] With the rise of intelligence and networking, tasks such as vehicle relocation and warehouse relocation have been connected to the network to varying degrees. The benefits of this connection are very obvious, and each link has become easy to manage and visualize. While improving the efficiency of mobilization, it is inevitable that the corresponding commanders and operators in each link will be reduced. In addition, the vehicle relocation process is not a fixed time and fixed route, but a dynamic process. It is difficult to avoid the safety risks brought to various functional personnel during the vehicle relocation process by setting up safety signs in the warehouse. In addition, for the real-time vehicle relocation process, it is difficult for various functional personnel to obtain the movement trajectory and prediction of the vehicle during the relocation process, and they cannot make effective avoidance.

[0003] The present invention provides a security monitoring system for intelligent vehicle and warehouse relocation, the main purpose of which is to monitor the vehicle relocation process and the mobile personnel movement area, to define the risk area by analyzing the movement direction and path of the vehicle in the process of relocation, and to use personnel intrusion monitoring to monitor in real time whether mobile personnel exist in the defined area to give warnings and urgently stop the relocation process. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an intelligent safety monitoring system for vehicle relocation and warehouse transfer, which is used to avoid the safety risks brought to various functional personnel during the vehicle relocation process.

[0005] To achieve the above objectives, the present invention provides a security monitoring system for intelligent vehicle relocation and warehouse relocation, including: a vehicle monitoring module, a personnel monitoring module, a communication module, a central monitoring system and an alarm module. The vehicle monitoring module is used to monitor the vehicle movement direction, vehicle movement speed and whether the vehicle parking state exceeds the limit; The personnel monitoring module and the vehicle monitoring module divide the dangerous area and the risk area, and monitor whether the personnel invade the dangerous area and the risk area; The communication module is used to realize communication between all devices; The central monitoring system is used to process the information provided by each module, and control the alarm module to alarm when human intrusion and vehicle stop status exceed the limit are monitored.

[0006] Further: the vehicle monitoring module includes at least one vehicle positioning camera and at least one GPS positioning device placed on the vehicle body; The vehicle positioning camera and the GPS positioning device simultaneously detect the vehicle movement direction and vehicle movement speed in two different ways, and predict the vehicle movement trajectory according to the vehicle movement direction and vehicle movement speed, specifically in the following steps: S1: The vehicle positioning camera and the GPS positioning device sample the vehicle position image and GPS positioning information at the same period t; S2: Update GPS positioning information in real time, convert GPS positioning information into two-dimensional plane coordinates, and calculate the coordinate points of the current period GPS positioning information on the two-dimensional plane The coordinate point on the two-dimensional plane with the GPS positioning information of the previous cycle , and then obtain the vehicle movement direction K1 and vehicle movement speed V1; S3: updating the vehicle position image in real time, performing grayscale processing on the collected vehicle position images in real time, and then extracting the coordinates of the feature points in each vehicle position image, calculating the slope and movement distance of the feature point coordinates in the vehicle position image collected in the current cycle and the feature point coordinates in the vehicle position image collected in the previous cycle, and then obtaining the vehicle movement direction K2 and the vehicle movement speed V2; S4: Use K1 and K2 to further correct the direction of movement, and use V1 and V2 to correct the vehicle's speed; S5: Predicting the vehicle motion trajectory according to the corrected vehicle motion direction and the corrected vehicle motion speed.

[0007] Further: the vehicle monitoring module also includes at least two laser scanning radars for detecting whether the parking state of the vehicle exceeds the limit; The laser scanning radar emits short laser pulses and calculates the geometric dimensions of the vehicle by receiving echoes.

[0008] Further: the personnel monitoring module includes at least one personnel intrusion recognition camera, which monitors the movement status of mobile personnel in real time, and divides the dangerous area in conjunction with the vehicle monitoring module to monitor whether personnel invade the dangerous area, specifically: The personnel intrusion recognition camera uploads its own coordinates and the plane coordinate points of the monitoring range to the central monitoring system and converts them into coordinate points on a two-dimensional plane; At the same time, the central monitoring system receives the position of the vehicle in the vehicle monitoring module, converts it into a mass point on the two-dimensional plane, regards the vehicle motion trajectory and vehicle motion speed as the motion state of the mass point, and predicts the motion trajectory of the mass point on the two-dimensional plane based on the motion state analysis of the mass point; The central monitoring system classifies the coordinate points whose Euclidean distance from all coordinate points on the particle motion trajectory is greater than 0.5m and less than 5m as warning coordinate points, and classifies the coordinate points whose Euclidean distance from all coordinate points on the particle motion trajectory is less than 0.5m as alarm coordinate points; The central monitoring system divides the area corresponding to the coordinate point of the plane coordinate point of the monitoring range and the warning coordinate point as a risk area. When the personnel intrusion recognition camera detects the presence of mobile personnel in the risk area, the mobile personnel warning is triggered and the central monitoring system displays a yellow warning; The area corresponding to the coordinate point with the same plane coordinate point as the alarm coordinate point in the monitoring range is divided into a dangerous area. When the personnel intrusion recognition camera detects the presence of mobile personnel in the dangerous area, the mobile personnel alarm is triggered and the central monitoring system displays a red alarm.

[0009] Further: the communication module includes at least one encoder and at least one switch; The encoder adopts the high-precision digital video and audio codec standard H.264 / AVC technology; The switch uses a fourth-layer switch technology that integrates a second-layer switch technology and a third-layer switch technology; The fourth layer switch technology mainly analyzes the transport layer header information of the data packet, combines the application layer protocol, that is, the application protocol of the transport layer, based on content filtering and QoS service quality management, identifies and distinguishes different traffic volumes, and assigns different service levels to each flow.

[0010] Further: the central monitoring system includes a GSM network, at least one single-chip microcomputer and at least one computer; The GMS network uses the data transmission function SMS short message service and GPRS general packet radio service to collect the distributed monitoring point data of the vehicle monitoring module and the personnel monitoring module in real time; The single-chip microcomputer is used for data collection and preliminary processing, adopts MAX232 chip, and utilizes multi-threading technology and API functions to monitor multi-serial port communication events.

[0011] Further: S2 obtains the vehicle movement direction K1 by specifically using a tangent approximation method based on differentiation and tangent approximation, as follows: The current period GPS positioning information is mapped to the coordinate point on the two-dimensional plane The coordinate point on the two-dimensional plane with the GPS positioning information of the previous cycle Consider them as two extreme values ​​that tend to approach each other, and use the following formula to calculate their slope: ; Among them, Q is the coordinate point of the GPS positioning information of the current period on the two-dimensional plane; P is the coordinate point of the GPS positioning information in the previous cycle on the two-dimensional plane; The slope k is the real-time vehicle movement direction.

[0012] Furthermore: the S3 grayscale processing is based on feature extraction of shape-specific points and dynamic angle division. The environment image in each vehicle position image is processed into fixed background coordinates of a two-dimensional plane coordinate system using feature extraction of shape-specific points, and then the vehicle image in each vehicle position image is divided into feature coordinates using dynamic angles, thereby calculating the vehicle movement direction K2 and the vehicle movement speed V2.

[0013] The present invention locates the vehicle position simultaneously through the GPS positioning device and the vehicle positioning camera respectively, and uses the change trend of two-dimensional plane coordinate points and the change of image feature points to reflect the movement trajectory of the vehicle, and then divides the risk area. At the same time, a personnel intrusion recognition camera is used to monitor in real time whether there is any personnel intrusion into the currently designated risk area, so as to warn the mobile personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention and the technical solutions in the prior art, the drawings required for use in the embodiments and the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some implementation methods recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0015] Figure 1 The system architecture diagram of the present invention; Figure 2 This is a vehicle trajectory prediction flow chart of the present invention. DETAILED DESCRIPTION

[0016] The specific embodiments of the present invention are described in detail below, and the process of the specific embodiments is shown in the accompanying drawings, wherein the same reference numerals represent the same parameters from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0017] Additionally, in the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure; however, it is apparent that one or more embodiments may be practiced without these specific details.

[0018] See also Figure 1 , a system architecture diagram of the present invention; It includes: vehicle monitoring module, personnel monitoring module, communication module, central monitoring system and alarm module; the vehicle monitoring module is used to monitor the vehicle movement direction, vehicle movement speed and whether the vehicle parking status exceeds the limit; the personnel monitoring module and the vehicle monitoring module divide the dangerous area and risk area, and monitor whether the personnel invade the dangerous area and risk area; The communication module is used to realize the communication between all devices; the central monitoring system is used to process the information provided by each module, and control the alarm module to alarm when human intrusion and vehicle stop status exceed the limit are monitored.

[0019] Specifically: the vehicle monitoring module includes at least one vehicle positioning camera, at least one GPS positioning device installed on the vehicle body and two laser scanning radars; the vehicle positioning camera is used to monitor the vehicle position image; the GPS positioning device is used to update the vehicle position; the laser scanning radar is used to determine whether the vehicle parking status exceeds the limit; the personnel monitoring module includes at least one personnel intrusion identification camera, which is used to monitor the movement status of mobile personnel in real time and upload the coordinates of the monitoring range to facilitate the subsequent division of risk areas; the communication module includes at least one encoder and at least one switch. The encoder adopts the high-precision digital audio and video codec standard H.264 / AVC technology, and the switch uses integrated second-layer switch technology and third-layer switch The fourth-layer switch technology of computer technology, the fourth-layer switch technology mainly analyzes the transport layer header information of the data packet, combines the application layer protocol, that is, the application protocol of the transport layer, based on content filtering and QoS service quality management, identifies and distinguishes different traffic volumes, and assigns different service levels to each flow; the central monitoring system includes a GSM network, at least one single-chip microcomputer and at least one computer. The GMS network uses the data transmission function SMS short message service and GPRS general packet wireless service to collect real-time data from the scattered monitoring points of the vehicle monitoring module and the personnel monitoring module. The single-chip microcomputer is used for data collection and preliminary processing, using the MAX232 chip, and using multi-threading technology and API functions to monitor multi-serial port communication events.

[0020] See also Figure 2 , the vehicle trajectory prediction flow chart of the present invention comprises the following steps: S1: The vehicle positioning camera and the GPS positioning device sample the vehicle position image and GPS positioning information at the same period t; S2: Update GPS positioning information in real time, convert GPS positioning information into two-dimensional plane coordinates, calculate the coordinate points of the current period GPS positioning information on the two-dimensional plane and the coordinate points of the previous period GPS positioning information on the two-dimensional plane, and then obtain the vehicle movement direction K1 and vehicle movement speed V1; Specifically: the vehicle movement direction K1, the tangent approach method based on differentiation and tangent approximation is specifically used as follows: The current period GPS positioning information is mapped to the coordinate point on the two-dimensional plane The coordinate point on the two-dimensional plane with the GPS positioning information of the previous cycle Consider them as two extreme values ​​that tend to approach each other, and use the following formula to calculate their slope: ; Among them, Q is the coordinate point of the GPS positioning information of the current period on the two-dimensional plane; P is the coordinate point of the GPS positioning information in the previous cycle on the two-dimensional plane; The slope k is the real-time vehicle movement direction.

[0021] S3: updating the vehicle position image in real time, performing grayscale processing on the collected vehicle position images in real time, and then extracting the coordinates of the feature points in each vehicle position image, calculating the slope and movement distance of the feature point coordinates in the vehicle position image collected in the current cycle and the feature point coordinates in the vehicle position image collected in the previous cycle, and then obtaining the vehicle movement direction K2 and the vehicle movement speed V2; Specifically: the grayscale processing is based on the feature extraction of shape-specific points and dynamic angle division. The environment image in each vehicle position image is processed into a fixed background coordinate of a two-dimensional plane coordinate system using the feature extraction of shape-specific points. Then, the vehicle image in each vehicle position image is divided into feature coordinates using dynamic angles, thereby calculating the vehicle movement direction K2 and the vehicle movement speed V2; S4: Use K1 and K2 to further correct the direction of movement, and use V1 and V2 to correct the vehicle's speed; Specifically: the corrected motion direction is the average value of K1 and K2, and the corrected speed is the maximum value of V1 and V2; S5: predicting the vehicle motion trajectory according to the corrected vehicle motion direction and the corrected vehicle motion speed; and dividing the early warning coordinate points and the alarm coordinate points according to the predicted motion trajectory; Specifically: the central monitoring system classifies the coordinate points whose Euclidean distance from all coordinate points on the motion trajectory is greater than 0.5m and less than 5m as warning coordinate points, and classifies the coordinate points whose Euclidean distance from all coordinate points on the motion trajectory is less than 0.5m as alarm coordinate points.

[0022] Finally, the personnel monitoring module compares the coordinates of the monitored location in real time to see if they are warning coordinate points and alarm coordinate points, and divides them into risk areas and dangerous areas. When mobile personnel are detected entering risk areas and dangerous areas, the system will issue corresponding alarms.

[0023] The present invention predicts the movement trajectory of the vehicle through various monitoring modules, divides the dangerous area in combination with real-time monitoring, and monitors whether mobile personnel step into the dangerous area, thereby providing a warning to the mobile personnel.

[0024] The above is a very detailed description of one or more embodiments of the present invention, but the content is only a specific example of the present invention and cannot be considered to limit the scope of application of the present invention. Any other methods and changes proposed based on the content of the present invention should fall within the scope of patent protection of the present invention.

Claims

1. A safety monitoring system for intelligent vehicle and warehouse relocation, characterized in that: include: Vehicle monitoring module, personnel monitoring module, communication module, central monitoring system and alarm module; The vehicle monitoring module is used to monitor the vehicle movement direction, vehicle movement speed and whether the vehicle parking state exceeds the limit; The personnel monitoring module and the vehicle monitoring module divide the dangerous area and the risk area, and monitor whether the personnel invade the dangerous area and the risk area; The communication module is used to realize communication between all devices; The central monitoring system is used to process the information provided by each module, and control the alarm module to alarm when human intrusion and vehicle stop status exceed the limit are monitored.

2. According to claim 1, a safety monitoring system for intelligent vehicle and warehouse relocation is characterized in that: The vehicle monitoring module includes at least one vehicle positioning camera and at least one GPS positioning device placed on the vehicle body; The vehicle positioning camera and the GPS positioning device simultaneously detect the vehicle movement direction and vehicle movement speed in two different ways, and predict the vehicle movement trajectory according to the vehicle movement direction and vehicle movement speed, specifically in the following steps: S1: The vehicle positioning camera and the GPS positioning device sample the vehicle position image and GPS positioning information at the same period t; S2: Update GPS positioning information in real time, convert GPS positioning information into two-dimensional plane coordinates, calculate the coordinate point (x1, y1) of the current period GPS positioning information on the two-dimensional plane and the coordinate point (x0, y0) of the previous period GPS positioning information on the two-dimensional plane, and then obtain the vehicle movement direction K1 and vehicle movement speed V1; S3: updating the vehicle position image in real time, performing grayscale processing on the collected vehicle position images in real time, and then extracting the coordinates of the feature points in each vehicle position image, calculating the slope and movement distance of the feature point coordinates in the vehicle position image collected in the current cycle and the feature point coordinates in the vehicle position image collected in the previous cycle, and then obtaining the vehicle movement direction K2 and the vehicle movement speed V2; S4: Use K1 and K2 to further correct the movement direction, and use V1 and V2 to correct the vehicle movement speed; S5: Predicting the vehicle motion trajectory according to the corrected vehicle motion direction and the corrected vehicle motion speed.

3. According to claim 1, the intelligent vehicle and warehouse relocation safety monitoring system is characterized in that: The vehicle monitoring module also includes at least two laser scanning radars for detecting whether the parking state of the vehicle exceeds the limit; The laser scanning radar emits short laser pulses and calculates the geometric dimensions of the vehicle by receiving echoes.

4. According to claim 1, the intelligent vehicle and warehouse relocation safety monitoring system is characterized in that: The personnel monitoring module includes at least one personnel intrusion recognition camera, which monitors the movement status of mobile personnel in real time, and divides the dangerous area in conjunction with the vehicle monitoring module to monitor whether personnel invade the dangerous area. Specifically: The personnel intrusion recognition camera uploads its own coordinates and the plane coordinate points of the monitoring range to the central monitoring system and converts them into coordinate points on a two-dimensional plane; At the same time, the central monitoring system receives the position of the vehicle in the vehicle monitoring module, converts it into a mass point on the two-dimensional plane, regards the vehicle motion trajectory and vehicle motion speed as the motion state of the mass point, and predicts the motion trajectory of the mass point on the two-dimensional plane based on the motion state analysis of the mass point; The central monitoring system classifies the coordinate points whose Euclidean distance from all coordinate points on the particle motion trajectory is greater than 0.5m and less than 5m as warning coordinate points, and classifies the coordinate points whose Euclidean distance from all coordinate points on the particle motion trajectory is less than 0.5m as alarm coordinate points; The central monitoring system divides the area corresponding to the coordinate point of the plane coordinate point of the monitoring range and the warning coordinate point as a risk area. When the personnel intrusion recognition camera detects the presence of mobile personnel in the risk area, the mobile personnel warning is triggered and the central monitoring system displays a yellow warning; The area corresponding to the coordinate point with the same plane coordinate point as the alarm coordinate point in the monitoring range is divided into a dangerous area. When the personnel intrusion recognition camera detects the presence of mobile personnel in the dangerous area, the mobile personnel alarm is triggered and the central monitoring system displays a red alarm.

5. According to claim 1, the intelligent vehicle and warehouse relocation safety monitoring system is characterized in that: The communication module includes at least one encoder and at least one switch; The encoder adopts the high-precision digital video and audio codec standard H.264 / AVC technology; The switch uses a fourth-layer switch technology that integrates a second-layer switch technology and a third-layer switch technology; The fourth layer switch technology mainly analyzes the transport layer header information of the data packet, combines the application layer protocol, that is, the application protocol of the transport layer, based on content filtering and QoS service quality management, identifies and distinguishes different traffic volumes, and assigns different service levels to each flow.

6. The intelligent vehicle and warehouse relocation safety monitoring system according to claim 1 is characterized in that: The central monitoring system includes a GSM network, at least one single-chip microcomputer and at least one computer; The GMS network uses the data transmission function SMS short message service and GPRS general packet radio service to collect the distributed monitoring point data of the vehicle monitoring module and the personnel monitoring module in real time; The single-chip microcomputer is used for data collection and preliminary processing, adopts MAX232 chip, and utilizes multi-threading technology and API functions to monitor multi-serial port communication events.

7. The intelligent vehicle and warehouse relocation safety monitoring system according to claim 2 is characterized in that: The S2 obtains the vehicle movement direction K1 by using a tangent approximation method based on differentiation and tangent approximation, as follows: The coordinate point (x0, y0) of the current period GPS positioning information on the two-dimensional plane and the coordinate point (x1, y1) of the previous period GPS positioning information on the two-dimensional plane are regarded as two extreme values ​​tending to approach each other, and their slopes are calculated using the following formula: Among them, Q is the coordinate point of the GPS positioning information of the current period on the two-dimensional plane; P is the coordinate point of the GPS positioning information in the previous cycle on the two-dimensional plane; The slope k is the real-time vehicle movement direction.

8. The intelligent vehicle and warehouse relocation safety monitoring system according to claim 2 is characterized in that: The S3 grayscale processing is based on the feature extraction of shape-specific points and dynamic angle division. The environment image in each vehicle position image is processed into fixed background coordinates of a two-dimensional plane coordinate system using the feature extraction of shape-specific points. The vehicle image in each vehicle position image is then divided into feature coordinates using dynamic angles, thereby calculating the vehicle movement direction K2 and the vehicle movement speed V2.

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