WO2021217914A1 - Procédé et appareil d'extraction de preuve d'endommagement, dispositif informatique et support de stockage - Google Patents

Procédé et appareil d'extraction de preuve d'endommagement, dispositif informatique et support de stockage Download PDF

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Publication number
WO2021217914A1
WO2021217914A1 PCT/CN2020/103839 CN2020103839W WO2021217914A1 WO 2021217914 A1 WO2021217914 A1 WO 2021217914A1 CN 2020103839 W CN2020103839 W CN 2020103839W WO 2021217914 A1 WO2021217914 A1 WO 2021217914A1
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WIPO (PCT)
Prior art keywords
information
target object
feature information
damage
data
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PCT/CN2020/103839
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English (en)
Chinese (zh)
Inventor
张超
赵勇
方永远
潘毅
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平安国际智慧城市科技股份有限公司
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Publication of WO2021217914A1 publication Critical patent/WO2021217914A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance

Definitions

  • This application relates to the field of smart logistics in smart cities, and in particular to methods, devices, computer equipment, and storage media for extracting damaged evidence.
  • Container transportation is an important part of modern international logistics. With the acceleration of economic globalization and the rapid development of international trade, container transportation has become an important form of transportation modernization due to its high efficiency, convenience and safety.
  • the current transportation system mainly tracks the goods according to the waybill number, and does not have the technology to track and detect the damage of the container.
  • the inventor realizes that the container is damaged and lost during the transportation, loading and unloading process, but it is difficult to determine the damage.
  • a device that can effectively distinguish, collect and extract the damage and shortage of container cargo.
  • This application provides a method for extracting damaged evidence, including the following steps:
  • This application also provides a device for extracting damaged evidence, including:
  • the collection unit is used to collect the characteristic information of the target object
  • a generating unit configured to generate stereo feature information based on the feature information
  • the matching unit is configured to match the three-dimensional feature information with preset reference information to obtain damage information
  • the acquiring unit is configured to encrypt the damaged information to generate damaged evidence data.
  • the present application also provides a computer device that includes a memory, a processor, and computer-readable instructions that are stored in the memory and can run on the processor.
  • the processor executes the computer-readable instructions to implement The following steps of the damaged evidence extraction method:
  • the present application also provides a computer-readable storage medium on which computer-readable instructions are stored, and when the computer-readable instructions are executed by a processor, the following steps of the method for extracting damaged evidence are realized:
  • the damaged evidence extraction method, device, computer equipment and storage medium provided in this application can process the collected feature information of the target object to generate three-dimensional feature information. By matching the three-dimensional feature information with preset reference information, it is determined whether the target object is If there is damage, then obtain the corresponding damage information and encrypt it to generate damage evidence data to provide reliable damage evidence for insurance claims.
  • FIG. 1 is a flowchart of an embodiment of the method for extracting damaged evidence described in this application
  • FIG. 2 is a flowchart of an embodiment of collecting characteristic information of a target object in this application
  • FIG. 3 is a flowchart of an embodiment of generating stereo feature information based on feature information in this application;
  • FIG. 4 is a flow chart of an embodiment of the application for matching three-dimensional feature information with preset reference information to obtain damage information
  • FIG. 5 is a block diagram of an embodiment of the device for extracting damaged evidence according to this application.
  • FIG. 6 is a hardware architecture diagram of an embodiment of the computer device of this application.
  • the damaged evidence extraction method, device, computer equipment, and storage medium provided in this application can be applied to the field of smart cities, such as smart medical services, smart transportation services, and smart life services.
  • This application can process the collected feature information of the target object to generate three-dimensional feature information. By matching the three-dimensional feature information with preset reference information, it is determined whether the target object is damaged. If so, the corresponding damage information is obtained and the corresponding damage information is obtained. Encryption, generate damage evidence data, and provide reliable damage evidence for insurance claims.
  • a method for extracting damage evidence in this embodiment includes the following steps:
  • Tag is configured on the target object.
  • the target object is used to refer to a container.
  • the tag installed on the container is a high-frequency, active tag.
  • the tag includes sleep mode and working mode. When the tag is not triggered, the tag is in sleep mode; when the tag enters the reading area, it is in sleep mode. Switch to working mode and send tag information for the reader module to read the tag information, or the reader module can write the corresponding information into the tag.
  • the switch between sleep mode and working mode can effectively save the energy of the label, usually the label can work for ten years.
  • step S1 shown in FIG. 2 to collect characteristic information of the target object includes:
  • the position information of the reading module can be obtained by setting a GPS positioning module on the reading module.
  • the position of the reading module is fixed, and a positioning module can be configured on the reading module to obtain the position information of the preset area; the reading module can be a reader.
  • the effective reading distance between the tag and the reader can reach 100m, and the reader can read the tag information on objects moving at a high speed (such as 120km/h).
  • Reading the tag information of the target object is mainly used in a preset area (a small area), and the location information can be static or dynamic.
  • the collection of dynamic position information (such as the entrance and exit and the position when moving in a certain area) is relatively simple.
  • the static position is mainly to obtain the plane coordinate position and the three-dimensional coordinate position (in order to save space, the containers are generally placed in a stacked manner).
  • the status information of the container can be written into the tag through the reader.
  • the status information can include aggregated information and de-aggregated information.
  • Aggregated information refers to the process of loading goods; de-aggregated information is the process of unloading goods from the container.
  • Aggregated information is mainly to use barcode technology to package items, then add tags or barcodes on the packaging boxes, and then put the boxes with added tags or barcodes into the container, and add active tags to the container.
  • RFID radio frequency
  • the information loaded on each cargo can be sent to the data server through a barcode reader and an RFID reader through a wired or wireless manner, and then the data server compares the loaded cargo information with the basic information of the container (such as arrival station, departure station, arrival time, etc.), after confirming that it is correct through comparison, write the data of this operation to the tag.
  • the data server can also send confirmation information to the operator's handheld device, and write data to the tag after the operator's confirmation.
  • Aggregation and de-aggregation operations are very important for LCL operations. LCL is the assembly of multiple customer goods in one box. It is easy to mistakenly load the goods in one box to another, resulting in loss of goods or wrong submission Condition. The use of aggregation and de-aggregation operations can effectively solve this problem.
  • Data collision refers to the simultaneous arrival of multiple radio frequency signals in the recognition area of the reader. It will respond to the commands of the reader and send signals to the reader at the same time, causing channel contention problems, signal interference with each other, leading to reading The device cannot correctly identify the data in the electronic tag, that is, a collision has occurred.
  • Tag collision and Reader collision There are two main types of data collision: Tag collision and Reader collision.
  • the time domain method (deterministic algorithm and uncertainty algorithm) can be adopted.
  • the uncertainty algorithm the tag randomly generates the response time.
  • Many uncertainty algorithms are based on the Aloha algorithm.
  • the deterministic algorithm is that the reader selects different tags to respond by searching for the unique ID of the tag.
  • Binary tree search method is the simplest deterministic algorithm.
  • the Colorwave protocol uses the localized characteristics of reader and tag communication to provide a real-time, distributed, and local MAC protocol to allocate communication frequencies and time slots for readers to reduce interference between readers. This method can greatly increase the communication load of the system. Data security is to prevent the reading equipment of other systems from reading or changing the information in the RFID Tag on the container.
  • middleware In order to prevent data leakage (such as: reading equipment of other systems to read or modify the information in the RFID Tag on the container), physical isolation, stop tag services, read access control, and dual-tag joint verification (yoking-proof) can be used Law. These methods are all based on hardware implementation.
  • middleware is used to realize the basic data collection of the container and its cargo.
  • RFID hardware can effectively solve the data collision and safety problems. Therefore, the middleware mainly solves: (1) the safety of the middleware itself and Data security issues in the process of interacting with existing systems; (2) Basic data reliability issues, including data redundancy and data errors.
  • the problem of data redundancy is that a tag (container) passes through the reading area for many times or stays in the reading area for a long time without any changes, causing the reader to obtain repeated data multiple times.
  • a combination of two mechanisms is used: data filtering and controlled reading.
  • Data filtering is to filter the data of the same label in the same time period, and the filtering processing operation is implemented in the local middleware.
  • the data filtering technology does not reduce the number of times to read RFID Tag.
  • RFID Tag will consume energy due to multiple readings and reduce the service life of RFID Tag.
  • the local data center can control the landmark to send a reading trigger signal within a certain time interval (for example, once every ten minutes). This can effectively save the energy of the tag and increase the service life of the tag.
  • Data error refers to the wrong data obtained during the basic data reading process (for example, the data is read when it should not be read, and the data in the aggregation and de-aggregation processes are inconsistent).
  • the middleware adopts the logic check method to effectively solve this problem.
  • the logic check rules are implemented in the middleware, and the wrong data can be effectively eliminated through these rules.
  • the data security of middleware mainly provides data security within the middleware and data security during the interaction with existing systems.
  • the middleware uses user access authentication, data transmission authentication, and uses secure data channels to transmit data. Thereby ensuring the security of the data interaction process.
  • step S11 the long-distance and fast RFID technology is used to realize the framework structure of rapid data acquisition and positioning in a small area, and corresponding solutions are proposed for some key problems in the system.
  • the middleware is used as the basic model of data collection. Middleware can be well integrated with other systems. Through the accurate and automatic collection of basic data, it can realize the visual management of the container and the cargo in the container during container transportation, improve work efficiency, and reduce error rate.
  • the acquisition module may be a group of image acquisition devices and an integrated system thereof, and multiple acquisition devices are used to collect images of the container from multiple angles, so as to facilitate the complete image information of the container.
  • the tag information is read through the reading module and the location information of the area where the reading module is located is associated with the read tag information, so as to achieve the purpose of obtaining the location of the container, and the characteristic information of the container is collected through the collection module.
  • the image information of the container is associated with the current position information of the container and the corresponding label information, so as to obtain all the information of the container in the preset area.
  • the two-dimensional image collected by the collection module is converted into a three-dimensional image in order to identify the size and type of the container.
  • step S2 described with reference to FIG. 3 generates stereo feature information based on the feature information, including:
  • the characteristic information includes at least two images
  • passive distance sensing technology can be used to obtain the distance between the collection module and the target object, and the size data of the target object can be calculated based on the distance; active depth sensing can also be used to obtain the distance between the collection module and the target object. The distance between the target object is calculated based on the distance.
  • Active depth sensing methods can include TOF (Time of Flight), structured light, laser scanning, etc.
  • matching the three-dimensional feature information with preset reference information to obtain damage information includes:
  • the preset reference information includes reference image information of multiple size types
  • the similarity comparison method may use an image perception algorithm (pHash algorithm).
  • An image perception algorithm is used to generate a "fingerprint" string for each picture, and the reference fingerprint string of the reference image information is compared with the fingerprint string of the target object. The closer the comparison result is, the more similar the picture is.
  • the process of comparing each picture in the stereo feature information with each reference picture in the reference image information using an image perception algorithm is:
  • Reduced size Reduce the image to a size of 8 ⁇ 8, a total of 64 pixels. By reducing the size, the details of the image can be removed, and only basic information such as structure/shading is retained, and image differences caused by different sizes/proportions are discarded;
  • Simplified color Convert the reduced image to 64-level grayscale, that is, there are only 64 colors for all pixels;
  • Compare the grayscale of the pixels compare the grayscale of each pixel with the average value. If it is greater than or equal to the average value, it is recorded as 1, and if it is less than the average value, it is recorded as 0;
  • the order of the processing process is not limited, as long as all images are in the same order; after the fingerprint is obtained, different images can be compared and different numbers of 64 bits can be obtained. In theory, this is equivalent to "Hamming distance" (In information theory, the Hamming distance between two strings of equal length is the number of different characters at the corresponding positions of the two strings). If the number of different data bits does not exceed 5, it means that the two images are very similar; if it is greater than 10, it means that they are two different images.
  • step S33 Determine whether the comparison value is greater than the comparison threshold, if yes, go to step S34; if not, go back to step S1;
  • the comparison threshold can be set as needed, which is equivalent to "Hamming distance” (Hamming distance, in information theory, the Hamming distance between two strings of equal length is the corresponding position of the two strings The number of different characters). If the number of different data bits does not exceed 5, it means that the two images are very similar; if it is greater than the contrast threshold (such as: 10), it means that they are two different images.
  • Himming distance in information theory, the Hamming distance between two strings of equal length is the corresponding position of the two strings The number of different characters. If the number of different data bits does not exceed 5, it means that the two images are very similar; if it is greater than the contrast threshold (such as: 10), it means that they are two different images.
  • step S4 encrypting the damaged information to generate damaged evidence data includes:
  • the damage information, the label information, and the corresponding location information of the target object are combined, a digital signature is added, and the damage evidence data is encrypted to generate the damage evidence data.
  • the digital signature may use any one of RSA, DSA, or ECDSA.
  • Digital signature its function is actually the same as handwritten signature. It is used to prove that a certain message or file is sent/approved by the person. It uses a public key encryption system to ensure two characteristics of non-forgery and non-repudiation.
  • RSA is mainly for the decomposition of large integers
  • DSA is mainly for the discrete logarithm problem
  • ECDSA which is a variant of DSA, is mainly for the discrete logarithm problem on the elliptic curve.
  • the server sends the RSA signature process as follows: the server publishes the public key and declares that the corresponding private key is in its hands; the server calculates the digest of the message M to obtain the digest D; the server uses the private key to sign D , Get the signature S; send M and S together; the client verifies the RSA signature process: the client first uses the same digest algorithm as the server to calculate the digest for M, and obtains the digest D; uses the server public key to unsign S, Get the digest D'; if D and D'are the same, it proves that M is indeed sent by the server and has not been tampered with.
  • the damaged evidence extraction method can process the collected feature information of the target object to generate stereo feature information, and then determine whether the target object is damaged by matching the stereo feature information with preset reference information. Obtain the corresponding damage information and encrypt it, generate damage evidence data, and provide reliable damage evidence for insurance claims.
  • the damage evidence extraction method is based on image technology to solve the problem of damage identification of the container to a large extent, and improve the applicability of the electronic evidence data device. This program belongs to the field of smart logistics, and the construction of smart cities can be promoted through this program.
  • a device 1 for extracting damage evidence of this embodiment includes: an acquisition unit 11, a generation unit 12, a matching unit 13, and an acquisition unit 14; wherein,
  • the collecting unit 11 is used to collect characteristic information of the target object
  • Tag is configured on the target object.
  • the target object is used to refer to a container.
  • the tag installed on the container is a high-frequency, active tag.
  • the tag includes sleep mode and working mode. When the tag is not triggered, the tag is in sleep mode; when the tag enters the reading area, it is in sleep mode. Switch to working mode and send tag information for the reader module to read the tag information, or the reader module can write the corresponding information into the tag.
  • the switch between sleep mode and working mode can effectively save the energy of the label, usually the label can work for ten years.
  • the collection unit 11 reads the tag information of the target object in a preset area through a reading module, and the preset area corresponds to the position information;
  • the position information of the reading module can be obtained by setting a GPS positioning module on the reading module.
  • the position of the reading module is fixed, and a positioning module can be configured on the reading module to obtain the position information of the preset area; the reading module can be a reader.
  • the effective reading distance between the tag and the reader can reach 100m, and the reader can read the tag information on objects moving at a high speed (such as 120km/h).
  • Reading the tag information of the target object is mainly used in a preset area (a small area), and the location information can be static or dynamic.
  • the collection of dynamic position information (such as the entrance and exit and the position when moving in a certain area) is relatively simple.
  • the location of the Reader is used to determine the location of the container.
  • the static position is mainly to obtain the plane coordinate position and the three-dimensional coordinate position (in order to save space, the containers are generally placed in a stacked manner).
  • the status information of the container can be written into the tag through the reader.
  • the status information can include aggregated information and de-aggregated information.
  • Aggregated information refers to the process of loading goods; de-aggregated information is the process of unloading goods from the container.
  • Aggregated information is mainly to use barcode technology to package items, then add tags or barcodes on the packaging boxes, and then put the boxes with added tags or barcodes into the container, and add active tags to the container.
  • RFID radio frequency
  • the information loaded on each cargo can be sent to the data server through a barcode reader and an RFID reader through a wired or wireless manner, and then the data server compares the loaded cargo information with the basic information of the container (such as arrival station, departure station, arrival time, etc.), after confirming that it is correct through comparison, write the data of this operation to the tag.
  • the data server can also send confirmation information to the operator's handheld device, and write data to the tag after the operator's confirmation.
  • Aggregation and de-aggregation operations are very important for LCL operations. LCL is the assembly of multiple customer goods in one box. It is easy to mistakenly load the goods in one box to another, resulting in loss of goods or wrong submission Condition. The use of aggregation and de-aggregation operations can effectively solve this problem.
  • Data collision refers to the simultaneous arrival of multiple radio frequency signals in the recognition area of the reader. It will respond to the commands of the reader and send signals to the reader at the same time, causing channel contention problems, signal interference with each other, leading to reading The device cannot correctly identify the data in the electronic tag, that is, a collision has occurred.
  • Tag collision and Reader collision There are two main types of data collision: Tag collision and Reader collision.
  • the time domain method (deterministic algorithm and uncertainty algorithm) can be adopted.
  • the uncertainty algorithm the tag randomly generates the response time.
  • Many uncertainty algorithms are based on the Aloha algorithm.
  • the deterministic algorithm is that the reader selects different tags to respond by searching for the unique ID of the tag.
  • Binary tree search method is the simplest deterministic algorithm.
  • the Colorwave protocol uses the localized characteristics of reader and tag communication to provide a real-time, distributed, and local MAC protocol to allocate communication frequencies and time slots for readers to reduce interference between readers. This method can greatly increase the communication load of the system. Data security is to prevent the reading equipment of other systems from reading or changing the information in the RFID Tag on the container.
  • middleware In order to prevent data leakage (such as: reading equipment of other systems to read or modify the information in the RFID Tag on the container), physical isolation, stop tag services, read access control, and dual-tag joint verification (yoking-proof) can be used Law. These methods are all implemented based on hardware.
  • middleware is used to realize the basic data collection of the container and its cargo.
  • RFID hardware can effectively solve the data collision and safety problems. Therefore, the middleware mainly solves: (1) the safety of the middleware itself and Data security issues in the process of interacting with existing systems; (2) Basic data reliability issues, including data redundancy and data errors.
  • the problem of data redundancy is that a tag (container) passes through the reading area for many times or stays in the reading area for a long time without any changes, causing the reader to obtain repeated data multiple times.
  • a combination of two mechanisms is used: data filtering and controlled reading.
  • Data filtering is to filter the data of the same label in the same time period, and the filtering processing operation is implemented in the local middleware.
  • the data filtering technology does not reduce the number of times to read RFID Tag.
  • RFID Tag will consume energy due to multiple readings and reduce the service life of RFID Tag.
  • the local data center can control the landmark to send a reading trigger signal within a certain time interval (for example, once every ten minutes). This can effectively save the energy of the tag and increase the service life of the tag.
  • Data error refers to the wrong data obtained during the basic data reading process (for example, the data is read when it should not be read, and the data in the aggregation and de-aggregation processes are inconsistent).
  • the middleware adopts the logic check method to effectively solve this problem.
  • the logic check rules are implemented in the middleware, and the wrong data can be effectively eliminated through these rules.
  • the data security of middleware mainly provides data security within the middleware and data security during the interaction with existing systems.
  • the middleware uses user access authentication, data transmission authentication, and uses secure data channels to transmit data. Thereby ensuring the security of the data interaction process.
  • the collection unit 11 can use long-distance, fast RFID technology to realize the framework structure of rapid data acquisition and positioning in a small area, and proposes corresponding solutions to some key problems in the system, and uses middleware as the basic model of data collection.
  • Middleware can be well integrated with other systems. Through the accurate and automatic collection of basic data, it can realize the visual management of the container and the cargo in the container during container transportation, improve work efficiency, and reduce error rate.
  • the collecting unit 11 collects the characteristic information of the target object in the corresponding preset area through the collecting module;
  • the acquisition module may be a group of image acquisition devices and an integrated system thereof, and multiple acquisition devices are used to collect images of the container from multiple angles, so as to facilitate the complete image information of the container.
  • the collection unit 11 is further configured to associate the characteristic information of the target object with the tag information and the corresponding position information.
  • the collection unit 11 reads the tag information through the reading module and associates the location information of the area where the reading module is located with the read tag information, so as to achieve the purpose of obtaining the location of the container.
  • the image information of the container is associated with the current position information of the container and the corresponding label information, so as to obtain all the information of the container in the preset area.
  • the generating unit 12 is configured to generate stereo feature information based on the feature information
  • the two-dimensional image collected by the collection module is converted into a three-dimensional image in order to identify the size and type of the container.
  • the feature information includes at least two images; the generating unit 12 calculates the size data of the target object according to the at least two images in the feature information; generates the size data of the target object according to the size data and the image Three-dimensional feature information, where the three-dimensional feature information includes the size data.
  • passive distance sensing technology can be used to obtain the distance between the collection module and the target object, and the size data of the target object can be calculated based on the distance; active depth sensing can also be used to obtain the distance between the collection module and the target object. The distance between the target object is calculated based on the distance.
  • Active depth sensing methods can include TOF (Time of Flight), structured light, laser scanning, etc.
  • the matching unit 13 is configured to match the stereo feature information with preset reference information to obtain damage information
  • the preset reference information includes reference image information of multiple size types
  • the matching unit 13 selects the reference image information of the size type corresponding to the size data according to the size data in the three-dimensional feature information; uses a similarity comparison method to compare the three-dimensional feature information with the reference image information Perform comparison and obtain the comparison value;
  • the similarity comparison method may use an image perception algorithm (pHash algorithm).
  • An image perception algorithm is used to generate a "fingerprint" string for each picture, and the reference fingerprint string of the reference image information is compared with the fingerprint string of the target object. The closer the comparison result is, the more similar the picture is.
  • the matching unit 13 is also used to determine whether the comparison value is greater than the comparison threshold, and when the comparison value is greater than the comparison threshold, the feature information corresponding to the stereo feature information is used as the damage information.
  • the acquiring unit 14 is configured to encrypt the damaged information to generate damaged evidence data.
  • the acquiring unit 14 combines the damaged information, the label information, and the corresponding location information of the target object, adds a digital signature, and performs encryption to generate the damaged evidence data.
  • the digital signature may use any one of RSA, DSA, or ECDSA.
  • Digital signature its function is actually the same as handwritten signature. It is used to prove that a certain message or file is sent/approved by the person. It uses a public key encryption system to ensure two characteristics of non-forgery and non-repudiation.
  • RSA is mainly for the decomposition of large integers
  • DSA is mainly for the discrete logarithm problem
  • ECDSA which is a variant of DSA, is mainly for the discrete logarithm problem on the elliptic curve.
  • the server sends the RSA signature process as follows: the server publishes the public key and declares that the corresponding private key is in its hands; the server calculates the digest of the message M to obtain the digest D; the server uses the private key to sign D , Get the signature S; send M and S together; the client verifies the RSA signature process: the client first uses the same digest algorithm as the server to calculate the digest for M, and obtains the digest D; uses the server public key to unsign S, Get the digest D'; if D and D'are the same, it proves that M is indeed sent by the server and has not been tampered with.
  • the damage evidence extraction device 1 can process the collected feature information of the target object to generate three-dimensional feature information, and then determine whether the target object is damaged by matching the three-dimensional feature information with preset reference information. Then obtain the corresponding damage information and encrypt it, generate damage evidence data, and provide reliable damage evidence for insurance claims.
  • the damage evidence extraction device 1 is based on image technology to solve the problem of the damage identification of the container to a large extent, and improves the applicability of the electronic evidence data device.
  • the present application also provides a computer device 2 which includes a plurality of computer devices 2.
  • the components of the damaged evidence extraction device 1 of the second embodiment can be dispersed in different computer devices 2.
  • the computer device 2 It can be a smart phone, a tablet, a laptop, a desktop computer, a rack server, a blade server, a tower server, or a cabinet server (including independent servers, or server clusters composed of multiple servers) that executes the program Wait.
  • the computer device 2 in this embodiment at least includes but is not limited to: a memory 21, a processor 23, a network interface 22, and a damaged evidence extraction device 1 (refer to FIG. 6) that can be communicatively connected to each other through a system bus.
  • FIG. 6 only shows the computer device 2 with components, but it should be understood that it is not required to implement all the illustrated components, and more or fewer components may be implemented instead.
  • the memory 21 includes at least one type of computer-readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access Memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disks, optical disks, etc.
  • the memory 21 may be an internal storage unit of the computer device 2, for example, a hard disk or a memory of the computer device 2.
  • the memory 21 may also be an external storage device of the computer device 2, for example, a plug-in hard disk equipped on the computer device 2, a smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, Flash Card, etc.
  • the memory 21 may also include both the internal storage unit of the computer device 2 and its external storage device.
  • the memory 21 is generally used to store the operating system and various application software installed in the computer device 2, such as the program code of the damaged evidence extraction method in the first embodiment.
  • the memory 21 can also be used to temporarily store various types of data that have been output or will be output.
  • the processor 23 may be a central processing unit (Central Processing Unit, CPU), a controller, a microcontroller, a microprocessor, or other data processing chips.
  • the processor 23 is generally used to control the overall operation of the computer device 2, for example, to perform data interaction or communication-related control and processing with the computer device 2.
  • the processor 23 is used to run the program code or process data stored in the memory 21, for example, to run the damaged evidence extraction device 1 and the like.
  • the network interface 22 may include a wireless network interface or a wired network interface, and the network interface 22 is generally used to establish a communication connection between the computer device 2 and other computer devices 2.
  • the network interface 22 is used to connect the computer device 2 with an external terminal through a network, and establish a data transmission channel and a communication connection between the computer device 2 and the external terminal.
  • the network may be an intranet (Intranet), the Internet (Internet), a global system of mobile communication (GSM), and wideband code division multiple access (Wideband Code). Division Multiple Access, WCDMA), 4G network, 5G network, Bluetooth (Bluetooth), Wi-Fi and other wireless or wired networks.
  • FIG. 6 only shows the computer device 2 with components 21-23, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead.
  • the damaged evidence extraction device 1 stored in the memory 21 can also be divided into one or more program modules, and the one or more program modules are stored in the memory 21 and are composed of one or more program modules.
  • a plurality of processors are executed to complete the application.
  • this application also provides a computer-readable storage medium, which includes multiple storage media, such as flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM ), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disks, optical disks, servers, App applications Shopping malls, etc., have computer-readable instructions stored thereon, and corresponding functions are realized when the programs are executed by the processor 23.
  • the computer-readable storage medium of this embodiment is used to store the damage evidence extraction device 1, and the computer-readable storage medium implements the damage evidence extraction method of the first embodiment when executed by the processor 23.
  • the computer-readable storage medium may be non-volatile or volatile.

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Abstract

La présente invention concerne le domaine technique des informations, et sont décrits ici un procédé et un appareil d'extraction de preuve d'endommagement, un dispositif informatique et un support de stockage qui sont appliqués au domaine de la logistique intelligente dans des villes intelligentes. Dans le procédé et l'appareil d'extraction de preuve d'endommagement, le dispositif informatique et le support de stockage selon la présente invention, des informations de caractéristiques collectées d'objet cible peuvent être traitées afin de générer des informations de caractéristiques tridimensionnelles, et la mise en correspondance des informations de caractéristiques tridimensionnelles avec des informations de référence prédéfinies permet de déterminer si l'objet cible est endommagé ou non; et si tel est le cas, les informations d'endommagement correspondantes sont acquises et chiffrées afin de générer des données de preuve d'endommagement, et fournir ainsi une preuve d'endommagement fiable pour des déclarations de sinistre.
PCT/CN2020/103839 2020-04-30 2020-07-23 Procédé et appareil d'extraction de preuve d'endommagement, dispositif informatique et support de stockage WO2021217914A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114723689A (zh) * 2022-03-25 2022-07-08 盛视科技股份有限公司 一种集装箱箱体残损检测方法

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115904263B (zh) * 2023-03-10 2023-05-23 浪潮电子信息产业股份有限公司 一种数据迁移方法、系统、设备及计算机可读存储介质

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102033070A (zh) * 2009-09-24 2011-04-27 宁波中科集成电路设计中心有限公司 一种集装箱破损监测系统
CN107274121A (zh) * 2017-05-25 2017-10-20 上海撬动网络科技有限公司 无固定场地集装箱检验系统
US20180144286A1 (en) * 2014-05-02 2018-05-24 Google Llc Machine-readable delivery platform for automated package delivery
CN110954546A (zh) * 2019-12-20 2020-04-03 上海撬动网络科技有限公司 一种非固定场景的集装箱图像采集和验视系统
CN210534787U (zh) * 2019-10-30 2020-05-15 重庆仙桃前沿消费行为大数据有限公司 物流智能信息采集装置

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018019373A (ja) * 2016-07-29 2018-02-01 パナソニックＩｐマネジメント株式会社 監視カメラ及び荷物読取方法
CN208420046U (zh) * 2018-05-25 2019-01-22 深圳市深触科技有限公司 一种获取货物信息的设备

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102033070A (zh) * 2009-09-24 2011-04-27 宁波中科集成电路设计中心有限公司 一种集装箱破损监测系统
US20180144286A1 (en) * 2014-05-02 2018-05-24 Google Llc Machine-readable delivery platform for automated package delivery
CN107274121A (zh) * 2017-05-25 2017-10-20 上海撬动网络科技有限公司 无固定场地集装箱检验系统
CN210534787U (zh) * 2019-10-30 2020-05-15 重庆仙桃前沿消费行为大数据有限公司 物流智能信息采集装置
CN110954546A (zh) * 2019-12-20 2020-04-03 上海撬动网络科技有限公司 一种非固定场景的集装箱图像采集和验视系统

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114723689A (zh) * 2022-03-25 2022-07-08 盛视科技股份有限公司 一种集装箱箱体残损检测方法

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