JP7318084B1 - Control device and control program - Google Patents

Abstract

An object of the present invention is to efficiently perform marine tasks. According to one embodiment, a commanding device includes an information acquisition unit, a group creation unit, and a process execution unit. The information acquisition unit acquires information of nodes having resources for performing preset ocean-related tasks. The group creation unit creates a group including a plurality of nodes capable of communicating data with each other according to the node information and the task acquired by the information acquisition unit. The processing execution unit causes the plurality of nodes to perform data communication with each other and to provide the resources to the plurality of nodes, thereby executing processing according to the task. [Selection drawing] Fig. 9

Description

The present disclosure relates to a supervisory device and a supervisory program.

Computers possessed by multiple entities may be used in the execution of ocean-related tasks.

Tasks related to the ocean include maritime accident response, ship route search, and ship maintenance. In addition, the plurality of entities includes not only ships but also ship owners, shipbuilding companies, ship engine manufacturers, shippers, government offices, insurance companies, and the like.

Conventionally, in distributed computing in which a plurality of computers perform tasks, a technique for automatically identifying a computer that performs tasks is known (see, for example, Patent Document 1).

Also, there is known a technique of organizing a plurality of vehicles having a communication function into a group capable of communicating with each other (see, for example, Patent Document 2).

Japanese Patent Application Publication No. 2016-504696 JP 2022-116616 A

However, conventional techniques suffer from the problem that they may not be able to efficiently perform maritime tasks.

For example, the techniques described in Patent Documents 1 and 2 do not perform maritime tasks.

One aspect of the present invention aims to provide a technology that can efficiently perform marine tasks.

In one aspect, the supervising device includes an information acquisition unit that acquires information on a node having a resource for performing a preset ocean-related task, and information on the node and the task acquired by the information acquisition unit a group creating unit for creating a group including a plurality of nodes capable of communicating data with each other according to the above, and causing the plurality of nodes to perform data communication with each other and to provide the resources to the plurality of nodes. and a process execution unit that executes a process corresponding to the task.

According to one aspect of the embodiments, marine tasks can be efficiently accomplished.

FIG. 1 is a diagram illustrating a configuration example of a network system according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of a node according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of a dominating node according to the embodiment; FIG. 4 is a diagram illustrating a configuration example of an operation management function according to the embodiment; FIG. 5 is a diagram showing an example of task information. FIG. 6 is a diagram showing an example of node information. FIG. 7 is a diagram for explaining the multiplexing structure. FIG. 8 is a diagram explaining a monitoring node. FIG. 9 is a diagram for explaining processing of the network system. FIG. 10 is a flowchart illustrating the flow of processing by a dominating node according to the embodiment. FIG. 11 is a flow chart showing the flow of processing for creating a group according to the embodiment. FIG. 12 is a diagram illustrating a configuration example of a network system. FIG. 13 is a diagram illustrating a configuration example of a network system. FIG. 14 is a diagram illustrating a configuration example of a network system. FIG. 15 is a diagram illustrating a configuration example of a network system. FIG. 16 is a diagram illustrating a configuration example of a network system. FIG. 17 is a diagram illustrating a hardware configuration example of a controlling device according to the embodiment;

Embodiments (hereinafter referred to as "embodiments") for carrying out the supervising device and supervising program according to the present disclosure will be described in detail below with reference to the drawings. Note that the present disclosure is not limited by this embodiment.

One of the purposes of this embodiment is to efficiently perform marine tasks. Therefore, in the present embodiment, a network (hereinafter referred to as a network system) is constructed with computers as nodes.

[Configuration of Embodiment]
A network system will be described with reference to FIG. FIG. 1 is a diagram illustrating a configuration example of a network system according to an embodiment.

As shown in FIG. 1, the network system 1 has a dominating node 20 and a plurality of nodes (node 10a, node 10b, node 10c, and node 10d). The dominating node 20 is an example of a dominating device.

Here, a node that is not a controlling node is called a general node. Also, in the following description, simply referring to a node means both a dominating node and a general node.

A node is a computer. A node is owned by an organization, such as a company, or an individual. The node is, for example, a server installed on the cloud or in a local environment, a desktop or laptop PC, a mobile terminal such as a smartphone, a computer installed in a mobile object such as a ship, or the like. Also, the node may be an ECU (Engine Control Unit) provided on the ship.

Each node included in the network system 1 can communicate data with each other. For example, each node of the network system 1 may perform data communication via the Internet, or may perform data communication directly between nodes. For example, the nodes communicate via mobile networks (eg Long Term Evolution (LTE), 5G), local wireless communications (eg Wi-Fi), or satellite communications for ships.

The fact that the nodes included in the network system 1 can communicate data with each other is not only that the nodes are connected by a so-called physical layer, but also that the nodes are connected in a layer higher than the physical layer (data link layer or higher). It means that it can be established.

For example, a node included in the network system 1 stores the address of a node to be communicated with, a password necessary for data transmission and reception, and the like, and establishes communication using the stored information.

Note that not all nodes included in network system 1 need to be connected to each other. For example, a node may be indirectly connected to a node with which it communicates via another node.

The dominating node 20 is a node for dominating general nodes. The dominating node 20 selects specific nodes from the candidate node group and clusters (groups) the selected nodes. The dominating node 20 and clustered general nodes constitute the network system 1 .

Each node included in the candidate node group can function as a general node, or can function as a dominating node.

In the example of FIG. 1, the candidate node group includes node 10a, node 10b, node 10c, node 10d, node 10e, and node 10f.

Then, the dominating node 20 performs clustering and includes the nodes 10a, 10b, 10c, and 10d in the cluster (network system 1). On the other hand, the dominating node 20 does not include the node 10e and the node 10f in the cluster (network system 1).

Here, the network system 1 is a system for accomplishing marine tasks. The dominating node 20 selects a node to be included in the network system 1 according to the content of the task, the resource possessed by the node, and the like.

The configuration of the node will be described with reference to FIGS. 2 and 3. FIG. FIG. 2 is a diagram illustrating a configuration example of a node according to the embodiment; FIG. 3 is a diagram illustrating a configuration example of a dominating node according to the embodiment;

The nodes 10 shown in FIG. 2 correspond to general nodes, namely the nodes 10a, 10b, 10c, 10d, 10e and 10f in FIG. However, the general node may have a configuration equivalent to that of the dominating node 20 .

As shown in FIG. 2, the node 10 has a functional section 11 and a resource section 12 . The functional unit 11 implements each function of the node 10 . The resource unit 12 is a computer resource (computer resource) that can be used when the network system 1 performs a task.

For example, the functional unit 11 and the resource unit 12 are computers or It is realized by various circuits.

The functional unit 11 has a resource management function 111 , a communication function 112 , a billing function 113 and a monitoring function 114 . Each function of the functional unit 11 is implemented by the CPU executing a program.

The resource management function 111 manages resources included in the resource unit 12 . For example, the resource management function 111 provides resources and limits the content and amount of resources to be provided.

Here, the resource unit 22 includes hardware resources 121 , software resources 122 and DB resources 123 .

Hardware resource 121 corresponds to computing power by a processor (eg, CPU or GPU). For example, when the resource management function 111 provides the hardware resource 121, the network system 1 can realize distributed computing. At this time, the node 10 may function as one thread of the processor.

For example, the resource management function 111 receives calculation formulas and data necessary for calculation of the calculation formulas from other nodes. Then, the resource management function 111 uses the hardware resource 121 to perform calculation according to the calculation formula, and returns the calculation result to another node.

Software resource 122 is a pre-written program. Programs provided as software resources 122 may be different for each node. Note that the software resource 132 may be a program of a predetermined unit called a module, procedure, function, or the like.

The resource management function 111 may provide the program, which is the software resource 122, to another node, or may execute the program using both the hardware resource 121 and the software resource 122 and provide the execution result. .

For example, consider a case where the software resource 122 includes an optimum route search program that calculates the optimum route from the current location to the destination by simulation.

At this time, the node 10 is provided with the ship's current location, destination, route candidates between the current location and the destination, and other data necessary for executing the optimum route search program. The resource management function 111 uses the hardware resource 121 to execute the optimum route search program based on the given data, and returns the route obtained as a result to other nodes.

The software resource 122 may also include a trained machine learning model (AI model). For example, consider the case where software resource 122 includes an image recognition model for recognizing objects in images.

At this time, the node 10 is given an image. The resource management function 111 uses the hardware resource 121 to input the given image to the image recognition model and return the recognition result to other nodes.

The DB resource 123 is information stored as data. Data stored as the DB resource 123 may be different for each node.

For example, the DB resource 123 stores data as a table with keys and values. In that case, the resource management function 111 returns the value obtained by searching the table based on the key specified by the other node to the other node.

The communication function 112 communicates with other nodes. For example, the communication function 112 includes a communication interface such as a NIC (Network Interface Controller) and a program for controlling the communication interface.

The charging function 113 is a function for charging a fee for provision of resources. For example, the billing function 113 calculates charges according to the content and amount of resources provided to other nodes by the resource management function 111 . For example, the billing function 113 calculates the charge by multiplying the unit price of each resource by the time or number of times provided.

Also, the billing function 113 can create bill format data for billing charges and transmit the data to a predetermined destination.

The monitor function 114 negotiates with other nodes. The monitoring function 114 requests other nodes to provide resources. In addition, the monitoring function 114 determines whether or not to accept a resource provision request received from another node.

The monitoring function 114 can negotiate on a rule basis according to the resources of each node.

Also, the monitoring function 114 may be realized by a machine learning model (AI model) instead of a rule base. For example, the monitoring function 114 inputs conditions presented by other nodes into the AI model. The machine learning model then outputs information indicating whether or not the resource may be provided based on the condition. The conditions include the content, amount, time, period, fee, etc. of the resource to be provided. In addition, the machine learning model is appropriately updated (trained) by adding the input data (conditions) and the evaluation of the results when it is determined whether or not to provide resources according to the output as teacher data. Note that the results may be evaluated according to the success or failure of the task and the degree of success (for example, profit if the task is related to business).

Next, the configuration of the dominating node 20 will be described with reference to FIG. As shown in FIG. 3 , the dominating node 20 has a functional unit 21 and a resource unit 22 .

The dominating node 20 has an operation management function 215 in addition to the same configuration as the node 10 . The resource management function 211, communication function 212, charging function 213 and monitoring function 214 of the dominating node 20 are equivalent to the resource management function 111, communication function 112, charging function 113 and monitoring function 114 of the node 10, respectively.

Also, the resource unit 22 (hardware resource 221 , software resource 222 and DB resource 223 ) of the dominating node 20 has the same function as the resource unit 22 of the node 10 .

The operation management function 215 will be described with reference to FIG. FIG. 4 is a diagram illustrating a configuration example of an operation management function according to the embodiment;

As shown in FIG. 4 , the operation management function 215 has an information acquisition section 2151 , a group creation section 2152 and a process execution section 2153 . The operation management function 215 also stores node information 2154 and task information 2155 .

The information acquisition unit 2151 acquires information on nodes having resources for performing preset ocean-related tasks. The information acquisition unit 2151 acquires node information from the node information 2154 . Also, the information acquisition unit 2151 acquires task information from the task information 2155 .

FIG. 5 is a diagram showing an example of task information. As shown in FIG. 5, task information 2155 is information that associates tasks with software resources, DB resources, and hardware resources.

In the example of FIG. 5, the task "cargo transportation" includes software resources "optimal route search", DB resources "vessel data", "operation plan data", "weather forecast data", and hardware resources. "CPU" and "GPU" are associated.

FIG. 6 is a diagram showing an example of node information. As shown in FIG. 6, the node information 2154 is information in which nodes are associated with software resources, DB resources, and hardware resources of each node.

In the example of FIG. 6, the node "system 30a" is associated with the software resource "optimal route search", the DB resource "vessel data", and the hardware resource "GPU".

The group creating unit 2152 creates a group including a plurality of nodes capable of communicating data with each other according to the node information and tasks acquired by the information acquiring unit 2151 .

For example, consider the case where the task to be accomplished is "cargo transportation". In the task information 2155, in order to carry out the task "freight transport", software resources "optimal route search", DB resources "vessel data", "operation plan data", "weather forecast data", It indicates that the hardware resources "CPU" and "GPU" are required.

Therefore, the group creating unit 2152 selects the "system 30a" having the software resource "optimal route search", the DB resource "ship data", and the hardware resource "GPU". In addition, the group creating unit 2152 selects the "system 30b" having the software resource "optimal route search", the DB resource "weather forecast data", and the hardware resource "CPU". In addition, the group creating unit 2152 selects the "system 30c" having the software resource "optimal route search", the DB resource "flight plan data", and the hardware resource "GPU". On the other hand, since "system 30d" does not have the resources necessary for the task "cargo transportation", the group creating unit 2152 does not select "system 30d".

The group creation unit 2152 groups the selected "system 30a", "system 30b", and "system 30c". As a result, a network system having "system 30a", "system 30b", and "system 30c" as nodes is constructed.

Furthermore, the group creation unit 2152 sets communication paths between nodes. For example, the group creating unit 2152 notifies the nodes included in the group of information necessary for communication, such as the address of each node, and stores the information.

In addition, the group creating unit 2152 uses a machine learning model (AI model) that outputs a communication path for data communication based on information about the nodes, and uses a machine learning model (AI model) for data communication between a plurality of nodes. A communication path may be determined. Thus, if a machine learning model can be prepared in advance, it becomes possible to automatically determine and recommend a communication route. Also, the machine learning model may be updated (trained) as appropriate based on the evaluation of the determined communication path (eg, communication speed, stability measurements).

Also, the group creating unit 2152 may connect each node to a plurality of nodes to construct a mesh network.

Note that the group creation unit 2152 may create groups using a machine learning model (AI model) that outputs a combination of nodes for executing processing based on information about nodes. Thus, if a machine learning model can be prepared in advance, groups can be created efficiently. Also, the machine learning model may be updated (trained) as appropriate based on the evaluation of the created group (for example, success or failure of the final task).

The processing execution unit 2153 causes the nodes grouped by the group creation unit 2152 to communicate data with each other and provide resources to the nodes, thereby executing processing according to the task.

In addition, the processing execution unit 2153 distributes the nodes that provide resources according to the resource usage status of each of the plurality of nodes.

For example, "system 30a" and "system 30b" both have the software resource "best route search". For this reason, the process execution unit 2153 causes both the "system 30a" and the "system 30b" to execute the process using the software resource "optimal route search" instead of only the "system 30a". This can prevent the load from concentrating on one node.

Further, the process execution unit 2153 may store the same data in each of a plurality of nodes and cause the plurality of nodes (network system) to function as a blockchain.
This makes it possible to ensure the transparency and reliability of information.

In addition, the processing execution unit 2153 calculates charges charged for resources provided by each of the plurality of nodes in order to execute the processing. In this case, the processing execution unit 2153 charges or collects the fee based on the fee calculated by the charging function 113 of each node.

If there is a customer who requested the execution of the task, the billing and collection of the fee will be made to the customer. The processing execution unit 2153 may transmit bill format data to the client, or may automatically withdraw charges in cooperation with the financial system.

Here, as shown in FIG. 7, the network system may be multiplexed. FIG. 7 is a diagram for explaining the multiplexing structure. Nodes marked with "N" are general nodes. Nodes marked with "L" are dominating nodes.

In the example of FIG. 7, a network system is further constructed with the network system supervised by the dominating node serving as nodes. In this way, dominating nodes and network systems may be multi-layered. Also, each node may belong to a plurality of network systems redundantly.

A set of multiple nodes with the same value can be regarded as a network system. In this case, any node included in the set can act as the dominating node.

For example, multiple nodes with the same value are nodes owned by the same entity (company or individual). Also, for example, multiple nodes having the same value are nodes owned by an entity (company or individual) who is a stakeholder for one task.

As in the example of FIG. 7, a network system may be constructed in which a set of multiple nodes having the same value are set as nodes.

Also, as shown in FIG. 8, some of the dominating nodes and general nodes can act as monitoring nodes. FIG. 8 is a diagram explaining a monitoring node. Nodes marked with "R" are monitoring nodes.

The monitor node performs inter-node negotiation by the monitor function 114 described above. Also, the monitoring node recommends the communication route determined by the group creating unit 2152 to each node.

FIG. 9 shows the flow of processing described so far. FIG. 9 is a diagram for explaining processing of the network system.

As shown in FIG. 9, it is assumed that there are a system 30a, a system 30b, a system 30c, and a system 30d as node candidates. Node candidate systems are computers such as servers, terminals, and ECUs.

In addition, the terminal 50 is operated by the user U. The user U requests the dominating node 20 to perform the task via the terminal 50 and receives the result of the task performed from the dominating node 20 .

The dominating node 20 first acquires node information (step S1). At this time, the dominating node 20 refers to the node information 2154 and the task information 2155 to acquire information.

The dominating node 20 adopts (selects) the system 30a and the system 30b by the operation management function 215 (step S2). On the other hand, the dominating node 20 does not adopt the system 30d (step S3). As described above, the operation management function 215 selects nodes having resources necessary for processing based on the node information 2154 and task information 2155 .

Here, it is assumed that the system 30c is selected through negotiation (internode negotiation) by the monitoring function 114 of the system 30b (step S4).

Here, the dominating node 20 creates a group including the adopted node (step S5). Then, the dominating node 20 executes processing according to the task by the created group (step S6).

[Processing Flow of Embodiment]
The processing flow of the dominating node 20 will be described with reference to FIG. FIG. 10 is a flowchart illustrating the flow of processing by a dominating node according to the embodiment.

As shown in FIG. 10, the dominating node 20 first receives a task input (step S11). For example, task input is performed via the terminal 50 .

Next, the dominating node 20 acquires task and node information (step S12). Then, the dominating node 20 creates a node group based on the acquired information (step S13).

Subsequently, the dominating node 20 determines a communication route between nodes included in the group (step S14). Then, the dominating node 20 executes processing using the resources of the nodes included in the group (step S15).

The process of creating a group (step S13 in FIG. 10) will be described with reference to FIG. FIG. 11 is a flow chart showing the flow of processing for creating a group according to the embodiment.

As shown in FIG. 11, the dominating node 20 sets 1 to i representing a number identifying a candidate node (step S131).

Next, the dominating node 20 determines whether or not the i-th node matches the task (step S132). If the i-th node has the resources necessary for the task, the dominating node 20 determines that the node is suitable for the task. On the other hand, if the i-th node does not have the resources necessary for the task, the dominating node 20 determines that the node is not suitable for the task.

If the i-th node matches the task (step S132, Yes), the dominating node 20 adopts the i-th node (step S133) and proceeds to step S134. On the other hand, if the i-th node does not match the task (step S132, No), the dominating node 20 proceeds to step S134 without adopting the i-th node.

The dominating node 20 determines whether or not the adopted node can execute the task (step S134). For example, when the content and amount of resources required for a task are completely supplemented by the content and amount of resources possessed by the adopted node, the dominating node 20 determines whether the adopted node can execute the task.

If the dominating node 20 determines that the adopted node can execute the task (step S134, Yes), it adds the adopted node to the group (step S136) and ends the process.

On the other hand, if the dominating node 20 determines that the adopted node cannot execute the task (step S134, No), it increases i by 1 (step S135) and returns to step S132.

[Effects of Embodiment]
As explained so far, the information acquisition unit 2151 acquires information on nodes having resources for performing preset ocean-related tasks. The group creating unit 2152 creates a group including a plurality of nodes capable of communicating data with each other according to the node information and tasks acquired by the information acquiring unit 2151 . The processing execution unit 2153 causes the plurality of nodes to perform data communication with each other and to provide the resources to the plurality of nodes, thereby executing processing according to the task.

Thus, in this embodiment, groups of nodes having resources can be created according to tasks. For this reason, according to the present embodiment, even marine tasks such as responding to marine accidents, maintaining ships, and transporting cargo can be performed efficiently by creating groups according to the tasks.

An example in which the above-described embodiment is adapted to a specific case will be described. For example, the network system in the embodiment executes processing for supporting navigation of ships. Also, for example, the network system in the embodiment executes processing related to port facilities where ships call.

[Example 1: Tsunami alert service]
An example in which the task is "Tsunami Alert Service" will be described with reference to FIG. FIG. 12 is a diagram illustrating a configuration example of a network system.

The task "Tsunami Alert Service" is to notify research institutes of information on the tsunami when the occurrence of a tsunami is detected by a ship.

As shown in FIG. 12, the ship 62 has a recording device 62a and a ship ECU 62b. In Example 1, the ship ECU 62b functions as a control node.

The ship ECU 62b creates a network system 1A having the cloud server 61, the other ship 62, and the research institute server 64 as nodes when the ship 62 detects a tsunami while sailing on a route in the Pacific Ocean.

Then, the vessel ECU 62b uses the resources of the network system 1A to start processing for executing the task "tsunami alert service".

First, the vessel ECU 62b inquires data from the cloud server 61 according to the position of the vessel 62, and obtains information on countries facing the Pacific Ocean (countries affected by tsunami). Based on the information obtained from the research institution server 64 capable of analyzing the tsunami, the ship ECU 62b selects the country, research institution, etc. that will transmit the information on the tsunami. The ship ECU 62b may query the cloud server 61 for data after collecting information from a plurality of ships.

Note that there are a plurality of ships 62 . The ship ECU mounted on each ship 62 creates a group including servers of research institutes in countries facing the route of the ship 62 . This creates a group in which groups are further multiplexed.

The ship ECU 62b causes the cloud server 61 to transmit the data necessary for using the online support video conference system, detailed data collection service, etc. to the selected country and research institute, and further to other ships.

The vessel ECU 62b can only perform simple processing such as threshold determination of sensor values using only its own resources. On the other hand, the vessel ECU 62b can extend its functions by using the resources of the cloud server 61 and perform analysis using machine learning models.

By executing the task "Tsunami Alert Service" by the ship ECU 62b, the government and research institutes can obtain detailed tsunami data, and can take countermeasures such as simulating damage and transmitting tsunami alerts to target areas. .

In addition, the ship ECU 62b can select the optimum communication line from a plurality of communication lines including the ship-to-land communication line according to the position of the ship 62 and use it as a communication path.

The ship ECU 62b may provide not only the resources of the cloud server 61 but also the resources of the ship ECU 62b itself. Further, the ship ECU 62b may provide only the resources that the ship ECU 62b itself has, without providing the resources of the cloud server 61, with emphasis on the speed of provision.

The ship ECU 62b stops providing resources after the task "Tsunami Alert Service" is completed. For example, after the government and research institutes have finished collecting detailed data, the ship ECU 62b disables the various tools provided.

Then, the vessel ECU 62b calculates the charges to be imposed on the country and research institute that have received the resources, and on other vessels. The ship ECU 62b can charge the use of the resource only when the resource is used beyond the default number of times of use.

In addition, the information and response history obtained by the vessel ECU 62b performing the task "tsunami alert service" may be stored together with the damage information by another network system composed of nodes related to research institutions. . This will improve the accuracy of future tsunami damage simulations.

According to the task "Tsunami Alert Service", early detection of tsunami and simulation of damage can be carried out, and damage can be minimized.

In addition, the vessel ECU 62b negotiates with another network system configured by nodes related to research institutes, and determines whether or not to provide information, to which research institutes the information is provided, and the range of information to be provided. may be determined. Negotiation may be based on the output of a machine learning model (AI model).

For example, the ship ECU 62b may set an evaluation value and a threshold for each piece of information to be provided, and may provide only information whose evaluation value exceeds the threshold. Also, the threshold and the range of information provided may be determined by negotiation.

Also, the function of automatically providing information by the vessel ECU 62b may be disabled. In this case, provision of information is done manually by humans.

In addition, the network system 1A can store information to be provided to another network system composed of nodes related to research institutes in each node and form a block chain. This makes it possible to ensure the transparency and reliability of the information provided.

[Embodiment 2: Main engine monitoring support service]
With reference to FIG. 13, an example in which the task is "monitoring support service for the main machine" will be described. FIG. 13 is a diagram illustrating a configuration example of a network system.

The task "main engine monitoring support service" is to respond when an abnormality occurs in the ship's main engine.

As shown in FIG. 13, the ship 62 has a recording device 62a and a ship ECU 62b. In Example 2, the ship ECU 62b functions as a control node.

When an abnormality occurs in the main engine of the ship 62, the ship ECU 62b creates a network system 1B having the cloud server 61, the engine maker server 63a, the engine maker server 63b, and the engine maker server 63c as nodes.

Engine maker server 63 a , engine maker server 63 b , and engine maker server 63 c are servers from a plurality of different manufacturers (or licensors) that provide the same type of main engine as installed on vessel 62 .

Then, the ship ECU 62b uses the resources of the network system 1B to start processing for performing the task "monitoring support service for the main engine".

First, the ship ECU 62b inquires data from the cloud server 61 according to the type of main engine in which an abnormality has occurred, and obtains manufacturer, ship owner, ship nationality, registered ship class information, and the like. Then, the vessel ECU 62b selects a compatible engine manufacturer server based on the acquired information and incidental information such as the next port of call country. The ship ECU 62b may query the cloud server 61 for data after collecting information from a plurality of ships.

Note that there are a plurality of ships 62 . The ship ECU mounted on each ship 62 creates a group based on the type of main engine, manufacturer, ship owner, ship nationality, registered ship class information, and the like. This creates a group in which groups are further multiplexed.

The vessel ECU 62b causes the cloud server 61 to transmit data necessary for using an online support video conference system, an abnormality correction (correction) tool, etc. to the vessel 62 and the selected engine manufacturer server.

The vessel ECU 62b can only perform simple processing such as threshold determination of sensor values using only its own resources. On the other hand, the vessel ECU 62b can extend its functions by using the resources of the cloud server 61 and perform analysis using machine learning models.

By the ship ECU 62b performing the task "monitoring support service for the main engine", the engine manufacturer can easily deal with the abnormality of the main engine. Furthermore, it is possible to reduce main engine troubles (delays in the operation plan) that would cause the ship 62 to stop.

In addition, the ship ECU 62b can select the optimum communication line from a plurality of communication lines including the ship-to-land communication line according to the position of the ship 62 and use it as a communication path.

The ship ECU 62b may provide not only the resources of the cloud server 61 but also the resources of the ship ECU 62b itself. Further, the ship ECU 62b may provide only the resources that the ship ECU 62b itself has, without providing the resources of the cloud server 61, with emphasis on the speed of provision.

The ship ECU 62b stops providing the resource after the task "monitoring support service for the main engine" is completed. For example, the ship ECU 62b invalidates the tool after executing the abnormality correction (correction) tool.

Then, the vessel ECU 62b calculates a charge to be imposed on the vessel or engine maker that has received the provision of resources. The ship ECU 62b can charge the use of the resource only when the resource is used beyond the default number of times of use.

In addition, the information and response history obtained by the vessel ECU 62b performing the task "monitoring support service for the main engine" may be stored by another network system composed of nodes related to the vessel association. As a result, the stored information can be used by the shipping association as a failure history of the ship, and the ship owner may be exempted from reporting to the classification society and conducting on-site inspections.

In addition, the ship ECU 62b negotiates with another network system configured by nodes related to the ship association, and determines whether or not to provide information, to which ship association the information is provided, and the range of information to be provided. may be determined. Negotiation may be based on the output of a machine learning model (AI model).

For example, the ship ECU 62b may set an evaluation value and a threshold for each piece of information to be provided, and may provide only information whose evaluation value exceeds the threshold. Also, the threshold and the range of information provided may be determined by negotiation.

Also, the function of automatically providing information by the vessel ECU 62b may be disabled. In this case, provision of information is done manually by humans.

In addition, the network system 1A can store information to be provided to another network system composed of nodes related to shipping associations in each node and form a block chain. This makes it possible to ensure the transparency and reliability of the information provided.

[Example 3: Harbor maintenance monitoring service]
An example in which the task is "port maintenance watching service" will be described with reference to FIG. FIG. 14 is a diagram illustrating a configuration example of a network system.

The task "port maintenance monitoring service" is to respond when an abnormality occurs in port facilities.

As shown in FIG. 14, the ship 62 has a recording device 62a and a ship ECU 62b. In Example 3, the ship ECU 62b functions as a control node.

The ship ECU 62b creates a network system 1C having the cloud server 61 and the port facility server 65 as nodes when an abnormality occurs in the port facilities at the port currently calling. Port facilities include cranes, chassis, cargo handling equipment such as forklifts, lighting, power receiving and transforming equipment, fuel supply equipment, etc. Also, the dominating node may be a computer provided in port facilities.

Then, the vessel ECU 62b uses the resources of the network system 1C to start processing for performing the task "port maintenance watching service".

First, the ship ECU 62b inquires data from the cloud server 61 according to the type of port facility in which an abnormality has occurred, and obtains the port facility manufacturer, type, port administrator (including local government), port operator (for example, Obtain information from port administrators (borrowers, terminal operators), maintenance companies, shippers, etc. Then, the ship ECU 62b selects a port facility server 65 that can handle the situation based on the acquired information and incidental information such as the delay time of the ship 62 and weather information. The ship ECU 62b may query the cloud server 61 for data after collecting information from a plurality of ships.

Groups may be created multiple times by port facility manufacturers, types, port administrators, port operators, port users (for example, port operators who rent equipment from port operators), maintenance companies, shippers, etc. .

The ship ECU 62 b causes the cloud server 61 to transmit data necessary for using an online support video conference system, an abnormality correction (correction) tool, etc. to the ship 62 and the selected port facility server 65 .

The vessel ECU 62b can only perform simple processing such as threshold determination of sensor values using only its own resources. On the other hand, the vessel ECU 62b can extend its functions by using the resources of the cloud server 61 and perform analysis using machine learning models.

By the ship ECU 62b performing the task "port maintenance monitoring service", the port facility maker can easily deal with abnormalities in the port facility. Furthermore, it is possible to reduce troubles that stop the harbor facilities.

Further, the ship ECU 62b selects the most suitable communication line based on the location of the port facility server 65 from a plurality of communication lines including the communication line contracted by the port manager or the port operator, and uses it as a communication path. can be done.

The ship ECU 62b may provide not only the resources of the cloud server 61 but also the resources of the ship ECU 62b itself. Further, the ship ECU 62b may provide only the resources that the ship ECU 62b itself has, without providing the resources of the cloud server 61, with emphasis on the speed of provision.

The ship ECU 62b stops providing resources after the task "port maintenance watching service" is completed. For example, the ship ECU 62b invalidates the tool after executing the abnormality correction (correction) tool.

Then, the ship ECU 62b calculates charges to be imposed on the port facility maker (owner of the port facility server 65), the port manager, and the port operator who have received the resources. The ship ECU 62b can charge the use of the resource only when the resource is used beyond the default number of times of use.

In addition, the information and response history obtained by the vessel ECU 62b performing the task "port maintenance watching service" may be stored by another network system configured by nodes related to port administrators. As a result, the stored information can be utilized by the port administrator as a failure history of port facilities, and the port operator and port users may be exempted from reporting to the port administrator and on-site inspections.

In addition, the ship ECU 62b negotiates with another network system configured by nodes related to port administrators to determine whether information is to be provided, to which port administrators the information is to be provided, and the information to be provided. may determine the range of Negotiation may be based on the output of a machine learning model (AI model).

For example, the ship ECU 62b may set an evaluation value and a threshold for each piece of information to be provided, and may provide only information whose evaluation value exceeds the threshold. Also, the threshold and the range of information provided may be determined by negotiation.

Also, the function of automatically providing information by the vessel ECU 62b may be disabled. In this case, provision of information is done manually by humans.

In addition, the network system 1A can store information to be provided to another network system composed of nodes related to port administrators in each node and block chain it. This makes it possible to ensure the transparency and reliability of the information provided.

[Example 4: Ship-port cooperation service]
An example in which the task is "ship-port cooperation service" will be described with reference to FIG. FIG. 15 is a diagram illustrating a configuration example of a network system.

The task "Ship-Port Coordination Service" is to maintain the vessels that have called at the port.

As shown in FIG. 15, the ship 62 has a recording device 62a and a ship ECU 62b. In Example 1, the ship ECU 62b functions as a control node.

When the vessel ECU 62b detects a decrease in fuel efficiency while the vessel 62 is sailing on the Pacific Ocean route (for example, when the fuel efficiency per unit time falls below a threshold value), the vessel ECU 62b establishes a network system with the cloud server 61 and the maintenance server 66 as nodes. Create 1D.

Then, the ship ECU 62b uses the resources of the network system 1D to start processing for executing the task "ship-port cooperation service".

First, the ship ECU 62b inquires data to the cloud server 61 according to the position of the ship 62, and obtains information on candidate ports of call on the navigation route and information such as the scheduled time of call. Then, the ship ECU 62b performs maintenance (inspection, cleaning (ship Select the request destination and the port of call for the whole or around the propeller) and repair).

Note that there are a plurality of ships 62 . The ship ECU mounted on each ship 62 creates a group including ports close to the route of the ship 62, maintenance request destinations, and the like. This creates a group in which groups are further multiplexed.

The ship ECU 62b causes the cloud server 61 to transmit data necessary for using the online support video conference system, maintenance (inspection, cleaning, repair) services, etc. to the selected maintenance server 66 to which maintenance is requested. The maintenance server 66 is a server for implementing a harbor management system, a harbor equipment remote monitoring system, and the like.

In addition, the ship ECU 62b selects the scheduled time of call at the port of call, the estimated delay time assumed from the port operation status, and the services that can be provided by the selected request destination. At this time, the ship ECU 62b performs a simulation using the resources of the cloud server 61 so that the operating rate of the port does not decrease due to a sudden demurrage of the ship, and then adjusts the cargo handling system of the port as necessary.

The vessel ECU 62b can only perform simple processing such as threshold determination of sensor values using only its own resources. On the other hand, the vessel ECU 62b can extend its functions by using the resources of the cloud server 61 and perform analysis using machine learning models.

By the ship ECU 62b executing the task "ship-port cooperation service", it is possible to detect a decrease in the fuel consumption of the ship 62 at an early stage.

In addition, the ship ECU 62b can select the optimum communication line from a plurality of communication lines including the ship-to-land communication line according to the position of the ship 62 and use it as a communication path.

The ship ECU 62b may provide not only the resources of the cloud server 61 but also the resources of the ship ECU 62b itself. Further, the ship ECU 62b may provide only the resources that the ship ECU 62b itself has, without providing the resources of the cloud server 61, with emphasis on the speed of provision.

The ship ECU 62b stops providing resources after the task "ship-port cooperation service" is completed. For example, when the request for maintenance such as cleaning is completed, the vessel ECU 62b invalidates the provided various tools.

Then, the vessel ECU 62b calculates the charge to be imposed on the maintenance request destination (the owner of the maintenance server 66) who receives the provision of the resource. The ship ECU 62b can charge the use of the resource only when the resource is used beyond the default number of times of use.

Further, the information and response history obtained by the ship ECU 62b performing the task "ship-port cooperation service" may be stored in the maintenance server 66 together with the information on the port of call. The stored information is used for maintenance simulation, fuel efficiency improvement, and optimum route simulation.

[Other Examples]
In addition, the dominating node can create a network system as shown in FIG. FIG. 16 is a diagram illustrating a configuration example of a network system.

As shown in FIG. 16, the network system 1E includes a cloud server 61, a ship 62 (including a recording device 62a and a ship ECU 62b), a shipper terminal 71, an operator terminal 72, a broker terminal 73, a shipowner terminal 74, and an insurance company server 75. , a shipyard server 76 , an engine manufacturer server 77 and a marine system server 78 . One of the devices included in the network system 1E functions as a dominating node, and the other devices function as general nodes.

The cloud server 61 can provide data as resources for executing the tools and services described in each embodiment.

The shipper terminal 71 is a terminal used by the shipper of the ship 62 . The operator terminal 72 is a terminal used by an operator. The operator terminal 72 provides the shipper terminal 71 with port management cooperation, cargo handling support, and support for marine transportation. The operator terminal 72 also receives fuel efficiency improvement support from the cloud server 61 .

The broker terminal 73 is a terminal used by the broker. The ship owner terminal 74 is a terminal used by the ship owner of the ship 62 . The broker terminal 73 exchanges information on buying and selling second-hand ships with the ship owner terminal 74 . The ship owner terminal 74 receives support for labor cost reduction from the cloud server 61 and also receives information on new ships from the shipyard server 76 .

The insurance company server 75 is a server used by an insurance company. The insurance company server 75 provides the ship owner terminal 74 with insurance-related information and AI monitoring and analysis results of the ship 62 . The insurance company server 75 also supports the ship owner terminal 74 in accident prevention.

Insurance company server 75 receives from cloud server 61 information on steering proficiency, breakdowns and accidents regarding vessel 62 .

The engine manufacturer server 77 provides the marine system server 78 with engine operating data and the like.

Marine system server 78 is a server used in the marine system. Marine system server 78 provides operational data to cloud server 61 . The marine system includes a system for managing loading and unloading of the vessel 62, a system for monitoring containers on the vessel 62, and the like.

Also, the recording device 62 a records data regarding the ship 62 . Data relating to driving, images, freight, ecology, etc. are input to the recording device 62a on-line. In addition, logs obtained by the ship 62 and manually input data related to maintenance are input to the recording device 62a offline. Also, the ship ECU 62b transmits various data including the data recorded in the recording device 62a to the cloud server 61 .

So far, embodiments have been described in which the resource is a computer resource (computer resource). On the other hand, resources provided by nodes are not limited to computer resources.

For example, the resource may be a main engine that is lent to a ship by an engine manufacturer. The dominating node 20 calculates a fee to be charged for the main engine, which is a resource, based on the cruising distance of the ship equipped with the main engine rented from the engine manufacturer. For example, the dominating node 20 calculates the charge by multiplying a predetermined amount of money per unit distance by the traveled distance of the vessel. Also, the dominating node 20 may calculate the fare based on the navigation time instead of the navigation distance.

For example, the charge calculated by the dominating node 20 is billed to the owner of the ship by the engine manufacturer.

FIG. 17 is a diagram illustrating a hardware configuration example of a controlling device according to the embodiment; A device that functions as a general node may also have the same configuration as the supervising device.

As shown in FIG. 17 , the dominating node 20 (dominating device) includes a computer having a processor 2010 , a memory 2020 , an input/output IF 2030 and a bus 2040 . Processor 2010 , memory 2020 , and input/output IF 2030 can transmit and receive information to and from each other via bus 2040 .

The processor 2010 performs each function by reading and executing the general program stored in the memory 2020 . The processor 2010 is an example of a processing circuit, for example, and includes one or more of a CPU, a DSP (Digital Signal Processor), and a system LSI (Large Scale Integration).

Memory 2020 includes one or more of RAM, ROM, flash memory, EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory). The input/output IF 2030 includes, for example, an AD converter, a DA converter, and an input/output port.

Note that the dominating node 20 may be configured to include a data reading unit that reads the dominating program from a recording medium in which the computer-readable dominating program is recorded. The processor 2010 can control the data reading unit to acquire the general program recorded on the recording medium from the data reading unit, and store the acquired general program in the memory 2020 . Recording media include, for example, one or more of non-volatile or volatile semiconductor memories, magnetic disks, flexible memories, optical disks, compact disks, and DVDs (Digital Versatile Disks).

The dominating node 20 may also include a communication unit that receives the dominating program from the server via the network. In this case, the processor 2010 can acquire the supervisory program from the server via the communication unit and store the acquired supervisory program in the memory 2020 .

The dominating node 20 may also include integrated circuits such as ASICs (Application Specific Integrated Circuits) and FPGAs (Field Programmable Gate Arrays).

It should be considered that the embodiments disclosed this time are illustrative in all respects and not restrictive. Indeed, the above-described embodiments may be embodied in many different forms. Also, the above-described embodiments may be omitted, substituted, or modified in various ways without departing from the scope and spirit of the appended claims.

1, 1A, 1B, 1C, 1D, 1E network system 10, 10a, 10b, 10c, 10d, 10e, 10f node 20 control node 11, 21 functional unit 12, 22 resource unit 111, 211 resource management function 112, 212 communication Functions 113, 213 Billing functions 114, 214 Monitoring functions 121, 221 Hardware resources 122, 222 Software resources 123, 223 DB resources 215 Operation management function 2151 Information acquisition unit 2152 Group creation unit 2153 Processing execution unit 2154 Node information 2155 Task information

Claims (14)

an information acquisition unit for acquiring information on a plurality of nodes, which are a plurality of computers each having a computer resource for performing a preset ocean-related task and capable of communicating data with each other;
A group for creating a group including an ECU mounted on a ship and one or more servers among the plurality of nodes as nodes according to the information of the plurality of nodes and the task obtained by the information obtaining unit. creation department,
and a processing execution unit that causes a plurality of nodes included in the group to perform data communication with each other and to provide the computer resource, thereby executing processing according to the task. 2. The supervising apparatus according to claim 1, wherein the processing execution unit distributes the nodes that provide the computer resources in accordance with the usage status of the computer resources of each of the plurality of nodes. The group creation unit creates the group using a machine learning model that outputs a combination of nodes included in the plurality of nodes for executing the processing, based on information of the plurality of nodes. 2. A centralizing device according to claim 1. 2. The supervising device according to claim 1, wherein the processing execution unit causes the plurality of nodes to function as a block chain by storing the same data in each of the plurality of nodes. The group creating unit uses a machine learning model for outputting a communication route for data communication based on information about the plurality of nodes, and a communication route for the plurality of nodes to perform data communication with each other. 2. The generalizing device according to claim 1, characterized in that it determines . 2. The generalizing device according to claim 1, wherein said processing execution unit calculates a fee charged for said computer resources provided by each of said plurality of nodes in order to execute said processing. . The group creating unit creates the group further including a server of a manufacturer of the main engine of the ship as a node ,
2. The supervising device according to claim 1, wherein the processing execution unit causes the plurality of nodes included in the group to execute processing for supporting navigation of the vessel. an information acquisition step of acquiring information on a plurality of nodes, which are a plurality of computers each having a computer resource for performing a preset ocean-related task and capable of communicating data with each other;
A group for creating a group including an ECU mounted on a ship and one or more servers among the plurality of nodes as nodes according to the information of the plurality of nodes and the task obtained by the information obtaining step. a creation step;
a process execution step of causing a plurality of nodes included in the group to communicate data with each other and to provide the computer resources, thereby executing a process corresponding to the task; management program. 9. The overall control program according to claim 8, wherein said processing execution step distributes the nodes that provide said computer resources according to the usage status of said computer resources of each of said plurality of nodes. The group creation step includes creating the group using a machine learning model that outputs a combination of nodes included in the plurality of nodes for executing the process, based on the information of the plurality of nodes. 9. The generalization program according to claim 8. 9. The supervising program according to claim 8, wherein said processing execution step causes said plurality of nodes to function as a block chain by storing the same data in each of said plurality of nodes. The group creation step uses a machine learning model for outputting a communication path for data communication based on information about the plurality of nodes, and a communication path for the plurality of nodes to perform data communication with each other. 9. The generalization program according to claim 8, characterized in that it determines . 9. The supervisory program according to claim 8, wherein said process execution step calculates a fee charged for said computer resources provided by each of said plurality of nodes in order to execute said process. . The group creation step creates the group further including a server of a manufacturer of the ship's main engine as a node ;
9. The supervising program according to claim 8, wherein said processing execution step causes a plurality of nodes included in said group to execute processing for supporting operation of said vessel.

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