CN116208745A - Dock ship berthing monitoring and recording system and method - Google Patents
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Abstract
The invention provides a dock ship berthing monitoring and recording system and a dock ship berthing monitoring and recording method, which are beneficial to promoting the realization of digital reform of port safety supervision, promote the conversion of a port operation supervision mode from passive manual polling check driven by an operation reporting plan at present to intelligent supervision through automatic monitoring and recording of dock ship berthing, overcome the problems of supervision deficiency caused by inaccurate reporting operation plan, incapability of full-time staring by supervision staff, difficult storage of massive port video monitoring data and the like, promote the construction of digital trace and full-flow supervision of port operation, and lay a solid foundation for coping with rapidly-increased port berths and port video monitoring quantity and for the high-speed development of port navigation.
Description
Technical Field
The invention relates to the field of data analysis application, in particular to a dock ship berthing monitoring and recording system and a dock ship berthing monitoring and recording method.
Background
At present, ports in China enter a development stage from large to strong, so that the development of wisdom, safety and green is accelerated, and the necessary trend of promoting the high-quality development of the port aviation industry is achieved. Along with the rapid increase of the number of wharfs berths, the port safety supervision has the characteristics of multiple points, wide range and large quantity, has the problems of high safety risk, strong manual dependence, low supervision efficiency and the like, and becomes a bottleneck problem for restricting the port development, so that the port safety supervision needs to be researched and solved.
Current regulatory means for port operations are classified into on-site inspection and off-site inspection. The limitation of on-site inspector programming cannot realize comprehensive inspection of the wharf in the jurisdiction; however, if the monitoring is performed off-site, the problems of delayed or inaccurate reporting information, limited monitoring observation range, large amount of manual operation and the like exist, and the effective port safety supervision effect cannot be brought into play in time.
Disclosure of Invention
In order to improve at least one of the above technical problems, an object of the present invention is to provide a dock vessel berthing monitoring and recording system, which is used for overcoming the problems of inaccurate reporting operation plan, lack of supervision caused by incapability of full time focusing on supervision by a supervisory personnel, and the like, and pushing a port operation supervision mode to be changed from passive manual polling check driven by an operation reporting plan to intelligent supervision.
In order to achieve the above object, a technical solution of the first aspect of the present invention provides a dock vessel berthing monitoring and recording system, which includes a port video monitoring system, a vessel automatic identification system (abbreviated as AIS), a dock radar, a data processing unit, and a port supervision platform. The port video monitoring is used for collecting video image pictures around the port berth in real time; the ship automatic identification system is used for receiving AIS data which are dynamically sent by ships in the nearby sea area and comprise dynamic information, static information and voyage information; the wharf radar is used for actively detecting and identifying ship targets at berths and tracking navigation tracks of the ship targets so as to realize ship supervision when the ship automatic identification system is not applicable; the data processing unit is respectively connected with the port video monitoring system, the ship automatic identification system and the wharf radar and is used for acquiring video image pictures, AIS data or detection data of the wharf radar and acquiring ship characteristic information according to the video image pictures, AIS data or detection data; the port supervision platform is connected with the data processing unit and is used for carrying out port operation risk assessment according to the AIS data and the ship characteristic information associated port business information data.
The technical scheme of the second aspect of the invention provides a dock ship berthing monitoring and recording method, which comprises the following steps:
step S1, acquiring a ship berthing event at the front edge of a wharf;
step S2, responding to a ship berthing event, identifying a ship target entering a berthing area, controlling port video monitoring in a linkage mode to automatically snapshot the ship target before berthing at a wharf berthing position, and extracting ship characteristic information from snapshot images or terrible video;
step S3, identifying a ship berthing wharf: judging whether the ship is berthed on the wharf front according to the ship dynamic information of the ship target and berthing front space information; the ship dynamic information comprises position information, navigational speed information and heading information;
step S5, business association analysis: if the ship target is berthed on the wharf, associating port business information data according to the ship dynamic information and the extracted ship characteristic information, and carrying out port operation risk assessment based on a preset port operation risk model.
According to the dock ship berthing monitoring and recording method, the ship target is terrible before the ship berths, and the detailed data about the ship target, namely the ship characteristic information, is acquired. Compared with the prior art that detailed data of a ship target are acquired after the ship approaches the wharf, the problem that the ship target with risk cannot be effectively monitored in time is solved, risk assessment and safety early warning can be carried out before the ship target approaches the wharf, the current situation of 'passive' or 'post' monitoring is changed, and the port safety monitoring efficacy is effectively exerted.
In addition, the dock ship berthing monitoring and recording method in the technical scheme provided by the invention can also have the following additional technical characteristics:
in the above technical solution, step S1 includes:
s11, real-time receiving and calculating AIS data, and obtaining dynamic information, static information and voyage information of a real-time position of a ship target in a monitoring sea area;
step S12, continuously tracking real-time dynamic information of a ship target, and identifying navigation states of the tracked ship target, including a navigation state, a berthing state and a anchoring state;
step S13, acquiring electronic fence space information of a berthing operation area of the wharf, and acquiring berthing and leaving events of the ship at the front edge of the wharf according to the real-time dynamic information of the ship target and the electronic fence space information of the berthing operation area of the wharf.
In other embodiments, step S1 includes:
step S14, adopting a radar to actively detect and identify a ship target at a berthing position, tracking a navigation track of the ship target, and acquiring a ship berthing and berthing event at the front edge of a wharf.
In any of the above solutions, step S2 includes:
step S21, position calculation: calculating the position relation between the ship target and the port video monitoring according to the ship target position, and determining control attitude data of the port video monitoring according to the position relation;
step S22, linkage control: and controlling port video monitoring equipment according to the control gesture data, and roughly aiming the monitoring visual angle at the ship target.
Step S23, video recognition: based on video image processing, detecting a ship target in a video image in real time, and judging whether the ship target is the ship target; if the ship target is the ship target, filtering an interference target in the monitoring picture according to the course and the navigational speed data of the ship target, and aligning the acquired axis of the ship target with a central rectangular frame of the monitoring picture;
step S24, detail snapshot: the method comprises the steps of performing sectional detail snapshot on the whole body of a ship target by integrating length and width information and position information of the ship target to generate a plurality of ship target images;
step S25, image stitching: image stitching is carried out on a plurality of ship pictures which are captured in detail, so that a complete ship picture is formed;
step S26, feature extraction: and extracting ship characteristic information, including ship type, ship name and ship overload judging result, of the complete ship picture by using a deep learning technology.
In any of the above embodiments, step S5 includes:
identifying a ship target according to the ship characteristic information, and reading associated port service information of the ship target; the associated port service information data comprises historical data information of the ship target and declaration information of the berthing;
performing risk assessment according to historical data information of the ship target to obtain a first risk assessment value;
carrying out consistency comparison on the ship characteristic information and the declaration information, and determining a second risk assessment value according to a consistency comparison result;
carrying the ship dynamic information and the ship characteristic information into a preset harbor operation risk model to obtain a third risk assessment value;
and obtaining a final port operation risk evaluation value according to all the risk evaluation values.
In any of the above embodiments, after step S3, the method further includes: step S4, capturing ship berthing videos: if the ship target is berthed on the front edge of the wharf, intercepting a process video segment from entering the berthing electronic fence to berthing on the front edge of the wharf as key information data of the ship berthing wharf operation; after step S5, the method further comprises: step S6, event recording and reminding: and recording the moment of berthing the ship to the wharf, the process video record, the ship snap-shot picture, the associated business information and the risk assessment result in the database, and pushing the result to the terminal for the port supervisory personnel to view.
In summary, the dock ship berthing monitoring and recording system and method provided by the invention are beneficial to promoting the realization of digital reform of the dock safety supervision, and through the automatic monitoring and recording of dock ship berthing, the port operation supervision mode is promoted to be changed from the passive manual polling check driven by the current operation declaration plan to the intelligent supervision, the problems of supervision deficiency caused by inaccurate declaration operation plan, incapability of full-time staring by supervision staff, difficult storage of massive port video monitoring data and the like are overcome, the digital trace and full-flow supervision of port operation are promoted to be constructed, and a solid foundation is laid for coping with the rapidly-increased port berths and port video monitoring quantity, and the high-speed development of port navigation.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, or may be learned by practice of the invention.
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The foregoing and/or additional aspects and advantages of the invention will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
fig. 1 is a schematic composition diagram of a quay ship berthing monitoring and recording system according to some embodiments of the invention.
Fig. 2 is a block flow diagram of a dock vessel berthing monitoring and recording method of some embodiments of the invention.
Fig. 3 is a schematic illustration of a dock vessel berthing in accordance with some embodiments of the invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
Some embodiments of the present application provide a dock vessel berthing monitoring and recording system, which realizes automation and intellectualization of supervision by fusing a vessel behavior recognition technology, a space-time intelligent technology, a video intelligent technology, and the like. The system comprises 5 parts of port video monitoring, a ship Automatic Identification System (AIS), a wharf radar, a data processing unit and a port supervision platform, as shown in figure 1.
The video monitoring of the port usually adopts a dome camera video monitoring, is deployed at a high point near the berth of the wharf, can acquire video image pictures around the berth of the port in real time, returns data to the data processing unit in real time in a video stream mode, and can receive a video monitoring control instruction to realize attitude control, focusing control and the like. The AIS is generally deployed at a high point near a port shoreline and is used for receiving AIS data which is dynamically transmitted by ships in the nearby sea area and comprises dynamic information, static information and voyage information.
The dock radar is usually deployed at the front edge of the dock and is used for actively detecting and identifying ship targets at berths, so that the supervision problem of the ship with the AIS partially closed is mainly solved. The data processing unit is used as a service unit for data association processing and equipment linkage control. The port supervision platform is a comprehensive application service platform oriented to port supervision, integrates information data of a port service system, a ship information system and a wharf ship berthing monitoring and recording system, and provides digitalized and informationized application service for supervision personnel.
Some embodiments of the present application provide a dock vessel berthing monitoring and recording method.
The dock ship berthing monitoring and recording method in the embodiment comprises the following specific steps:
1. AIS receiving and analyzing: and acquiring real-time position dynamic information, static information and voyage information of a ship target in the observation and monitoring sea area by receiving and resolving shore-based/satellite-borne AIS data in real time.
2. And (3) identifying ship navigation states: the navigation state of the ship target is identified and monitored by continuously tracking the real-time dynamic information of the ship target, including navigation, berthing, anchoring and the like, and comprehensive discrimination can be further carried out by combining with port geographic information (dock berth, channel, anchor information) and the like.
3. Dock electronic fence monitoring: and (5) automatically monitoring the event of entering and exiting the electronic fence of the ship according to real-time AIS dynamic information (longitude and latitude, course, navigational speed and the like) of the ship target and the space information of the electronic fence of the dock berth operating area, and triggering the step (5).
4. Dock radar monitoring: and (5) according to the real-time data calculation and analysis of the wharf radar detection, judging and identifying the ship berthing and berthing leaving events at the front edge of the wharf, making up the ship berthing monitoring discovery problem of partially closing the AIS signal, and triggering the step (5) when the ship berthing wharf is discovered.
5. Port video monitoring linkage: according to dock electronic fence monitoring or dock radar monitoring, identifying and finding a berthing ship target, controlling port video monitoring in a linkage mode to automatically snapshot and record the ship target before berthing the dock, and extracting ship characteristic information.
5.1, position calculation: and calculating the position relation with the port video monitoring according to the ship target position, and acquiring port video monitoring control attitude data.
5.2, linkage control: and controlling port video monitoring equipment according to the calculated attitude data, and coarsely aiming the monitoring visual angle at the ship target.
5.3, video identification: based on video image processing, detecting a ship target in a video image in real time, judging whether the ship target is the ship target, simultaneously filtering an interference target in a monitoring picture by combining heading and navigational speed data monitored by AIS or wharf radar, and aligning an axis of the acquired ship target with a central rectangular frame (a central point position and a length-width normalization value) of the monitoring picture. (preferably, the Yolo 5 algorithm is used as the basic algorithm for the marine vessel target recognition model in consideration of the performance and real-time requirements of the detection algorithm.)
5.4, detail snapshot: and (3) performing sectional detail snapshot on the whole body of the ship target by combining the length and width information and the position information of the ship target, so as to generate a plurality of ship target images with rich details.
5.5, image stitching: and performing image stitching on the multiple ship pictures captured in detail to form a complete ship picture.
5.6, extracting features: and carrying out ship type discrimination, ship name extraction, ship feature (ship length and ship width) extraction, ship overload identification and the like on the ship images with rich snapshot details by utilizing a deep learning technology.
6. And (5) identifying a ship berthing wharf: and comprehensively judging whether the ship is berthed on the wharf front by combining the dynamic information (position, navigational speed and heading) of the ship and the berthing front space information.
7. Intercepting ship berthing video: and intercepting a process video clip from entering the dock berthing electronic fence to berthing on the front edge of the dock berthing as key information data of the operation of berthing the ship on the dock.
8. And (3) business association analysis: and according to AIS information and extracted ship characteristic information (ship name or IMO or MMSI), associating port service information data, and carrying out port operation risk assessment based on a port operation risk model (which can be constructed based on the relevant regulations of the existing risk level evaluation standard).
9. Event recording and reminding: the moment of berthing the ship at the wharf, the process video record, the ship snap-shot picture, the associated business information, the risk assessment information and the like are recorded in detail, and the method can be used as a piece of port operation dynamic information and risk early warning pushing port supervision personnel and can be used as a port operation database record, so that a data foundation is laid for further port intelligent supervision.
At present, some related technologies propose a method for identifying loading and unloading events of a container terminal by means of AIS data, firstly identifying the static events of all container ships in a port, and then referring to the distance between the ships and berths, the change angle of the ship heading and the static time, and classifying the identified static events into loading and unloading events and non-loading and unloading events by training a support vector machine (Support Vector Machine, SVM) classifier. The method is objective, real-time and efficient, but is only applicable to large container terminals (with complete ship information) and is not applicable to handling event identification of general terminals.
Some related art proposals are applicable to intelligent handling event recognition methods for general docks. First, AIS data is extracted near the departure port loading berth so that the screened vessels may only be in a state of long-term stay (including loading vessels, auxiliary vessels and patrol vessels) through which the screened vessels travel, stay briefly. Then, the stationary event is identified by clustering the interval time and the geographic distance of the adjacent tracks of the ship. Finally, sorting and screening loading and unloading events from the static events. The example verification result shows that the loading and unloading event identification model provided by the method has higher accuracy and recall rate, and the time stamp of the beginning and the end of the identified loading and unloading event and the loading and unloading berth are also very accurate.
The technology is more in "post" statistical analysis of port operation, and does not meet the requirement of real-time supervision application, and because the ship body type of berthing the wharf usually exceeds the frame of port video monitoring, when the ship berthes to the wharf, the video frame usually can only snap on to the local information thereof, and part of the information can be blocked by a gantry crane or a facility at the front edge of the wharf, and the useful information can not be extracted "post".
In addition, in other related technologies, the proposed ship berthing supervision system acquires information of berthing or leaving of a ship in real time through a signal collector arranged on the outer side of a berth, and then scans and identifies the information (including information such as a ship name, MMSI, IMO and the like) of a ship body by using a camera so as to implement ship berthing supervision, but the problem that the ship is triggered by berthing errors exists, and meanwhile, the identification of the ship is based on a video picture of port video monitoring, but the ship is intelligently analyzed by video monitoring after berthing to the wharf, so that complete ship body information cannot be acquired for a large-sized wharf, and the practical application effect is poor.
In other related technologies, the berth supervision system and the berth supervision method based on satellite positioning and video monitoring technology can extract character number information on ships, and correlate AIS data with scheduling business data to implement port private, illegal and overtime berth behaviors for discovery and identification, however, video image processing is highly dependent on training data and application scenes, real-time video processing calculation amount of multi-channel videos is large, meanwhile, the influence of illumination and weather is large, ships berthed at wharfs are blocked to a certain extent, video image analysis technology cannot guarantee that ship body information is acquired, and application difficulty is large.
The three-dimensional ship supervision platform system of the AIS system, the video monitoring system and the business system is integrated with the ship, port and cargo integrated information service system in other related technologies, and the three-dimensional ship supervision platform system provides functions of manual filling, inquiring and statistical analysis for dock dispatching personnel for dock management, so that dock management is enhanced. The patent still uses traditional manual entry methods, which are inefficient and do not provide adequate accuracy.
Other related art ship abnormal behavior recognition methods based on navigation track features provide for monitoring and abnormal recognition of ship navigation compliance by using anchor-forbidden ground and channel region information. However, the method lacks design consideration on dock berth supervision, lacks monitoring on closing AIS ships, and lacks video monitoring to visually monitor and record target information.
In summary, compared with the related art, the invention surrounds the port safety supervision requirement, and provides a digital system and method aiming at the real-time supervision scene of berthing of a ship at a wharf, which integrates space-time intelligence and video intelligence technologies, utilizes AIS, electronic fence and wharf radar multisource integration to trigger and identify a ship berthing event, and controls port video monitoring in a linkage way to automatically snapshot and record the berthing ship, extract information, correlate port business data and ship file information, and realize risk assessment and safety early warning on the berthing ship. The technology solves the problems of supervision deficiency and the like caused by inaccurate reporting operation plan and incapability of full-time staring by supervision staff, and promotes the port operation supervision mode to be changed from passive manual polling check driven by the operation reporting plan to intelligent supervision.
In addition, by applying the dock ship berthing monitoring and recording method provided by the invention, the digital and intelligent level of port safety supervision can be improved, and the digital trace record of port operation supervision is constructed by digital means so as to balance the contradiction between the rapidly developed port shipping industry and the safety supervision requirement, thereby promoting the efficient, safe and intelligent development of port operation. Secondly, the port safety supervision work with heavy tasks and the limited supervision staff compiling can be balanced, the pertinence, timeliness and comprehensiveness of supervision are improved through a digital means, the port operation supervision mode is promoted to be changed from the passive manual polling view driven by the operation reporting plan at present to the intelligent supervision, and the problems that the reporting operation plan is inaccurate, supervision staff cannot focus on the supervision in full time, and the like are solved. And thirdly, converting massive port video monitoring data into structural characteristic data through a video intelligent technology, solving the problems of difficult storage of the massive port video monitoring data and the like, and laying a data foundation for monitoring, identifying and early warning the berthing of the ship at the lifting wharf through incremental learning of the berthing data of the massive ship.
In the description of the present specification, the terms "one embodiment," "some embodiments," "particular embodiments," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A dock vessel berthing monitoring and recording system, comprising:
the port video monitoring is used for collecting video image pictures around the port berth in real time;
the ship automatic identification system is used for receiving AIS data which are dynamically sent by ships in the nearby sea area and comprise dynamic information, static information and voyage information;
the wharf radar is used for actively detecting and identifying ship targets at berths and tracking navigation tracks of the ship targets so as to realize ship supervision when the ship automatic identification system is not applicable;
the data processing unit is respectively connected with the port video monitoring system, the ship automatic identification system and the wharf radar and is used for acquiring video image pictures, AIS data or detection data of the wharf radar and acquiring ship characteristic information according to the video image pictures, AIS data or detection data;
and the port supervision platform is connected with the data processing unit and is used for carrying out port operation risk assessment according to the AIS data and the ship characteristic information associated port business information data.
2. The dock ship berthing monitoring and recording method is characterized by comprising the following steps of:
step S1, acquiring a ship berthing event at the front edge of a wharf;
step S2, responding to a ship berthing event, identifying a ship target entering a berthing area, controlling port video monitoring in a linkage mode to automatically snapshot the ship target before berthing at a wharf berthing position, and extracting ship characteristic information from snapshot images or terrible video;
step S3, identifying a ship berthing wharf: judging whether the ship is berthed on the wharf front according to the ship dynamic information of the ship target and berthing front space information; wherein the ship dynamic information comprises position information, navigational speed information and heading information;
step S5, business association analysis: if the ship target is berthed on the wharf, associating port business information data according to the ship dynamic information and the extracted ship characteristic information, and carrying out port operation risk assessment based on a preset port operation risk model.
3. The dock vessel berthing monitoring and recording method according to claim 2, wherein the step S1 comprises:
s11, real-time receiving and calculating AIS data, and obtaining dynamic information, static information and voyage information of a real-time position of a ship target in a monitoring sea area;
step S12, continuously tracking real-time dynamic information of a ship target, and identifying navigation states of the tracked ship target, including a navigation state, a berthing state and a anchoring state;
step S13, acquiring electronic fence space information of a berthing operation area of the wharf, and acquiring berthing and leaving events of the ship at the front edge of the wharf according to the real-time dynamic information of the ship target and the electronic fence space information of the berthing operation area of the wharf.
4. The dock vessel berthing monitoring and recording method according to claim 2, wherein the step S1 comprises:
step S14, adopting a radar to actively detect and identify a ship target at a berthing position, tracking a navigation track of the ship target, and acquiring a ship berthing and berthing event at the front edge of a wharf.
5. The dock vessel berthing monitoring recording method according to any one of claims 2 to 4, wherein the step S2 includes:
step S21, position calculation: calculating the position relation between the ship target and the port video monitoring according to the ship target position, and determining control attitude data of the port video monitoring according to the position relation;
step S22, linkage control: and controlling port video monitoring equipment according to the control gesture data, and roughly aiming the monitoring visual angle at the ship target.
Step S23, video recognition: based on video image processing, detecting a ship target in a video image in real time, and judging whether the ship target is the ship target; if the ship target is the ship target, filtering an interference target in the monitoring picture according to the course and the navigational speed data of the ship target, and aligning the acquired axis of the ship target with a central rectangular frame of the monitoring picture;
step S24, detail snapshot: the method comprises the steps of performing sectional detail snapshot on the whole body of a ship target by integrating length and width information and position information of the ship target to generate a plurality of ship target images;
step S25, image stitching: image stitching is carried out on a plurality of ship pictures which are captured in detail, so that a complete ship picture is formed;
step S26, feature extraction: and extracting ship characteristic information, including ship type, ship name and ship overload judging result, of the complete ship picture by using a deep learning technology.
6. The dock vessel berthing monitoring recording method according to any one of claims 2 to 4, wherein the step S5 includes:
identifying a ship target according to the ship characteristic information, and reading associated port service information of the ship target; the relevant port service information data comprise historical data information of the ship target and declaration information of the berthing;
performing risk assessment according to historical data information of the ship target to obtain a first risk assessment value;
carrying out consistency comparison on the ship characteristic information and the declaration information, and determining a second risk assessment value according to a consistency comparison result;
carrying the ship dynamic information and the ship characteristic information into a preset harbor operation risk model to obtain a third risk assessment value;
and obtaining a final port operation risk evaluation value according to all the risk evaluation values.
7. The dock vessel berthing monitoring recording method of any one of claims 2 to 4, wherein,
after step S3, the method further comprises: step S4, capturing ship berthing videos: if the ship target is berthed on the front edge of the wharf, intercepting a process video segment from entering the berthing electronic fence to berthing on the front edge of the wharf as key information data of the ship berthing wharf operation;
after step S5, the method further comprises: step S6, event recording and reminding: and recording the moment of berthing the ship to the wharf, the process video record, the ship snap-shot picture, the associated business information and the risk assessment result in the database, and pushing the result to the terminal for the port supervisory personnel to view.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116634631A (en) * | 2023-06-09 | 2023-08-22 | 江苏唐城霓虹数码科技有限公司 | Intelligent control method and system for double lifting of port high-pole lamp for illumination monitoring |
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| CN116634631A (en) * | 2023-06-09 | 2023-08-22 | 江苏唐城霓虹数码科技有限公司 | Intelligent control method and system for double lifting of port high-pole lamp for illumination monitoring |
| CN116634631B (en) * | 2023-06-09 | 2024-01-12 | 江苏唐城霓虹数码科技有限公司 | Intelligent control method and system for double lifting of port high-pole lamp for illumination monitoring |
| CN116502782A (en) * | 2023-06-26 | 2023-07-28 | 中国水产科学研究院南海水产研究所 | Dynamic management method and system for entering and exiting ports of fishing port ships based on geographic information system |
| CN116502782B (en) * | 2023-06-26 | 2024-01-09 | 中国水产科学研究院南海水产研究所 | Dynamic management method and system for entering and exiting ports of fishing port ships based on geographic information system |
| CN117315573A (en) * | 2023-09-20 | 2023-12-29 | 亿海蓝（北京）数据技术股份公司 | Oil supply ship operation behavior identification method and system, electronic equipment and storage medium |
| CN117315573B (en) * | 2023-09-20 | 2024-06-04 | 亿海蓝（北京）数据技术股份公司 | Oil supply ship operation behavior identification method and system, electronic equipment and storage medium |
| CN117218601A (en) * | 2023-10-18 | 2023-12-12 | 亿海蓝（北京）数据技术股份公司 | Method and device for determining authenticity of ship leaning operation and readable storage medium |
| CN117218601B (en) * | 2023-10-18 | 2024-06-04 | 亿海蓝（北京）数据技术股份公司 | Method and device for determining authenticity of ship leaning operation and readable storage medium |
| CN117420566A (en) * | 2023-10-23 | 2024-01-19 | 长春理工大学 | Laser-assisted ship berthing method |
| CN117831019A (en) * | 2023-12-29 | 2024-04-05 | 亿海蓝（北京）数据技术股份公司 | Ship service data generation method and system, electronic equipment and storage medium |
| CN117636690A (en) * | 2024-01-24 | 2024-03-01 | 亿海蓝（北京）数据技术股份公司 | Ship voyage generation method and device, electronic equipment and readable storage medium |
| CN117636690B (en) * | 2024-01-24 | 2024-03-29 | 亿海蓝（北京）数据技术股份公司 | Ship voyage generation method and device, electronic equipment and readable storage medium |
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