Bridge ship collision accident early warning method and system based on multi-source data fusion

Abstract

The invention is suitable for the technical field of accident early warning, and particularly relates to a bridge ship collision accident early warning method and system based on multi-source data fusion, and the method comprises the steps: delimiting an early warning region of a bridge ship collision accident, drawing a shipping traffic map of the early warning region, marking all bridges, selecting risk point locations, and determining water diversion personnel. And configuring a one-to-one correspondence relationship between the risk point location and the water diversion personnel, defining the risk point location as a deployment position of a Bluetooth receiver, collecting a Bluetooth beacon signal, and uploading the Bluetooth beacon signal to a pre-constructed early warning processing platform. By determining the water diversion personnel, the position and state of the target ship can be mastered, human errors of shipping personnel are reduced, the accident occurrence probability is reduced, the navigation safety is further improved, and by establishing the communication link, the water diversion personnel can provide piloting guidance for the shipping personnel, and the risk assessment and prevention and control capability is enhanced; and the accuracy of accident early warning is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of accident early warning, and particularly relates to a bridge ship collision accident early warning method and system based on multi-source data fusion. Background Art

[0002] A bridge ship collision accident refers to a situation where a ship, during navigation, due to operational errors, weather factors, equipment failures or other reasons, hits a bridge structure, causing damage to the bridge or the ship, and may even lead to casualties or blockage of the waterway. Multi-source data refers to data from different sensors, monitoring systems and information platforms, including the positioning information, navigation speed, direction, weather conditions, sea current conditions, bridge structure status and traffic flow of the ship, etc.

[0003] In the existing early warning of bridge ship collision accidents, it generally relies on geographic information systems and the positioning data of ships, and combines the experience of ship crew for risk assessment. However, in unfamiliar and complex geographical environments (such as narrow waterways and special bridge designs, etc.), environmental factors have a greater impact on ship navigation, and it is impossible for humans to accurately judge the relative position between the ship and the bridge and the collision risk, resulting in limited early warning effects. To solve this problem, in large straits or ports, pilots are generally arranged to guide the shipping route.

[0004] Therefore, "how to use pilots for remote guidance" is the technical problem to be solved by the present invention. Summary of the Invention

[0005] The purpose of the present invention is to provide a bridge ship collision accident early warning method and system based on multi-source data fusion to solve the problem of "how to use pilots for remote guidance" proposed in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] A bridge ship collision accident early warning method based on multi-source data fusion, the method includes:

[0008] Define the early warning area of the bridge ship collision accident, draw the shipping traffic map of the early warning area, mark all the bridges, select risk points, determine the pilots, configure the one-to-one correspondence between the risk points and the pilots, and define the deployment positions of Bluetooth receivers for the risk points, collect Bluetooth beacon signals, and upload them to the pre-constructed early warning processing platform;

[0009] When the Bluetooth receiver receives a real-time signal, it defines the target ship, and via the early warning processing platform, sends a data reading request to the target ship. Using the edge devices pre-deployed at the deployment location, it receives multi-source data uploaded by the target ship, where the multi-source data at least includes: basic ship parameters, lidar monitoring data, AIS navigation data, ship control data, and video surveillance data. Based on the basic ship parameters, the risk level of the target ship is configured, where the risk level at least includes: high, medium, and low;

[0010] Judge whether the risk level of the target ship is low. If so, send a slow-down reminder to the target ship;

[0011] If not, define the bridge at the deployment location as a risk target, connect the equipment terminal of the pilot to the early warning processing platform, and open the reading permission of the multi-source data of the risk target. Via the edge device, establish a communication link between the equipment terminal and the target ship.

[0012] Further, the steps of demarcating the early warning area of the ship-bridge collision accident, drawing the shipping traffic map of the early warning area, marking all the bridges, selecting the risk points, and determining the pilot include:

[0013] Receive the accident notice uploaded by the pilot, establish a link between the edge device and the preset warning device, and trigger the activation of the warning device, where the warning device is deployed on the bridge road surface;

[0014] Configure the influencing factors of the ship-bridge collision accident, where the influencing factors at least include: meteorological environment and waterway busyness;

[0015] Embed a public notice section into the early warning processing platform, generate pilot information using the corresponding relationship, and upload the pilot information to the public notice section.

[0016] Further, the steps of configuring the one-to-one correspondence between the risk points and the pilots, defining the risk points as the deployment locations of the Bluetooth receivers, collecting Bluetooth beacon signals, and uploading them to the pre-constructed early warning processing platform include:

[0017] Establish a mapping between the Bluetooth beacon signal and the basic ship parameters;

[0018] Construct a signal query table, where the signal query table consists of signal items and parameter items, and send the signal query table to all edge devices in parallel.

[0019] Further, the method further includes:

[0020] Obtain the predetermined route of the target ship and configure the traveling direction;

[0021] Determine the arrival time of each risk point on the traveling direction, generate a passing schedule, and construct a notification rule.

[0022] Further, the step of, when the Bluetooth receiver receives a real-time signal, defining the target ship and sending a data reading request to the target ship via the early warning processing platform includes:

[0023] Embed a sleep mechanism into the Bluetooth receiver, and exit the sleep mechanism when the real-time signal is received;

[0024] Use the real-time signal to traverse the signal query table to obtain a target item, write the target item into a preset template to generate a prompt message, and send the prompt message to the terminal device.

[0025] Further, the step of configuring the risk level of the target ship based on the basic ship parameters includes:

[0026] Modify the risk level based on the influencing factors;

[0027] Construct a threshold set composed of several behavior thresholds, where each behavior threshold corresponds to at least one emergency response rule, and when the multi-source data exceeds the corresponding behavior threshold, trigger and start the corresponding emergency response rule.

[0028] Further, the method further includes:

[0029] Select accident black spots in the predetermined route, collect the environmental data at the accident black spots, and add the accident black spots to the deployment locations;

[0030] Define the Bluetooth receiver at the accident black spot as an additional device, and send the environmental data to the additional device.

[0031] Further, the system includes:

[0032] An upload module, used to delimit the early warning area of the bridge ship collision accident, draw the shipping traffic map of the early warning area, mark all the bridges, select risk points, determine the pilot, configure the one-to-one correspondence between the risk points and the pilot, define the risk points as the deployment locations of the Bluetooth receivers, collect Bluetooth beacon signals, and upload them to the pre-constructed early warning processing platform;

[0033] A receiving module, which is used to define a target ship when the Bluetooth receiver receives a real-time signal, send a data reading request to the target ship via the early warning processing platform, and use edge devices pre-deployed at the deployment location to receive multi-source data uploaded by the target ship, where the multi-source data at least includes: basic ship parameters, lidar monitoring data, AIS navigation data, ship control data, and video surveillance data. Based on the basic ship parameters, configure the risk level of the target ship, where the risk level at least includes: high, medium, and low;

[0034] A judgment module, which is used to judge whether the risk level of the target ship is low. If so, send a slow-down reminder to the target ship. If not, define the bridge at the deployment location as a risk target, connect the equipment terminal of the pilot to the early warning processing platform, and open the reading permission of the multi-source data of the risk target, and build a communication link between the equipment terminal and the target ship via the edge device.

[0035] Further, the uploading module includes:

[0036] A receiving unit, which is used to receive the accident notice uploaded by the pilot, establish a connection between the edge device and a preset warning device, and trigger the start of the warning device, where the warning device is deployed on the bridge road surface;

[0037] A configuration unit, which is used to configure the influencing factors of the bridge ship collision accident, where the influencing factors at least include: meteorological environment and waterway busyness;

[0038] A publicity unit, which is used to embed a publicity section in the early warning processing platform, generate pilot information using the corresponding relationship, and upload the pilot information to the publicity section;

[0039] A mapping unit, which is used to establish a mapping between the Bluetooth beacon signal and the basic ship parameters;

[0040] A sending unit, which is used to construct a signal query table, where the signal query table consists of signal items and parameter items, and parallelly send the signal query table to all edge devices.

[0041] Further, the configuration module includes:

[0042] An exit unit, which is used to embed a sleep mechanism in the Bluetooth receiver and exit the sleep mechanism when receiving the real-time signal;

[0043] A sending unit, which is used to traverse the signal query table using the real-time signal to obtain a target item, write the target item into a preset template to generate a prompt message, and send the prompt message to the terminal device

[0044] A correction unit, configured to correct the risk level by using the influencing factors;

[0045] A triggering unit, configured to construct a threshold set composed of a plurality of behavior thresholds, where each behavior threshold corresponds to at least one emergency response rule, and when the multi-source data exceeds the corresponding behavior threshold, trigger the corresponding emergency response rule to start.

[0046] Compared with the prior art, the beneficial effects of the present invention are:

[0047] By determining the risk points, early warning and avoidance of ships can be carried out, effectively improving the navigation safety. By deploying Bluetooth receivers, it is possible to monitor in real time whether a ship will pass through a risk point, increasing the early warning time. By determining the pilot, the position and status of the target ship can be mastered, reducing the human errors of the ship's crew and lowering the probability of accidents, further improving the navigation safety. By establishing a communication link, the pilot can provide pilotage guidance for the ship's crew, enhancing the risk assessment and prevention and control capabilities, and greatly improving the accuracy of accident early warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a flowchart of a bridge ship collision accident early warning method based on multi-source data fusion provided by an embodiment of the present invention;

[0049] Figure 2 It is a first sub-flowchart of a bridge ship collision accident early warning method based on multi-source data fusion provided by an embodiment of the present invention;

[0050] Figure 3 It is a second sub-flowchart of a bridge ship collision accident early warning method based on multi-source data fusion provided by an embodiment of the present invention;

[0051] Figure 4 It is a block diagram of the composition of a bridge ship collision accident early warning system based on multi-source data fusion provided by an embodiment of the present invention;

[0052] Figure 5 It is a block diagram of the composition of an upload module in a bridge ship collision accident early warning system based on multi-source data fusion provided by an embodiment of the present invention;

[0053] Figure 6 It is a block diagram of the composition of a configuration module in a bridge ship collision accident early warning system based on multi-source data fusion provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] In Embodiment 1, Figure 1 The implementation process of the bridge ship collision accident early warning method based on multi-source data fusion provided by the embodiments of the present invention is shown, and the details are as follows:

[0056] S100: Define the early warning area of the bridge ship collision accident, draw the shipping traffic map of the early warning area, mark all the bridges, select the risk points, determine the pilot personnel, configure the one-to-one correspondence between the risk points and the pilot personnel, define the deployment positions of the risk points as the positions of Bluetooth receivers, collect Bluetooth beacon signals, and upload them to the pre-constructed early warning processing platform.

[0057] Define the area that needs to be warned of bridge ship collision accidents, that is, the early warning area. Using geographic information systems and shipping simulation technologies, based on bridge structural characteristics, navigation heights, pier distributions, ship routes, and waterway distributions, etc., draw the shipping traffic map of the early warning area, and mark the positions of all bridges on the shipping traffic map. Combining accident statistics data and ship traffic density, etc., determine the positions of bridges with higher risks, that is, risk points. The risk points are: closer piers, sharp bend waterways, and areas with strong tides, etc.; According to the method of pilot personnel in places such as straits or ports, configure several pilot personnel for each or every few risk points. In other words, each risk point corresponds to at least one pilot personnel. The responsibilities of the pilot personnel include monitoring ship navigation data, analyzing abnormal ship behaviors, warning of potential risks, providing guidance to ship personnel, and taking over ship control when necessary; Deploy Bluetooth receivers at the risk points. The Bluetooth receivers can receive Bluetooth beacon signals on the ships and upload them to the pre-constructed early warning processing platform. The early warning processing platform can perform real-time analysis on the Bluetooth beacon signals and identify abnormal ship behaviors.

[0058] S200: When the Bluetooth receiver receives the real-time signal, define the target ship, send a data reading request to the target ship through the early warning processing platform, and use the edge devices pre-deployed at the deployment positions to receive the multi-source data uploaded by the target ship. The multi-source data at least includes: ship basic parameters, lidar monitoring data, AIS navigation data, ship control data, and video surveillance data. Based on the ship basic parameters, configure the risk level of the target ship. The risk level at least includes: high, medium, and low.

[0059] When the Bluetooth receiver receives the real-time signal, it analyzes the real-time signal and defines the ship corresponding to the source of the real-time signal as the target ship. The identity of the target ship can be identified by establishing the correspondence between the real-time signal and the target ship. The early warning processing platform sends a data reading request to the target ship, asking the target ship to upload multi-source data, including ship basic parameters, lidar monitoring data, AIS navigation data, ship control data, video surveillance data, etc. By analyzing the multi-source data, it can assist the pilot in risk assessment and decision-making. The ship basic parameters include: overall length, draft, displacement, and the number of passengers carried, etc. The installation positions of the video surveillance devices mainly include the cab, the ship's side, the front and rear decks, etc. The video surveillance data in the cab is mainly used to show the pilot the process of navigation adjustment, while the video surveillance data at the ship's side and the front and rear decks is mainly used to broaden the pilot's vision and provide a data basis for the pilot's guidance process.

[0060] Furthermore, the multi-source data is sent to the edge device through Bluetooth communication or other available wireless communication means (such as 5G network), where the edge device is installed at the deployment location. By setting up the edge device, it can ensure that the pilot can obtain key data in real time and take appropriate control measures in a timely manner, such as notifying the ship to adjust its course, reduce its speed, or sending an alarm to the relevant shipping management department to ensure the safety of the bridge and shipping. The edge device can be an edge server, a computing device, and an edge gateway. In addition, it should be noted that the edge device can be integrated with the Bluetooth receiver in the same device. The specific data transmission path is: from the target ship to the Bluetooth receiver and then to the edge device. At this time, according to actual needs, the multi-source data in the target ship can also be directly sent to the edge device.

[0061] According to the overall length and draft in the ship basic parameters, etc., determine the risk level of the ship passing through the risk point. Each ship has a different risk level corresponding to different risk points. The risk levels are divided into high, medium, and low. The higher the risk level, the more likely a ship collision accident will occur. In real life, if the ship is small and the speed is slow, the corresponding risk level will be lower.

[0062] S300: Judge whether the risk level of the target ship is low. If it is, send a slow-down reminder to the target ship. If not, define the bridge at the deployment location as the risk target, connect the equipment terminal of the pilot to the early warning processing platform, and open the reading permission of the multi-source data of the risk target. Through the edge device, establish a communication link between the equipment terminal and the risk target.

[0063] If the risk level of the target ship is low, it indicates that the probability of an accident is small. At this time, use the Bluetooth beacon signal to send a slow-down reminder to the target ship. If the risk level of the target ship is high, define the risk points that the target ship is about to pass through as risk targets, and grant the water pilot the permission to read the multi-source data of the target ship, and establish a communication link between the terminal device of the water pilot and the target ship. Using the communication link, the water pilot can view the real-time monitoring data in the cab of the target ship, and establish contact with the ship's crew through a megaphone, walkie-talkie, and early warning processing platform, etc., so as to provide a reference for the course adjustment of the target ship.

[0064] In real life, water pilots are generally familiar with the channel terrain at risk points. Water pilots in areas such as straits or ports can provide guidance for the course adjustment of passing ships.

[0065] In Embodiment 2, Figure 2 The implementation process of the bridge ship collision accident early warning method based on multi-source data fusion provided by the embodiment of the present invention is shown. The steps of demarcating the early warning area of the bridge ship collision accident, drawing the shipping traffic map of the early warning area, marking all the bridges, selecting risk points, and determining the water pilot are described in detail as follows:

[0066] S101: Receive the accident notice uploaded by the water pilot, establish a link between the edge device and the preset alarm device, and trigger the activation of the alarm device, where the alarm device is deployed on the bridge road surface;

[0067] After a bridge ship collision accident occurs, receive the accident notice uploaded by the water pilot through the terminal device, and establish a communication link between the edge device and the preset alarm device deployed on the bridge road surface. The edge device, as an intermediate processing node, is responsible for parsing accident data and determining the accident level, and is also responsible for sending a trigger instruction to the alarm device. The alarm device can be a warning light or a display screen, etc. The alarm device is installed on the bridge road surface, and uses the alarm device to emit sound and light warnings, which can timely remind the vehicles and pedestrians driving on the bridge to pay attention to avoidance.

[0068] S102: Configure the influencing factors of the bridge ship collision accident, where the influencing factors at least include: meteorological environment and channel busyness.

[0069] The influencing factors of bridge ship collision accidents mainly include environment, ship characteristics, and shipping management conditions, etc. The key influencing factors at least include meteorological environment and channel busyness. The meteorological environment factors cover wind speed and direction, rainfall, haze concentration, tidal changes, and water flow velocity, etc. The channel busyness refers to the density of ships on the channel.

[0070] S103: Embed a public notice section into the warning processing platform, generate water diversion information using the corresponding relationship, and upload the water diversion information to the public notice section.

[0071] Embed a public notice section into the warning processing platform, generate water diversion information using the location of each risk point, the identity information and communication methods of the corresponding water diversion personnel, etc., and display the water diversion information in the public notice section.

[0072] In Embodiment 3, Figure 2 The implementation process of the bridge ship collision accident warning method based on multi-source data fusion provided by the embodiment of the present invention is shown. The following details the steps of configuring the one-to-one correspondence between the risk points and the water diversion personnel, defining the deployment location of the risk points as the location of the Bluetooth receiver, collecting Bluetooth beacon signals, and uploading them to the pre-constructed warning processing platform, as follows:

[0073] S104: Establish a mapping between the Bluetooth beacon signal and the basic parameters of the ship.

[0074] Record the Bluetooth beacon signal and the basic parameters of each passing ship, and establish the relationship between the two.

[0075] S105: Construct a signal query table, where the signal query table consists of a signal item and a parameter item, and distribute the signal query table to all edge devices in parallel.

[0076] Use the Bluetooth beacon signal and the basic parameters of the ship to construct a signal query table, and distribute the signal query table to all edge devices, where each edge device stores the signal query table; by constructing the signal query table, data such as the total length, draft, and displacement of the ship can be quickly determined according to the Bluetooth beacon signal.

[0077] In Embodiment 4, Figure 3 The implementation process of the bridge ship collision accident warning method based on multi-source data fusion provided by the embodiment of the present invention is shown. The following details the steps of, when the Bluetooth receiver receives a real-time signal, defining the target ship and sending a data reading request to the target ship via the warning processing platform, as follows:

[0078] S201: Embed a sleep mechanism into the Bluetooth receiver, and exit the sleep mechanism when the real-time signal is received.

[0079] Embed a sleep mechanism into the Bluetooth receiver deployed at the risk point. The sleep mechanism is as follows: when no Bluetooth beacon signal is detected, the Bluetooth receiver enters the low-power mode and only maintains the basic heartbeat detection function to reduce energy consumption and data processing burden; when the Bluetooth receiver captures the real-time Bluetooth beacon signal sent by the ship, it exits the sleep mode, resumes the normal working state, and starts the data collection and parsing process.

[0080] S202: Use the real-time signal to traverse the signal query table to obtain the target item, write the target item into the preset template to generate a prompt message, and send the prompt message to the terminal device.

[0081] After collecting the real-time signal of the target ship, traverse the signal query table, define the basic ship parameters corresponding to the target ship as the target item, write the target item into the preset template to generate a prompt message, and send the prompt message to the terminal device. The preset template is pre-formulated by the management personnel or the pilot of the early warning processing platform; the prompt message can be: "Ship name: Freight 001, Type: Cargo ship, Speed: 12 knots, Course: 270° (westward)".

[0082] In Embodiment 5, Figure 3 The implementation process of the bridge ship collision accident early warning method based on multi-source data fusion provided by the embodiment of the present invention is shown. The following details the steps of configuring the risk level of the target ship based on the basic ship parameters as follows:

[0083] S203: Modify the risk level based on the influencing factors.

[0084] Adjust the risk level according to influencing factors such as weather and wind speed.

[0085] S204: Construct a threshold set composed of several behavior thresholds, where each behavior threshold corresponds to at least one emergency response rule. When the multi-source data exceeds the corresponding behavior threshold, the corresponding emergency response rule is triggered and started.

[0086] When the multi-source data exceeds the behavior threshold, start the corresponding response rule; for example, the behavior threshold is: speed 15 knots. When the speed of the target ship is 18 knots, start the corresponding emergency response rule, where the emergency response rule can be: send a "forced deceleration" instruction to the target ship and notify the pilot to assist in control.

[0087] In Embodiment 6, different from Embodiment 1, in the embodiment of the present invention, the method further includes:

[0088] Obtain the predetermined route of the target ship and configure the traveling direction;

[0089] Determine the arrival time of each risk point in the said traveling direction, generate a route schedule, and construct a notification rule.

[0090] Utilize the early warning processing platform to receive the pre - determined route uploaded by the target ship, determine the starting point, ending point, navigation path, key channel nodes, etc. of the target ship, and calculate the arrival time of the target ship passing through each risk point according to the traveling direction of the target ship, and generate a route schedule. The route schedule includes the name or number of the risk points passed through and the corresponding arrival time. When the target ship arrives at a risk point, start the notification rule, where the notification rule is: send a prompt message to the pilot corresponding to the risk point, and the prompt message should include the route schedule.

[0091] In Embodiment 7, different from Embodiment 1, in the embodiment of the present invention, the method further includes:

[0092] In the said pre - determined route, select accident black spots, collect the environmental data at the accident black spots, and add the accident black spots to the deployment locations;

[0093] Define the Bluetooth receiver at the accident black spot as an additional device, and send the environmental data to the additional device.

[0094] In the pre - determined route, according to information such as historical accident data, AIS trajectory analysis, and shipping flow statistics, select accident - prone areas (i.e., accident black spots), add the accident black spots to the deployment locations, and deploy Bluetooth receivers and edge devices at the accident black spots to collect the environmental data at the accident black spots. The environmental data is the water flow velocity, flow direction, and tidal level change. Utilize the environmental data to generate a risk reminder and send the risk reminder to the additional device. The additional device is either the Bluetooth receiver or the edge device at the accident black spot. The risk reminder is: "The water flow ahead is rapid, please operate with caution" or "High accident - prone area, please reduce the ship speed to within 10 knots".

[0095] Figure 4 Shows the composition structure block diagram of the bridge - ship collision accident early warning system based on multi - source data fusion provided by the embodiment of the present invention. The bridge - ship collision accident early warning system 1 based on multi - source data fusion includes:

[0096] An upload module 11, used to delimit the early warning area of the bridge - ship collision accident, draw the shipping traffic map of the early warning area, mark all the bridges, select risk points, determine management personnel, configure the one - to - one correspondence between the risk points and the management personnel, define the deployment locations of the risk points as Bluetooth receivers, collect Bluetooth beacon signals, and upload them to the pre - constructed early warning processing platform;

[0097] A receiving module 12, which is used to define a target ship when the Bluetooth receiver receives a real-time signal, send a data reading request to the target ship via the early warning processing platform, and use edge devices pre-deployed at the deployment location to receive multi-source data uploaded by the target ship, where the multi-source data at least includes: basic ship parameters, lidar monitoring data, AIS navigation data, ship control data, and video surveillance data, and configure a risk level for the target ship based on the basic ship parameters, where the risk level at least includes: high, medium, and low;

[0098] A judging module 13, which is used to judge whether the risk level of the target ship is low. If so, send a slow-down reminder to the target ship. If not, define the bridge at the deployment location as a risk target, connect the device terminal of the management personnel to the early warning processing platform, and open the reading permission of the multi-source data of the risk target, and establish a communication link between the device terminal and the risk target via the edge device.

[0099] Figure 5 The composition structure block diagram of the bridge ship collision accident early warning system provided by the embodiment of the present invention is shown. The uploading module 11 includes:

[0100] A receiving unit 111, which is used to receive the accident notice uploaded by the pilot, establish a connection between the edge device and the preset warning device, and trigger the activation of the warning device, where the warning device is deployed on the bridge road surface;

[0101] A configuration unit 112, which is used to configure the influencing factors of the bridge ship collision accident, where the influencing factors at least include: meteorological environment and waterway busyness;

[0102] A publicity unit 113, which is used to embed a publicity section in the early warning processing platform, generate pilot information using the corresponding relationship, and upload the pilot information to the publicity section;

[0103] A mapping unit 114, which is used to establish a mapping between the Bluetooth beacon signal and the basic ship parameters;

[0104] A sending-down unit 115, which is used to construct a signal query table, where the signal query table consists of signal items and parameter items, and send the signal query table to all edge devices in parallel.

[0105] Figure 6 The composition structure block diagram of the bridge ship collision accident early warning system provided by the embodiment of the present invention is shown. The configuration module 12 includes:

[0106] An exit unit 121 is used to embed a sleep mechanism into the Bluetooth receiver and exit the sleep mechanism when the real-time signal is received;

[0107] A sending unit 122 is used to utilize the real-time signal to traverse the signal query table to obtain a target item, write the target item into a preset template to generate a prompt message, and send the prompt message to the terminal device

[0108] A correction unit 123 is used to correct the risk level by using the influencing factor;

[0109] A triggering unit 124 is used to construct a threshold set composed of several behavior thresholds, where each behavior threshold corresponds to at least one emergency response rule, and when the multi-source data exceeds the corresponding behavior threshold, the corresponding emergency response rule is triggered to start.

[0110] Among them, the upload module 11 is mainly used to complete step S100, the receiving module 12 is mainly used to complete step S200, and the judgment module 13 is mainly used to complete step S300;

[0111] The receiving unit 111 is mainly used to complete step S101, the configuration unit 112 is mainly used to complete step S102, the publicity unit 113 is mainly used to complete step S103, the mapping unit 114 is mainly used to complete step S104, and the sending unit 115 is mainly used to complete step S105;

[0112] The exit unit 121 is mainly used to complete step S201, the sending unit 122 is mainly used to complete step S202, the correction unit 123 is mainly used to complete step S203, and the triggering unit 124 is mainly used to complete step S204.

[0113] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as these combinations of technical features do not conflict, they should be considered as the scope described in this specification.

[0114] The above-described embodiments only represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

[0115] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A bridge-ship collision accident early warning method based on multi-source data fusion, characterized in that: The method comprises: Delineate the warning area for bridge-ship collision accidents, draw a shipping traffic map of the warning area, mark all bridges, select risk points, determine pilots, configure a one-to-one correspondence between the risk points and the pilots, define the risk points as the deployment locations of Bluetooth receivers, collect Bluetooth beacon signals, and upload them to the pre-built warning processing platform; When the Bluetooth receiver receives the real-time signal, a target ship is defined, and a data reading request is sent to the target ship via the early warning processing platform, and the multi-source data uploaded by the target ship is received by using the edge device pre-deployed at the deployment location, wherein the multi-source data at least includes: basic ship parameters, laser radar monitoring data, AIS navigation data, ship control data and video monitoring data, and the risk level of the target ship is configured based on the basic ship parameters, wherein the risk level at least includes: high, medium and low; Determine whether the risk level of the target ship is low, and if so, send a slow-down reminder to the target ship; If not, the bridge at the deployment location is defined as a risk target, the equipment terminal of the water pilot is connected to the early warning processing platform, and the reading permission of the multi-source data of the risk target is opened, and a communication link between the equipment terminal and the risk target is established through the edge device.

2. The bridge-ship collision accident early warning method based on multi-source data fusion according to claim 1 is characterized in that: The steps of delineating the warning area for bridge-ship collision accidents, drawing a shipping traffic map of the warning area, marking all bridges, selecting risk points, and determining pilots include: Receive the accident notification uploaded by the pilot, establish a link between the edge device and the preset alarm device, and trigger the alarm device to start, wherein the alarm device is deployed on the bridge pavement; The influencing factors of bridge-ship collision accidents are configured, wherein the influencing factors at least include: meteorological environment and waterway busyness; A public announcement section is embedded in the early warning processing platform, water diversion information is generated by utilizing the corresponding relationship, and the water diversion information is uploaded to the public announcement section.

3. The bridge-ship collision accident early warning method based on multi-source data fusion according to claim 1 is characterized in that: The steps of configuring a one-to-one correspondence between the risk point and the pilot, defining the risk point as a deployment location of a Bluetooth receiver, collecting Bluetooth beacon signals, and uploading them to a pre-built early warning processing platform include: Establishing a mapping between the Bluetooth beacon signal and basic ship parameters; A signal query table is constructed, wherein the signal query table consists of signal items and parameter items, and the signal query table is sent to all edge devices in parallel.

4. The bridge-ship collision accident early warning method based on multi-source data fusion according to claim 1 is characterized in that: The method further comprises: Obtain the scheduled route of the target ship and configure the travel direction; Determine the arrival time of each risk point in the direction of travel, generate a route schedule, and construct notification rules.

5. The bridge-ship collision accident warning method based on multi-source data fusion according to claim 3 is characterized in that: The step of defining a target ship after the Bluetooth receiver receives the real-time signal and sending a data reading request to the target ship via the early warning processing platform includes: Embed a sleep mechanism in the Bluetooth receiver, and exit the sleep mechanism after receiving the real-time signal; The real-time signal is used to traverse the signal query table to obtain a target item, the target item is written into a preset template, prompt information is generated, and the prompt information is sent to a terminal device.

6. The bridge-ship collision accident early warning method based on multi-source data fusion according to claim 2 is characterized in that: The step of configuring the risk level of the target ship based on the basic parameters of the ship comprises: Based on the influencing factors, modify the risk level; A threshold set consisting of several behavior thresholds is constructed, wherein each behavior threshold corresponds to at least one emergency handling rule, and when the multi-source data exceeds the corresponding behavior threshold, the corresponding emergency handling rule is triggered and started.

7. The bridge-ship collision accident early warning method based on multi-source data fusion according to claim 4 is characterized in that: The method further comprises: In the predetermined route, an accident black spot is selected, environmental data at the accident black spot is collected, and the accident black spot is added to the deployment position; The Bluetooth receiver at the accident black spot is defined as an additional device, and the environmental data is sent to the additional device.

8. A bridge-ship collision accident warning system based on multi-source data fusion, characterized in that: The system comprises: The upload module is used to delineate the warning area for bridge-ship collision accidents, draw a shipping traffic map of the warning area, mark all bridges, select risk points, determine pilots, configure a one-to-one correspondence between the risk points and the pilots, define the risk points as the deployment locations of Bluetooth receivers, collect Bluetooth beacon signals, and upload them to the pre-built warning processing platform; A receiving module, configured to define a target ship after the Bluetooth receiver receives a real-time signal, send a data reading request to the target ship via the early warning processing platform, and receive multi-source data uploaded by the target ship using an edge device pre-deployed at the deployment location, wherein the multi-source data at least includes: basic ship parameters, laser radar monitoring data, AIS navigation data, ship control data and video monitoring data, and configure a risk level of the target ship based on the basic ship parameters, wherein the risk level at least includes: high, medium and low; The judgment module is used to judge whether the risk level of the target ship is low. If so, a slow-down reminder is sent to the target ship. If not, the bridge at the deployment location is defined as a risk target, the equipment terminal of the pilot is connected to the early warning processing platform, and the reading permission of the multi-source data of the risk target is opened, and a communication link between the equipment terminal and the target ship is established via the edge device.

9. The bridge-ship collision accident warning system based on multi-source data fusion according to claim 8 is characterized in that: The upload module includes: A receiving unit, used to receive the accident notification uploaded by the pilot, establish a link between the edge device and the preset alarm device, and trigger the alarm device to start, wherein the alarm device is deployed on the bridge pavement; A configuration unit, used to configure influencing factors of bridge-ship collision accidents, wherein the influencing factors at least include: meteorological environment and waterway busyness; A publicizing unit, used for embedding a publicizing section into the early warning processing platform, generating water diversion information by using the corresponding relationship, and uploading the water diversion information to the publicizing section; A mapping unit, used to establish a mapping between the Bluetooth beacon signal and basic ship parameters; The sending unit is used to construct a signal query table, wherein the signal query table consists of signal items and parameter items, and the signal query table is sent to all edge devices in parallel.

10. The bridge-ship collision accident warning system based on multi-source data fusion according to claim 9 is characterized in that: The configuration module includes: An exit unit, used for embedding a sleep mechanism into the Bluetooth receiver, and exiting the sleep mechanism after receiving the real-time signal; A sending unit is used to use the real-time signal to traverse the signal query table, obtain the target item, write the target item into a preset template, generate prompt information, and send the prompt information to the terminal device A correction unit, used to correct the risk level by using the influencing factors; The trigger unit is used to construct a threshold set consisting of several behavior thresholds, wherein each behavior threshold corresponds to at least one emergency handling rule, and when the multi-source data exceeds the corresponding behavior threshold, the corresponding emergency handling rule is triggered and started.

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