CN111639134A - Industrial link supervision method and system based on block chain - Google Patents
Industrial link supervision method and system based on block chain Download PDFInfo
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- CN111639134A CN111639134A CN202010479773.8A CN202010479773A CN111639134A CN 111639134 A CN111639134 A CN 111639134A CN 202010479773 A CN202010479773 A CN 202010479773A CN 111639134 A CN111639134 A CN 111639134A
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Abstract
The invention provides a block chain-based industrial link supervision method and system, when the method is used, each handover link in an industrial chain is used as a node, an image during handover is collected in each node, then the collected handover image is transferred and stored as data and compressed, the compressed data of all the nodes are packed into a first block within fixed time, and an industrial block chain is constructed, so that the handover image can be prevented from being tampered; the method comprises the steps of carrying out image recognition analysis on collected images by adopting an image recognition algorithm, automatically analyzing and extracting violation frames, packaging the violation frames of all nodes into a second block, and constructing the second block into a supervision block chain.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to an industrial link supervision method and system based on a block chain.
Background
In the prior art, each link of an industrial chain is relatively independent and is difficult to trust each other, so that a third-party detection and authentication mechanism is required to participate, the third-party detection and authentication mechanism is a center of the whole detection and authentication process, product quality information is given, and each performance index of a product is guaranteed to meet the regulations of relevant standards and user requirements by the authority and the fairness of the third-party detection and authentication mechanism.
However, this mode has extremely low trust transfer efficiency, and may have unreal behaviors such as tampering data, detecting reports, etc., and situations such as intentionally concealing quality problems, etc., so as to reduce the credibility of information and have high quality control risk. Meanwhile, on the premise that direct mutual trust cannot be achieved, cooperation work cannot be performed among all the ring sections of the industrial chain, a large amount of repeated verification and inspection work needs to be performed, the operation efficiency of the whole industrial chain is low, and a large amount of time and cost are wasted in establishing and transmitting trust. Meanwhile, in the traditional mode, when the problem of the handover link occurs and the problem reason needs to be traced, the related responsible party on the industrial chain can reduce the responsibility born by the responsible party to the minimum by destroying and forging the related evidence of the handover link, and finally the unreliability of each handover link of the industrial chain is caused.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an industrial link supervision method and system based on a block chain, which can record the images of all the handover links in the industrial chain and store the images in a distributed manner.
An industrial link supervision method based on a block chain comprises the following steps:
collecting an industry handover image, and storing the industry handover image as compressed data;
taking each intersection point as a node, packaging the compressed data of all nodes into a first block in a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
image recognition algorithm is adopted in each node to conduct image recognition analysis on the cross-connection image to obtain violation frames, the violation frames of all the nodes are packaged into second blocks in a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring block chain, and data of the second blocks are stored in each node in a distributed mode.
Further, the industry cross-over image is a cross-over process image of each cross-over point in the industry.
Further, the industry cross-over image is a picture or a short video of a cross-over process of each cross-over point in the industry.
Furthermore, an RLE algorithm is adopted to compress the industry connection image into compressed data.
Furthermore, the cross-over point comprises a monitoring device, and the monitoring device collects industry cross-over images.
An industrial link supervision system based on a block chain comprises an industrial handover node module, wherein the industrial handover node module collects industrial handover images and stores the industrial handover images as compressed data;
taking each intersection point as a node, packaging the compressed data of all the nodes into a first block by a node module or a superior server within a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
the method comprises the steps that image recognition analysis is carried out on a handover image in each node module by adopting an image recognition algorithm to obtain violation frames, the node modules or the upper server pack the violation frames of all nodes into second blocks within a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring area block chain, and data of the second blocks are stored in each node in a distributed mode.
Further, the industry cross-over image is a cross-over process image of each cross-over point in the industry.
Further, the industry cross-over image is a picture or a short video of a cross-over process of each cross-over point in the industry.
Furthermore, an RLE algorithm is adopted to compress the industry connection image into compressed data.
Furthermore, the cross-over point comprises a monitoring device, and the monitoring device collects industry cross-over images.
When the method is used, each handover link in an industrial chain is used as a node, images during handover are collected in each node, the collection process can be carried out by a certain camera in the handover link or by handover personnel, then the collected handover images are transferred and stored as data and compressed, and the transfer and storage compression process can be carried out by a handover terminal in charge of the node; then, constructing a block chain, and packing the compressed data of all nodes into a first block within a fixed time, wherein the fixed time can be preset, for example, 12 hours or 24 hours; the compression time of compressed data, the hash of the compressed data and the hash of the last block are recorded into the block head of the current block as a block characteristic value, the compressed data are recorded into the block body of the current block, then blocks generated successively are constructed into an industrial block chain, and the data in the blocks are stored in each node in a distributed manner; in order to further improve the supervision of an industrial chain handover link, an image recognition algorithm is adopted to perform image recognition analysis on the acquired image, an illegal action frame, namely an image frame corresponding to the illegal action, is automatically analyzed and extracted, a reference value of the illegal action can be preset, the image recognition algorithm is adopted to automatically search for a frame which is the same as or similar to the reference value, and after the illegal action frame is recognized, a supervision area block chain is constructed for the illegal action frame; specifically, the violation frames of all nodes are packed into a second block within a certain time period, and then the second block is constructed into a supervision block chain, wherein the collection time of the violation frames, the hash of the violation frames and the hash of the previous block are specifically recorded into the block header of the current second block as a characteristic value, and the data of the violation frames are recorded into the block body of the current second block. Therefore, an independent monitoring area block chain is constructed for identifying the extracted violation frames, the data volume of the block chain is small, a large number of useless images cannot be recorded, and the block chain and the industrial block chain of the first block are independent and do not influence each other, when the violation is required to be called, the violation can be called quickly from the monitoring area block chain, and the violation frames do not need to be found for being called and used by searching and looking up a large number of illegal action frames from the industrial block chain; after the violation frame is quickly called from the monitoring area block chain, the front and rear complete images of the violation frame can be called from the complete images in the industrial area block chain according to the collection time of the violation frame as a retrieval basis to know a complete event.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby. It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
The invention firstly provides a method, in particular to an industrial link supervision method based on a block chain, which comprises the following steps: collecting an industry handover image, and storing the industry handover image as compressed data; taking each intersection point as a node, packaging the compressed data of all nodes into a first block in a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
image recognition algorithm is adopted in each node to conduct image recognition analysis on the cross-connection image to obtain violation frames, the violation frames of all the nodes are packaged into second blocks in a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring block chain, and data of the second blocks are stored in each node in a distributed mode.
In an actual implementation manner, the specific steps of this embodiment may be:
taking each handover link in an industrial chain as a node, collecting images during handover in each node, wherein the collection process can be collection by a certain camera in the handover link or collection by handover personnel, then transferring the collected handover images into data and compressing the data, and the transfer compression process can be carried out by a handover terminal in charge of the node;
then, constructing a block chain, and packing the compressed data of all nodes into a first block within a fixed time, wherein the fixed time can be preset, for example, 12 hours or 24 hours; the compression time of compressed data, the hash of the compressed data and the hash of the last block are recorded into the block head of the current first block as a block characteristic value, the compressed data are recorded into the block body of the current first block, then the first blocks generated successively are constructed into an industrial block chain, and the data in the first blocks are stored in each node in a distributed manner;
in order to further improve the supervision of an industrial chain handover link, an image recognition algorithm is adopted to perform image recognition analysis on the acquired image, an illegal action frame, namely an image frame corresponding to the illegal action, is automatically analyzed and extracted, a reference value of the illegal action can be preset, the image recognition algorithm is adopted to automatically search for a frame which is the same as or similar to the reference value, and after the illegal action frame is recognized, a supervision area block chain is constructed for the illegal action frame; specifically, the violation frames of all nodes are packed into a second block within a certain time period, and then the second block is constructed into a supervision block chain, wherein the collection time of the violation frames, the hash of the violation frames and the hash of the previous block are specifically recorded into the block header of the current second block as a characteristic value, and the data of the violation frames are recorded into the block body of the current second block. Therefore, an independent monitoring area block chain is constructed for identifying the extracted violation frames, the data volume of the block chain is small, a large number of useless images cannot be recorded, and the block chain and the industrial block chain of the first block are independent and do not influence each other, when the violation is required to be called, the violation can be called quickly from the monitoring area block chain, and the violation frames do not need to be found for being called and used by searching and looking up a large number of illegal action frames from the industrial block chain; after the violation frame is quickly called from the monitoring area block chain, the front and rear complete images of the violation frame can be called from the complete images in the industrial area block chain according to the collection time of the violation frame as a retrieval basis to know a complete event.
In practical use, the industrial handover may be, for example, a link handover in logistics, a link handover in storage, a shift link of a taxi, and a passenger receiving and getting-off link of a net appointment car, and the device for acquiring the image may be any device having a camera function in the link handover.
Specifically, in some embodiments, the industry handover image is a handover process image of each handover point in the industry, i.e., a continuous video recording is performed at each handover point, and the image of the whole process is recorded, but this method is memory-consuming.
In another embodiment, the industry cross-over image is a picture or a short video of the cross-over process of each cross-over point in the industry, that is, the picture or the short video is intermittently captured among the cross-over points, so that the memory can be saved, but a lot of pictures or short videos can be captured.
Preferably, the RLE algorithm is used to compress the industry interfacing image into compressed data.
Specifically, including supervisory equipment on the handing-over point, supervisory equipment gathers industry handing-over image, adopts some supervisory equipment to carry out image acquisition to handing-over link promptly.
An industrial link supervision system based on a block chain comprises an industrial handover node module, wherein the industrial handover node module collects industrial handover images and stores the industrial handover images as compressed data;
taking each intersection point as a node, packaging the compressed data of all the nodes into a first block by a node module or a superior server within a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
the method comprises the steps that image recognition analysis is carried out on a handover image in each node module by adopting an image recognition algorithm to obtain violation frames, the node modules or the upper server pack the violation frames of all nodes into second blocks within a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring area block chain, and data of the second blocks are stored in each node in a distributed mode.
When the system is used, each handover link in an industrial chain is used as a node, a node module is arranged in each node, and the node module collects images during handover, wherein the collection process can be collection by a certain camera in the handover link or collection by handover personnel, and then the collected handover images are transferred and stored into data through storage computing equipment arranged in the node module and are compressed; the node modules can be specifically terminal equipment, intelligent equipment and the like operated in an industrial handover link, such as a code scanner during logistics storage handover, monitoring equipment in a network car reservation, a smart phone used by a client during getting on and off of the network car reservation and the like;
then constructing a block chain, and packaging the compressed data of all nodes into a first block within a fixed time, wherein the packaging process can be carried out by a node module or a superior server; the fixed time may be preset, for example, 12 hours or 24 hours; the compression time of compressed data, the hash of the compressed data and the hash of the last block are recorded into the block head of the current block as a block characteristic value, the compressed data are recorded into the block body of the current block, then blocks generated successively are constructed into an industrial block chain, and the data in the blocks are stored in each node in a distributed manner; the description mode of the block header and the block body may be described by the node module, or may be described by a subordinate server of the node module.
In order to further improve the supervision of an industrial chain handover link, an image recognition algorithm is adopted in a node module to perform image recognition analysis on an acquired image, an illegal action frame, namely an image frame corresponding to the illegal action, is automatically analyzed and extracted, a reference value of the illegal action can be preset, a frame which is the same as or similar to the reference value is automatically searched by adopting the image recognition algorithm, and a supervision block chain is constructed aiming at the illegal action frame after the illegal action frame is recognized; specifically, the violation frames of all nodes are packed into a second block within a certain time period, and then the second block is constructed into a supervision block chain, wherein the collection time of the violation frames, the hash of the violation frames and the hash of the previous block are specifically recorded into the block header of the current second block as a characteristic value, and the data of the violation frames are recorded into the block body of the current second block. Therefore, an independent monitoring area block chain is constructed for identifying the extracted violation frames, the data volume of the block chain is small, a large number of useless images cannot be recorded, and the block chain and the industrial block chain of the first block are independent and do not influence each other, when the violation is required to be called, the violation can be called quickly from the monitoring area block chain, and the violation frames do not need to be found for being called and used by searching and looking up a large number of illegal action frames from the industrial block chain; after the violation frame is quickly called from the monitoring area block chain, the front and rear complete images of the violation frame can be called from the complete images in the industrial area block chain according to the collection time of the violation frame as a retrieval basis to know a complete event.
In practical use, the industrial handover may be, for example, a link handover in logistics, a link handover in storage, a shift link of a taxi, and a passenger receiving and getting-off link of a net appointment car, and the device for acquiring the image may be any device having a camera function in the link handover.
In this embodiment, the industry handover image is a handover process image of each handover point in the industry, that is, a continuous video recording is performed at each handover point, and an image of the whole process is recorded, but this method is memory-consuming.
Further, the industry handover image is a picture or a short video of a handover process of each handover point in the industry, that is, the picture or the short video is intermittently and discontinuously acquired among the handover points, so that the memory can be saved, but a lot of pictures or short videos which can be used can be basically acquired.
Furthermore, an RLE algorithm is adopted to compress the industry connection image into compressed data.
Further, the cross-over point is provided with a monitoring device, the monitoring device collects industry cross-over images, namely, the monitoring device collects images of the cross-over link.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. An industrial link supervision method based on a block chain is characterized by comprising the following steps: the method comprises the following steps:
collecting an industry handover image, and storing the industry handover image as compressed data;
taking each intersection point as a node, packaging the compressed data of all nodes into a first block in a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
image recognition algorithm is adopted in each node to conduct image recognition analysis on the cross-connection image to obtain violation frames, the violation frames of all the nodes are packaged into second blocks in a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring block chain, and data of the second blocks are stored in each node in a distributed mode.
2. The block chain-based industry link supervision method according to claim 1, wherein:
the industry handover image is a handover process image for each handover point in the industry.
3. The block chain-based industry link supervision method according to claim 2, wherein:
the industry cross-over image is a picture or short video of the cross-over process of each cross-over point in the industry.
4. The block chain-based industry link supervision method according to claim 3, wherein:
and compressing the industry interfacing image into compressed data by adopting an RLE algorithm.
5. The block chain-based industry link supervision method according to claim 4, wherein:
the cross-over point comprises a monitoring device, and the monitoring device collects industry cross-over images.
6. The utility model provides an industry link supervisory systems based on block chain which characterized in that:
the system comprises an industry cross-connection node module, a data processing module and a data processing module, wherein the industry cross-connection node module is used for acquiring an industry cross-connection image and storing the industry cross-connection image as compressed data;
taking each intersection point as a node, packaging the compressed data of all the nodes into a first block by a node module or a superior server within a fixed time period, sequentially constructing the sequentially generated first blocks into an industrial block chain, and storing the data of the first blocks in each node in a distributed manner;
the method comprises the steps that image recognition analysis is carried out on a handover image in each node module by adopting an image recognition algorithm to obtain violation frames, the node modules or the upper server pack the violation frames of all nodes into second blocks within a preset time period, the second blocks generated in sequence are sequentially constructed into a monitoring area block chain, and data of the second blocks are stored in each node in a distributed mode.
7. The system of claim 6, wherein:
the industry handover image is a handover process image for each handover point in the industry.
8. The system of claim 7, wherein:
the industry cross-over image is a picture or short video of the cross-over process of each cross-over point in the industry.
9. The system of claim 8, wherein the system comprises:
and compressing the industry interfacing image into compressed data by adopting an RLE algorithm.
10. The system of claim 9, wherein the system comprises:
the cross-over point comprises a monitoring device, and the monitoring device collects industry cross-over images.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117649061A (en) * | 2024-01-30 | 2024-03-05 | 山东达斯特信息技术有限公司 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117649061A (en) * | 2024-01-30 | 2024-03-05 | 山东达斯特信息技术有限公司 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
| CN117649061B (en) * | 2024-01-30 | 2024-04-26 | 山东达斯特信息技术有限公司 | Multi-node networking electricity analysis method and system for environmental protection monitoring |
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