CN115271612A - Logistics park safety monitoring method, device, equipment and storage medium - Google Patents
Logistics park safety monitoring method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of logistics parks, and discloses a method, a device, equipment and a storage medium for monitoring the safety of a logistics park. The method comprises the following steps: reading target monitoring data from a database, and analyzing the target monitoring data to obtain a target image corresponding to the park; preprocessing a target image, and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
Description
Technical Field
The invention relates to the technical field of logistics parks, in particular to a method, a device, equipment and a storage medium for monitoring the safety of a logistics park.
Background
At present, the logistics of China is rapidly developed, and relatively centralized industrial layout and a representative logistics intelligent park are formed. With the development of production of logistics enterprises and the gradual expansion of the scale of the production of the logistics enterprises, huge potential risks may exist in the field of the logistics park, accidents are prevented in the conventional logistics park through various measures such as manual safety detection, safety operation and hidden danger troubleshooting, and the risks are reduced.
The system for early warning risk management has too single function, such as vehicle waiting, has great dependence on inspection personnel, cannot monitor in real time, is easy to artificially tamper data, and has uncertain responsibility when the vehicle waiting time exceeds the real time, so that a comprehensive logistics park monitoring system needs to be built, the vehicle, personnel and site management capacity is improved, and the processes of pre-accident prevention, accident response, in-accident treatment and good recovery of an accident are ensured.
Disclosure of Invention
The method and the system mainly aim to analyze the park status data and perform early warning on the abnormal status data, effectively ensure timely troubleshooting and early warning of abnormal conditions of the logistics intelligent park and reduce potential safety hazards of the park.
The invention provides a safety monitoring method for a logistics park in a first aspect, which comprises the following steps: reading target monitoring data from a preset database, wherein the target monitoring data is data obtained by monitoring a target monitoring area; analyzing the target monitoring data to obtain a target image corresponding to the park, wherein the target image comprises a park entering person image, a target vehicle image, a park road image and a platform image; preprocessing the target image and setting an abnormal state threshold value of the park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds the abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
Optionally, in a first implementation manner of the first aspect of the present invention, before the reading the target monitoring data from the preset database, the method further includes: and acquiring data of target areas in the garden based on a plurality of data acquisition devices to obtain at least one group of target monitoring data, wherein the target areas comprise a plurality of monitoring areas.
Optionally, in a second implementation manner of the first aspect of the present invention, the preprocessing the target image and setting the abnormal state threshold of the campus includes: preprocessing the target image to obtain a vehicle image of a target vehicle; identifying the vehicle image to obtain vehicle data of the target vehicle; matching order data and a transportation scheme of the target vehicle from a preset database based on the vehicle data of the target vehicle; and setting an abnormal state threshold value of the park based on the order data and the transportation scheme.
Optionally, in a third implementation manner of the first aspect of the present invention, the preprocessing the target image and setting an abnormal state threshold of the campus further includes: preprocessing the target image to obtain a platform image; identifying the platform image to obtain platform data; extracting the platform data to obtain platform parking data, and obtaining a plurality of sampling points according to the platform parking data, the vehicle data and a preset parking distance; and setting an abnormal state threshold value of the park based on the plurality of sampling points and the pose data of the target vehicle.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the preprocessing the target image and setting an abnormal state threshold of the campus, further includes: performing feature extraction on the first image data to obtain the facial features of the persons entering the garden; comparing the facial features of the park entering personnel with facial feature data in a preset configuration file; if the facial features of the garden entering personnel are not matched with the facial feature data in the configuration file, the garden entering personnel are non-registered personnel; and acquiring audio data of the unregistered personnel, marking the number of the unregistered personnel based on the audio data, and setting an abnormal state threshold of the park.
Optionally, in a fifth implementation manner of the first aspect of the present invention, before the performing feature extraction on the first image data to obtain the facial features of the person entering the garden, the method further includes: and analyzing the target monitoring data to obtain first image data of the people entering the garden in the garden.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the performing behavior recognition processing on the target monitoring data to obtain a behavior recognition result corresponding to at least one group of the target monitoring data includes: performing behavior recognition processing on each video frame in at least one group of target monitoring data to obtain a behavior recognition result corresponding to each video frame; and performing data fusion on the behavior recognition result corresponding to each video frame to obtain at least one group of behavior recognition results corresponding to the target monitoring data.
The second aspect of the present invention provides a safety monitoring device for a logistics park, comprising: the system comprises a reading module, a processing module and a display module, wherein the reading module is used for reading target monitoring data from a preset database, and the target monitoring data is obtained by monitoring a target monitoring area; the first analysis module is used for analyzing the target monitoring data to obtain a target image corresponding to the garden, wherein the target image comprises a garden entering person image, a target vehicle image, a garden road image and a platform image; the preprocessing module is used for preprocessing the target image and setting an abnormal state threshold value of the park; the identification module is used for carrying out behavior identification processing on the target monitoring data to obtain behavior identification results corresponding to at least one group of target monitoring data; and the sending module is used for determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds the abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
Optionally, in a first implementation manner of the second aspect of the present invention, the safety monitoring apparatus for a logistics park further includes: and the data acquisition module is used for acquiring data of target areas in the garden based on a plurality of data acquisition devices to obtain at least one group of target monitoring data, wherein the target areas comprise a plurality of monitoring areas.
Optionally, in a second implementation manner of the second aspect of the present invention, the preprocessing module is specifically configured to: preprocessing the target image to obtain a vehicle image of a target vehicle; identifying the vehicle image to obtain vehicle data of the target vehicle; matching order data and a transportation scheme of the target vehicle from a preset database based on the vehicle data of the target vehicle; and setting an abnormal state threshold value of the park based on the order data and the transportation scheme.
Optionally, in a third implementation manner of the second aspect of the present invention, the first parsing module includes:
the analysis unit is used for preprocessing the target image to obtain a platform image; the identification unit is used for identifying the platform image to obtain platform data; the extraction unit is used for extracting the platform data to obtain platform parking data, and obtaining a plurality of sampling points according to the platform parking data, the vehicle data and a preset parking distance; and the setting unit is used for setting the abnormal state threshold value of the park on the basis of the plurality of sampling points and the pose data of the target vehicle.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the preprocessing module is further specifically configured to: performing feature extraction on the first image data to obtain the facial features of the persons entering the garden; comparing the facial features of the persons entering the garden with facial feature data in a preset configuration file; if the facial features of the garden entering personnel are not matched with the facial feature data in the configuration file, the garden entering personnel are not registered personnel; and acquiring audio data of the unregistered personnel, marking the number of the unregistered personnel based on the audio data, and setting an abnormal state threshold of the park.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the safety monitoring device for a logistics park further includes: and the second analysis module is used for analyzing the target monitoring data to obtain first image data of the people entering the garden in the garden.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the identification module is specifically configured to: performing behavior recognition processing on each video frame in at least one group of target monitoring data according to each group of target monitoring data in the at least one group of target monitoring data to obtain a behavior recognition result corresponding to each video frame; and performing data fusion on the behavior recognition result corresponding to each video frame to obtain at least one group of behavior recognition results corresponding to the target monitoring data.
The third aspect of the present invention provides a safety monitoring device for a logistics park, comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor calls the instructions in the memory to enable the logistics park safety monitoring equipment to execute the steps of the logistics park safety monitoring method.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the above-mentioned logistics park safety monitoring method.
According to the technical scheme provided by the invention, target monitoring data are read from a database and analyzed to obtain target images corresponding to the garden; preprocessing a target image, and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of a method for monitoring the safety of a logistics park according to the present invention;
fig. 2 is a schematic diagram of a second embodiment of the method for monitoring the safety of the logistics park provided by the invention;
fig. 3 is a schematic diagram of a third embodiment of the method for monitoring the safety of the logistics park provided by the invention;
fig. 4 is a schematic view of a first embodiment of a safety monitoring device for a logistics park, provided by the invention;
FIG. 5 is a schematic view of a second embodiment of the safety monitoring device for a logistics park, provided by the invention;
fig. 6 is a schematic diagram of an embodiment of a safety monitoring device for a logistics park, provided by the invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for monitoring the safety of a logistics park, and the technical scheme of the invention is that target monitoring data are firstly read from a database and analyzed to obtain a target image corresponding to the park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be implemented in other sequences than those illustrated or described herein. Moreover, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of an embodiment of the present invention is described below, and referring to fig. 1, a first embodiment of a method for monitoring the safety of a logistics park according to an embodiment of the present invention includes:
101. reading target monitoring data from a preset database, wherein the target monitoring data is data obtained by monitoring a target monitoring area;
in the embodiment, an acquisition platform is established for each key position in the intelligent logistics park; the collection platform includes the sensor, the information screening system, storage system and monitored control system, be connected with vehicle collection system on the sensor, platform collection system, temperature acquisition system, the electric power collection system, equipment collection system and personnel collection system, and the sensor is connected with the information screening system, the information screening system is connected with storage system, monitored control system is connected with storage system, processing platform includes classified information receiving system, information analysis system and signal output part, classified information receiving system is connected with the information analysis system, the information analysis system is connected with signal output part, the warning platform includes signal input part, a display, speaker and warning light all are connected with signal input part. The acquisition platform is used for acquiring monitoring data in each monitoring area.
102. Analyzing the target monitoring data to obtain a target image corresponding to the park, wherein the target image comprises a park entering person image, a target vehicle image, a park road image and a platform image;
in this embodiment, acquire vehicle, platform, equipment status data in the commodity circulation wisdom garden monitored data from gathering the platform: the vehicle data may include: a vehicle waiting trunk line, a loading and unloading operation branch line, a vehicle waiting branch line, a platform waiting timeout-trunk line and a loading and unloading operation timeout-trunk line; the dock data may include: platform number, platform name, platform type, bay upper section, bay lower section, belonging area and the like; the device status data may include: device name, device physical number, device type, device address, whether the device is on, and the like.
103. Preprocessing a target image and setting an abnormal state threshold value of a park;
in this embodiment, according to the acquired monitoring data, the abnormal state thresholds of the vehicle, the platform, and the equipment in the intelligent logistics park can be set: such as vehicle abnormal state: the method comprises the following steps of vehicle waiting overtime-trunk overtime of 15min, loading and unloading operation overtime-branch overtime of 30min, vehicle waiting overtime-branch overtime of 30min, platform waiting overtime-branch overtime of 15min, platform waiting overtime-trunk overtime of 20min and loading and unloading operation overtime-trunk overtime of 25min. The vehicle overtime state threshold is obtained by averaging vehicle acquisition time data in the acquisition platform.
104. Performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data;
in this embodiment, the data processing server may perform behavior recognition processing on the at least one group of area monitoring data to obtain a target behavior recognition result corresponding to the at least one group of area monitoring data.
Specifically, firstly, for each group of regional monitoring data in the at least one group of regional monitoring data, performing behavior recognition processing on each frame of regional monitoring video frame included in the regional monitoring data to obtain a behavior recognition result corresponding to each frame of regional monitoring video frame included in the regional monitoring data; and secondly, aiming at each group of regional monitoring data in the at least one group of regional monitoring data, fusing the behavior recognition results corresponding to each frame of regional monitoring video frame included in the regional monitoring data to obtain a target behavior recognition result corresponding to the regional monitoring data.
105. And determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
In this embodiment, when the vehicle, the platform, the equipment status data in the current commodity circulation wisdom garden in the collection platform is different with the status data who sets for, the system automatically acquires the difference data value, and according to the corresponding solution of difference data value automatic acquisition, send unusual data and solution to corresponding managers, handle after managers receive unusual data and solution again. By using the method, abnormal conditions of the logistics intelligent park are checked and early warned in time; the stable operation of vehicles, platforms and equipment is effectively guaranteed, and the safety factors of people and equipment of companies are improved.
In the embodiment of the invention, target monitoring data are read from a database and analyzed to obtain a target image corresponding to a park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
Referring to fig. 2, a second embodiment of the method for monitoring the safety of the logistics park according to the embodiment of the present invention includes:
201. based on a plurality of data acquisition devices, carrying out data acquisition on a target area in a park to obtain at least one group of target monitoring data;
in this embodiment, the data processing server is communicatively connected with a plurality of data acquisition terminal devices, the plurality of data acquisition terminal devices are respectively arranged in a plurality of monitoring areas, so, the data processing server can control at least one data acquisition terminal device among the plurality of data acquisition terminal devices to perform data acquisition on a corresponding monitoring area based on the device correlation information among the plurality of data acquisition terminal devices when determining that the target area needs to be subjected to data acquisition through the plurality of data acquisition terminal devices so as to realize area monitoring, and obtain at least one group of corresponding area monitoring data. Wherein the target area includes the plurality of monitoring areas.
Specifically, the data processing server is in communication connection with a plurality of data acquisition terminal devices, and the data acquisition terminal devices are respectively arranged in a plurality of monitoring areas, so that the data processing server can determine whether data acquisition is required to be performed on a target area through the data acquisition terminal devices to realize area monitoring. Wherein the target area may include the plurality of monitoring areas. The data processing server may control at least one data acquisition terminal device of the multiple data acquisition terminal devices to perform data acquisition on a corresponding monitoring area based on the device correlation information between the multiple data acquisition terminal devices, so as to obtain at least one set of area monitoring data (e.g., at least one area monitoring video, etc.) corresponding to the at least one data acquisition terminal device.
202. Reading target monitoring data from a preset database;
203. analyzing the target monitoring data to obtain a target image corresponding to the park;
204. preprocessing a target image to obtain a platform image, and identifying the platform image to obtain platform data;
in this embodiment, the platform is often regular in shape and raised above the ground, the floor area is also large, and the platform parking area can be understood as an area in a large range near the platform where vehicles can park. The platform data may include position data of a plurality of platform boundary points, the platform boundary points may be sequence points on the platform boundary, and due to the large floor space of the platform and the perception of the existence of blind areas, the data of the platform is different from common data structures, and the point sequence is often used to express the edge or boundary of the platform.
Specifically, whether the vehicle enters the platform parking area or not can be confirmed according to the mark on the map in the driving process of the vehicle, if so, whether the vehicle is in an indoor scene or not can be judged according to whether the vehicle enters the indoor area of the map, if so, the vehicle can be determined to enter the platform parking area of the indoor scene, the platform data generated by the sensing module can be read, and the platform data can be sent to the process communication service. The sensing module can acquire a platform image, identify point cloud data of a platform boundary and obtain position data of a plurality of platform boundary points, namely platform data.
205. The method comprises the steps of extracting platform data to obtain platform parking data, and obtaining a plurality of sampling points according to the platform parking data, vehicle data and a preset parking distance;
in this embodiment, the platform parking segment may be a partial segment that is most suitable for parking a vehicle in the entire boundary of the platform, the data of the platform parking segment includes position data of a plurality of target platform boundary points, and a connection line of the plurality of target platform boundary points is parallel to the sampling baseline, that is, the platform parking segment is parallel to the sampling baseline. The expected parking distance may be a preset expected distance between the body of the vehicle and the platform of the vehicle, and may be determined according to actual conditions. The sampling baseline can be understood as a straight line where the vehicle is expected to be parked, and can be generated in real time.
After the vehicle obtains the platform data, the plurality of platform boundary points can be connected to obtain a plurality of line segments, the longest line segment is determined as the platform parking segment, each point in the line segment is the target platform boundary point, the data of the platform parking segment is extracted from the platform data, and then a sampling baseline can be generated in real time according to the data of the platform parking segment, the vehicle width and the expected parking distance.
In some embodiments, generating a sampled baseline from the data of the dock docking section, the vehicle width, and the desired docking distance may include; fitting according to the data of the platform docking section to obtain a linear equation of the platform docking section; and determining a linear equation of a sampling base line according to the linear equation of the platform parking section, the vehicle width and the expected parking distance, wherein the sampling base line is parallel to the platform parking section.
206. Setting an abnormal state threshold value of the park based on the plurality of sampling points and the pose data of the target vehicle;
in this embodiment, sampling is performed according to a point from a preset endpoint of the platform docking section to a closest point of the sampling baseline, and a plurality of sampling points are obtained, including: determining a point on the sampling base line closest to the preset endpoint as a closest point; determining the closest point as an initial base point, moving the initial base point along the longitudinal direction according to the longitudinal sampling step length until the length of the dock parking section is reached, and obtaining a plurality of target base points; according to the initial base point and the target base point, generating a plurality of transverse sampling points according to a transverse sampling step length and a preset transverse distance; and determining the combination of the initial base point, the plurality of target base points and the plurality of transverse sampling points as a plurality of sampling points.
The longitudinal sampling step length and the transverse sampling step length can be set according to actual situations, and for example, both can be set to 10 centimeters. The preset transverse distance can be the longest distance of preset transverse sampling, and the distance is from a sampling base line, and the abnormal state threshold of the park is set according to the sampling point and the pose data of the target vehicle.
207. Performing behavior recognition processing on each video frame in the target monitoring data aiming at each group of target monitoring data in at least one group of target monitoring data to obtain a behavior recognition result corresponding to each video frame;
in this embodiment, first, for each group of area monitoring data in the at least one group of area monitoring data, it is determined whether a behavior recognition result corresponding to each frame of area monitoring video frame included in the area monitoring data is a first behavior recognition result, where the first behavior recognition result is used to characterize that a target behavior (such as violation) that does not meet a preconfigured target behavior condition exists in the corresponding monitoring area;
secondly, counting the number of regional monitoring video frames of which the corresponding behavior recognition result is the first behavior recognition result and included in the regional monitoring data aiming at each group of regional monitoring data in the at least one group of regional monitoring data to obtain the video frame counting frame number corresponding to the regional monitoring data; then, for each group of regional monitoring data in the at least one group of regional monitoring data, obtaining a target behavior identification result corresponding to the regional monitoring data based on the video frame counting frame number corresponding to the regional monitoring data.
208. Performing data fusion on the behavior recognition result corresponding to each video frame to obtain behavior recognition results corresponding to at least one group of target monitoring data;
in this embodiment, first, for each group of area monitoring data in the at least one group of area monitoring data, the video frame statistical frame number corresponding to the area monitoring data is determined as a target behavior identification result corresponding to the area monitoring data, where the target behavior identification result is used to represent the number of target behaviors that do not satisfy a preconfigured target behavior condition and exist in the corresponding monitoring area; or alternatively
Secondly, counting the number of regional monitoring video frames included in the regional monitoring data aiming at each group of regional monitoring data in the at least one group of regional monitoring data to obtain the statistical number of video frames corresponding to the regional monitoring data, obtaining the frame number ratio value of the video frames corresponding to the regional monitoring data based on the ratio value between the statistical frame number of the video frames corresponding to the regional monitoring data and the statistical number of the video frames, and determining the frame number ratio value of the video frames as a target behavior identification result corresponding to the regional monitoring data, wherein the target behavior identification result is used for representing the number of target behaviors which do not meet a preset target behavior condition and exist in the corresponding monitoring region.
209. And determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
In the embodiment of the invention, target monitoring data are read from a database and analyzed to obtain a target image corresponding to a park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
Referring to fig. 3, a third embodiment of the method for monitoring the safety of the logistics park according to the embodiment of the present invention includes:
301. reading target monitoring data from a preset database, wherein the target monitoring data are data obtained by monitoring a target monitoring area;
302. analyzing the target monitoring data to obtain a target image corresponding to the garden, wherein the target image comprises a garden entering person image, a target vehicle image, a garden road image and a platform image;
303. analyzing the target monitoring data to obtain a vehicle image of the target vehicle, and identifying the vehicle image to obtain vehicle data of the target vehicle;
in the embodiment, the target monitoring data are analyzed to obtain the vehicle image of the target vehicle, for vehicles in general operation, the vehicle to be loaded enters the park, the vehicle identification device at the gate of the park identifies the vehicle information, and the vehicle information is uploaded to the vehicle intelligent scheduling management cloud platform.
When a vehicle enters a park, the vehicle identification device identifies vehicle license plate information, guarantees that a vehicle voucher enters the park and is accurately managed, and is beneficial to realizing real-time monitoring and dynamic recording of the vehicle.
304. Matching order data and a transportation scheme of the target vehicle from a preset database based on the vehicle data of the target vehicle, and setting an abnormal state threshold value of the park based on the order data and the transportation scheme;
in this embodiment, planning a loading scheme for a target vehicle includes: and planning a loading scheme for the target vehicle by combining an intelligent optimization algorithm according to the queuing condition displayed on the platform display screen.
Optionally, planning a loading scheme for the target vehicle by combining an intelligent optimization algorithm according to the queuing condition displayed on the display screen of the platform, including: and planning a loading scheme for the target vehicle by combining an intelligent optimization algorithm according to the vehicle running condition displayed on the platform display screen and the working condition of the platform. The queuing condition displayed on the display screen of the platform can represent the condition of vehicles currently queued for loading, or can represent the working condition of the platform. For example, the vehicle order information and the order storage information are matched, and a loading sequence and a loading time section with the minimum time cost are planned for the vehicle by combining an intelligent optimization algorithm according to the queuing condition of the conventional platform.
Further, the park monitoring system can be used for managing each monitoring device, receiving the cloud platform notification, and monitoring whether the vehicle is loaded according to the path and whether the loading is finished.
305. Analyzing the target monitoring data to obtain first image data of persons entering the garden in the garden;
in this embodiment, the facial image acquisition device, for example, the high definition camera may be dispersedly disposed at a plurality of positions in the monitored area, so as to obtain target monitoring data from a plurality of viewpoints, analyze the target monitoring data, and obtain first image data of people entering the garden in the garden. Face recognition is simplified by imaging the person entering the garden from multiple viewpoints.
306. Extracting the features of the first image data to obtain the facial features of the garden entering personnel, and comparing the facial features of the garden entering personnel with the facial feature data in a preset configuration file;
in this embodiment, further, the facial features of the person entering the garden are extracted from the image data, so as to obtain the facial features of the person entering the garden. Comparing the obtained face features of the person entering the garden with stored face feature data, for example, if the face features of the person entering the garden are matched with the stored face feature data in the cloud storage unit, judging that the person entering the garden is a registration person in the garden; if not, the person entering the park is judged to be an unregistered person, and in order to reduce the potential safety hazard of the park, safety early warning measures are executed for the unregistered person in the embodiment.
307. If the facial features of the garden entering personnel are not matched with the facial feature data in the configuration file, the garden entering personnel are not registered personnel;
in this embodiment, if the facial features of the person entering the garden do not match the facial feature data in the configuration file, the person entering the garden is a non-registered person, audio data of the non-registered person is obtained, the keyword including the position information is extracted from the audio data, and an expected destination corresponding to the keyword is obtained from the configuration file.
308. Acquiring audio data of non-registered personnel, marking the number of the non-registered personnel based on the audio data, and setting an abnormal state threshold value of the park;
in this embodiment, the audio recognition model based on artificial intelligence may recognize keywords from audio data, and further, the keywords include "a certain company", "a certain park", and the like, and the audio recognition model is obtained by training a training sample including the keywords. Further, in the configuration file of the present embodiment, the keywords "a certain company", "a certain campus", and the like are associated with location information, for example, the expected destination of "a certain company" is in building No. 1, E; in this embodiment, the expected destination of the unregistered person is obtained from the audio data of the unregistered person in the manner of acquiring the keyword, and the number of the unregistered persons is marked based on the audio data, so as to set the abnormal state threshold of the campus.
309. Performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data;
310. and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
Steps 301-302 and 309-310 in this embodiment are similar to steps 101-102 and 104-105 in the first embodiment, and are not repeated here.
In the embodiment of the invention, target monitoring data are read from a database and analyzed to obtain a target image corresponding to a park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
With reference to fig. 4, the method for monitoring the safety of the logistics park in the embodiment of the present invention is described above, and a safety monitoring apparatus of the logistics park in the embodiment of the present invention is described below, where a first embodiment of the safety monitoring apparatus of the logistics park in the embodiment of the present invention includes:
the reading module 401 is configured to read target monitoring data from a preset database, where the target monitoring data is data obtained by monitoring a target monitoring area;
a first analyzing module 402, configured to analyze the target monitoring data to obtain a target image corresponding to the campus, where the target image includes a garden entering person image, a target vehicle image, a campus road image, and a dock image;
a preprocessing module 403, configured to preprocess the target image and set an abnormal state threshold of the campus;
an identifying module 404, configured to perform behavior identification processing on the target monitoring data to obtain a behavior identification result corresponding to at least one group of the target monitoring data;
a sending module 405, configured to determine current state data of the campus based on the behavior recognition result, determine whether the current state data exceeds the abnormal state threshold, and if so, send abnormal alarm information to a preset alarm center.
In the embodiment of the invention, target monitoring data are read from a database and analyzed to obtain a target image corresponding to a park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time investigation early warning, has reduced the potential safety hazard in garden.
Referring to fig. 5, a second embodiment of the safety monitoring device for a logistics park according to the embodiment of the present invention specifically includes:
a reading module 401, configured to read target monitoring data from a preset database, where the target monitoring data is obtained by monitoring a target monitoring area;
a first analyzing module 402, configured to analyze the target monitoring data to obtain a target image corresponding to the campus, where the target image includes a park entry person image, a target vehicle image, a campus road image, and a dock image;
a preprocessing module 403, configured to preprocess the target image and set an abnormal state threshold of the campus;
an identifying module 404, configured to perform behavior identification processing on the target monitoring data to obtain a behavior identification result corresponding to at least one group of the target monitoring data;
a sending module 405, configured to determine current state data of the campus based on the behavior recognition result, determine whether the current state data exceeds the abnormal state threshold, and send abnormal alarm information to a preset alarm center if the current state data exceeds the abnormal state threshold.
In this embodiment, the safety monitoring device for logistics park further includes:
the data acquisition module 406 is configured to perform data acquisition on a target area in the campus based on a plurality of data acquisition devices to obtain at least one set of target monitoring data, where the target area includes a plurality of monitoring areas.
In this embodiment, the preprocessing module 403 is specifically configured to:
preprocessing the target image to obtain a vehicle image of a target vehicle;
identifying the vehicle image to obtain vehicle data of the target vehicle;
matching order data and a transportation scheme of the target vehicle from a preset database based on the vehicle data of the target vehicle;
and setting an abnormal state threshold value of the park based on the order data and the transportation scheme.
In this embodiment, the first parsing module 402 includes:
the analysis unit 4021 is configured to pre-process the target image to obtain a dock image;
an identification unit 4022, configured to identify the platform image to obtain platform data;
the extraction unit 4023 is configured to extract the platform data to obtain platform stop data, and obtain a plurality of sampling points according to the platform stop data, the vehicle data and a preset stop distance;
a setting unit 4024, configured to set an abnormal state threshold of the campus based on the plurality of sampling points and the pose data of the target vehicle.
In this embodiment, the preprocessing module 403 is further specifically configured to:
performing feature extraction on the first image data to obtain the facial features of the persons entering the garden;
comparing the facial features of the persons entering the garden with facial feature data in a preset configuration file;
if the facial features of the garden entering personnel are not matched with the facial feature data in the configuration file, the garden entering personnel are not registered personnel;
and acquiring audio data of the unregistered personnel, marking the number of the unregistered personnel based on the audio data, and setting an abnormal state threshold of the park.
In this embodiment, the safety monitoring device for logistics park further includes:
and the second analysis module 407 is configured to analyze the target monitoring data to obtain first image data of people entering the park in the park.
In this embodiment, the identification module 404 is specifically configured to:
performing behavior recognition processing on each video frame in at least one group of target monitoring data according to each group of target monitoring data in the at least one group of target monitoring data to obtain a behavior recognition result corresponding to each video frame;
and performing data fusion on the behavior recognition result corresponding to each video frame to obtain the behavior recognition result corresponding to at least one group of target monitoring data.
In the embodiment of the invention, target monitoring data are read from a database and analyzed to obtain a target image corresponding to a park; preprocessing a target image and setting an abnormal state threshold value of a park; performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data; and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds an abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center. This scheme is through carrying out the analysis to garden status data, carries out the early warning to abnormal state data, has effectively ensured commodity circulation wisdom garden abnormal conditions in time the troubleshooting early warning, has reduced the potential safety hazard in garden.
Fig. 4 and 5 describe the logistics park safety monitoring apparatus in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the logistics park safety monitoring apparatus in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 6 is a schematic structural diagram of a logistics park safety monitoring apparatus according to an embodiment of the present invention, where the logistics park safety monitoring apparatus 600 may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing applications 633 or data 632. Memory 620 and storage medium 630 may be, among other things, transitory or persistent storage. The program stored in the storage medium 630 may include one or more modules (not shown), each of which may include a series of instructions for the logistics park security monitoring apparatus 600. Further, the processor 610 may be configured to communicate with the storage medium 630, and execute a series of instruction operations in the storage medium 630 on the logistics park safety monitoring apparatus 600, so as to implement the steps of the logistics park safety monitoring method provided by the above-mentioned method embodiments.
The logistics park security monitoring apparatus 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input-output interfaces 660, and/or one or more operating systems 631, such as Windows server, mac OS X, unix, linux, freeBSD, and so on. Those skilled in the art will appreciate that the configuration of the logistics park safety monitoring apparatus shown in fig. 6 does not constitute a limitation of the logistics park safety monitoring apparatus provided herein, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, or a volatile computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the instructions are executed on a computer, the instructions cause the computer to execute the steps of the logistics park security monitoring method.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is substantially or partly contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A safety monitoring method for a logistics park is characterized by comprising the following steps:
reading target monitoring data from a preset database, wherein the target monitoring data are obtained by monitoring a target monitoring area;
analyzing the target monitoring data to obtain a target image corresponding to the park, wherein the target image comprises a park entering person image, a target vehicle image, a park road image and a platform image;
preprocessing the target image and setting an abnormal state threshold value of the park;
performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of target monitoring data;
and determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds the abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
2. The logistics park safety monitoring method of claim 1, wherein before reading the target monitoring data from the preset database, further comprising:
and based on a plurality of data acquisition devices, carrying out data acquisition on target areas in the park to obtain at least one group of target monitoring data, wherein the target areas comprise a plurality of monitoring areas.
3. The logistics park safety monitoring method of claim 1, wherein the preprocessing of the target image and the setting of the abnormal state threshold of the park comprise:
preprocessing the target image to obtain a vehicle image of a target vehicle;
identifying the vehicle image to obtain vehicle data of the target vehicle;
matching order data and a transportation scheme of the target vehicle from a preset database based on the vehicle data of the target vehicle;
and setting an abnormal state threshold value of the park based on the order data and the transportation scheme.
4. The method according to claim 1, wherein the preprocessing the target image and setting the threshold value of the abnormal state of the park further comprises:
preprocessing the target image to obtain a platform image;
identifying the platform image to obtain platform data;
extracting the platform data to obtain platform parking data, and obtaining a plurality of sampling points according to the platform parking data, the vehicle data and a preset parking distance;
and setting an abnormal state threshold value of the park based on the plurality of sampling points and the pose data of the target vehicle.
5. The method according to claim 1, wherein the preprocessing the target image and setting the threshold value of the abnormal state of the park further comprises:
performing feature extraction on the first image data to obtain the facial features of the persons entering the garden;
comparing the facial features of the persons entering the garden with facial feature data in a preset configuration file;
if the facial features of the garden entering personnel are not matched with the facial feature data in the configuration file, the garden entering personnel are not registered personnel;
and acquiring audio data of the unregistered personnel, marking the number of the unregistered personnel based on the audio data, and setting an abnormal state threshold of the park.
6. The logistics park safety monitoring method of claim 5, wherein before the feature extraction is performed on the first image data to obtain the facial features of the park entering personnel, the method further comprises:
and analyzing the target monitoring data to obtain first image data of the people entering the garden in the garden.
7. The logistics park safety monitoring method of claim 1, wherein the performing behavior recognition processing on the target monitoring data to obtain behavior recognition results corresponding to at least one group of the target monitoring data comprises:
performing behavior recognition processing on each video frame in at least one group of target monitoring data according to each group of target monitoring data in the at least one group of target monitoring data to obtain a behavior recognition result corresponding to each video frame;
and performing data fusion on the behavior recognition result corresponding to each video frame to obtain at least one group of behavior recognition results corresponding to the target monitoring data.
8. The utility model provides a commodity circulation garden safety monitoring device which characterized in that, commodity circulation garden safety monitoring device includes:
the system comprises a reading module, a processing module and a display module, wherein the reading module is used for reading target monitoring data from a preset database, and the target monitoring data is obtained by monitoring a target monitoring area;
the first analysis module is used for analyzing the target monitoring data to obtain a target image corresponding to the park, wherein the target image comprises a park entering person image, a target vehicle image, a park road image and a platform image;
the preprocessing module is used for preprocessing the target image and setting an abnormal state threshold of the park;
the identification module is used for carrying out behavior identification processing on the target monitoring data to obtain behavior identification results corresponding to at least one group of target monitoring data;
and the sending module is used for determining the current state data of the park based on the behavior recognition result, judging whether the current state data exceeds the abnormal state threshold value, and if so, sending abnormal alarm information to a preset alarm center.
9. The utility model provides a commodity circulation garden safety monitoring equipment which characterized in that, commodity circulation garden safety monitoring equipment includes: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the logistics park safety monitoring apparatus to perform the steps of the logistics park safety monitoring method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for logistics park safety monitoring of any one of claims 1 to 7.
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| CN202211018791.1A CN115271612A (en) | 2022-08-24 | 2022-08-24 | Logistics park safety monitoring method, device, equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116610921A (en) * | 2023-06-14 | 2023-08-18 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN117172463A (en) * | 2023-08-28 | 2023-12-05 | 湖北顺安伟业科技有限公司 | Park monitoring data management system |
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2022
- 2022-08-24 CN CN202211018791.1A patent/CN115271612A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116610921A (en) * | 2023-06-14 | 2023-08-18 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN116610921B (en) * | 2023-06-14 | 2024-02-09 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN117172463A (en) * | 2023-08-28 | 2023-12-05 | 湖北顺安伟业科技有限公司 | Park monitoring data management system |
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