A monitoring method, device and medium for improving grain depot safety based on blockchain

Abstract

The embodiments of this specification disclose a monitoring method, device and medium for improving the safety of grain depots based on blockchain, the method comprising: establishing a corresponding relationship between each intelligent monitoring terminal and a grain depot to be monitored according to terminal identifications of multiple intelligent monitoring terminals and location information of multiple grain depots to be monitored; encrypting the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored to generate multiple corresponding first identification codes, sending the multiple first identification codes to the blockchain technology platform for data storage, collecting grain depot videos of the grain depot to be monitored in real time through the intelligent monitoring terminal, encrypting the corresponding relationship between the grain depot video and the grain depot to be monitored to generate a second identification code, sending the second identification code and the grain depot video to the blockchain technology platform for data storage, and verifying the video source of the grain depot video according to the first identification code and the second identification code; if the verification is passed, the grain depot to be monitored is monitored, avoiding the problem of unreliable monitoring data.

Description

Technical Field

[0001] This specification relates to the field of blockchain technology, and in particular to a monitoring method, device and medium for improving grain storage safety based on blockchain. Background Art

[0002] In order to better manage food security issues, the trend of combining grain depot monitoring and computer technology is becoming more and more obvious. Remote monitoring has also been widely used in grain depot security. The remote monitoring system can monitor the working conditions of some important places in the grain depot in real time, which not only reduces on-site inspections and the cost of manual management of grain depots, but also facilitates the management and data collection of grain storage work.

[0003] In the existing grain depot supervision field, multiple grain depots are often monitored simultaneously by remotely acquiring surveillance videos. The remote intelligent data collection devices are easily replaced or tampered with, which affects the security of the acquired surveillance videos. In addition, the surveillance videos collected by the acquisition devices that have been replaced manually cannot represent the true status of the grain depot, resulting in erroneous monitoring and unreliable monitoring data. Summary of the invention

[0004] One or more embodiments of this specification provide a blockchain-based monitoring method, device and medium for improving grain warehouse safety, which is used to solve the following technical problems: remote intelligent collection devices are easily replaced or tampered with, resulting in erroneous monitoring and unreliable monitoring data.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a monitoring method for improving the safety of grain depots based on blockchain, which is applied to a grain depot intelligent monitoring system, wherein the grain depot intelligent monitoring system includes a blockchain technology platform and multiple intelligent monitoring terminals, and the method includes: establishing a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored according to the terminal identification of the multiple intelligent monitoring terminals and the location information of multiple grain depots to be monitored; encrypting the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored, generating multiple corresponding first identification codes, and sending the multiple first identification codes to the blockchain technology platform for data storage, wherein the first The identification code is used to identify the unique correspondence between the intelligent monitoring terminal and the grain depot to be monitored; the grain depot video of the grain depot to be monitored is collected in real time through the intelligent monitoring terminal, the correspondence between the grain depot video and the grain depot to be monitored is encrypted, and a second identification code is generated, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique correspondence between the grain depot video and the grain depot to be monitored; according to the first identification code and the second identification code, the video source of the grain depot video is verified; if the verification passes, the grain depot to be monitored is monitored.

[0007] Furthermore, the grain depot intelligent monitoring system includes a plurality of abnormal movement sensors, and the abnormal movement sensors are installed on the intelligent monitoring terminal; before the grain depot video of the grain depot to be monitored is collected by the intelligent monitoring terminal, the method also includes: monitoring the abnormal movement data of the intelligent monitoring terminal in real time by the abnormal movement sensor, and obtaining the latest position data of the intelligent monitoring terminal according to the abnormal movement data; determining the current grain depot where the intelligent monitoring terminal is located according to the latest position data of the intelligent monitoring terminal; generating a corresponding relationship between the location information of the current grain depot and the intelligent monitoring terminal; encrypting the corresponding relationship between the intelligent monitoring terminal and the current grain depot according to the identification key of the intelligent monitoring terminal, generating a corresponding third identification code, and sending the third identification code to the blockchain technology platform; verifying the correctness of the third identification code according to the first identification code, if the third identification code does not match the first identification code, it is determined that the position of the intelligent monitoring terminal has changed without passing the correctness verification; if the position of the intelligent monitoring terminal has changed, the operation of shielding the collection of grain depot video is performed on the intelligent monitoring terminal.

[0008] Furthermore, the verification of the grain depot video according to the first identification code and the second identification code specifically includes: determining a current identification code corresponding to the grain depot to be monitored among the multiple first identification codes; parsing the current identification code through the blockchain technology platform to obtain a current intelligent monitoring terminal corresponding to the current identification code; parsing the second identification code through the blockchain technology platform to obtain the grain depot video corresponding to the second identification code; judging whether the designated intelligent terminal corresponding to the grain depot video is consistent with the current intelligent monitoring terminal through the video acquisition parameters of the current intelligent terminal and the video parameters of the grain depot video; if the designated intelligent terminal is consistent with the current intelligent monitoring terminal, the verification of the grain depot video is passed.

[0009] Further, the monitoring of the grain depot to be monitored based on the grain depot video specifically includes: converting the grain depot video into a grain depot image sequence, wherein the grain depot image sequence includes multiple grain depot images and time data corresponding to the grain depot images; performing image feature extraction on the multiple grain depot images, and dividing the grain depot images into a first category of grain depot images and a second category of grain depot images according to the extracted image features, wherein the first category of grain depot images include human features, and the second category of grain depot images do not include human features; performing image deduplication on the first category of grain depot images, removing the same grain depot images at adjacent moments in the first category of grain depot images, and obtaining multiple designated grain depot images in the first category of grain depot images; and performing image deduplication on the second category of grain depot images, removing the same grain depot images at adjacent moments in the second category of grain depot images, and obtaining multiple preset grain depot images in the second category of grain depot images; monitoring the man-made hidden dangers in the grain depot to be monitored through the multiple designated grain depot images; and monitoring the environmental hidden dangers in the grain depot to be monitored through the multiple preset grain depot images.

[0010] Furthermore, the environmental hazards of the grain depot to be monitored are monitored through the multiple preset grain depot images, specifically including: calculating the values ​​of the R channel, the G channel and the B channel at each pixel in each preset grain depot image; merging the multiple preset grain depot images into an environmental hazard monitoring image according to the average value of the R channel, the average value of the G channel and the average value of the B channel of each pixel in all the preset grain depot images; inputting the environmental hazard monitoring image into a pre-trained temperature detection model, so that the temperature detection model outputs the detected temperature of each pixel according to the three-channel ratio of each pixel in the environmental hazard monitoring image, wherein the three-channel ratio of each pixel includes the ratio of the R channel to the G channel, the ratio of the R channel to the B channel, and the ratio of the G channel to the B channel; determining the temperature at each position in the grain depot to be monitored according to the detected temperature of each pixel, and monitoring the temperature in the grain depot to be monitored.

[0011] Furthermore, the man-made hidden dangers in the grain depot to be monitored are monitored through the multiple designated grain depot images, specifically including: pre-constructing a behavior feature library of man-made hidden dangers; extracting human features in the multiple designated grain depot images to obtain multiple body movement features; generating corresponding behavior videos according to the body movement features according to the time data of the multiple designated grain depot images; extracting behavior features in the behavior videos, and comparing them with the features in the behavior feature library to identify whether the behavior of the human figure belongs to hidden danger behavior, so as to realize the monitoring of the man-made hidden dangers in the grain depot to be monitored.

[0012] Furthermore, the human figure features also include facial features, and the behavior of identifying the human figure is a hidden danger behavior. After that, the method also includes: collecting facial information of the person in charge of the grain depot to be monitored through the intelligent monitoring terminal in advance, and uploading it to the blockchain technology platform; extracting the facial features of the person in charge of the facial information of the person in charge, and saving it to the behavior feature library; comparing the facial features of the human figure with the facial features of the person in charge, and identifying the human figure; if the human figure is the person in charge of the grain depot to be monitored, generating early warning information and sending it to the management node, and issuing a hidden danger warning to the regulatory department; if the human figure is not the person in charge of the grain depot to be monitored, generating early warning information and sending it to the corresponding intelligent monitoring terminal for hidden danger warning.

[0013] Furthermore, after monitoring the grain depot to be monitored, the method further includes: when performing a traceability query on the grain depot monitoring data, obtaining all grain depot videos of the grain depot to be monitored collected by the intelligent monitoring terminal through the second identification code for traceability.

[0014] One or more embodiments of this specification provide a monitoring device for improving grain depot safety based on blockchain, including:

[0015] at least one processor; and,

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: establish a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored according to the terminal identifications of the multiple intelligent monitoring terminals and the location information of the multiple grain depots to be monitored; encrypt the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored, generate corresponding multiple first identification codes, and send the multiple first identification codes to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; collect the grain depot video of the grain depot to be monitored in real time through the intelligent monitoring terminal, encrypt the corresponding relationship between the grain depot video and the grain depot to be monitored, generate a second identification code, and send the second identification code and the grain depot video to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; verify the video source of the grain depot video according to the first identification code and the second identification code; if the verification passes, monitor the grain depot to be monitored. One or more embodiments of this specification provide a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to:

[0018] According to the terminal identifications of the multiple intelligent monitoring terminals and the location information of the multiple grain depots to be monitored, a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is established; the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is encrypted to generate a corresponding multiple first identification codes, and the multiple first identification codes are sent to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; the grain depot video of the grain depot to be monitored is collected in real time by the intelligent monitoring terminal, the corresponding relationship between the grain depot video and the grain depot to be monitored is encrypted to generate a second identification code, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; according to the first identification code and the second identification code, the video source of the grain depot video is verified; if the verification passes, the grain depot to be monitored is monitored. At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects: by setting the first representation code, a one-to-one correspondence between the intelligent monitoring terminal and the grain depot is determined, and the first identification code is uploaded to the blockchain technology platform. With the help of the anti-tampering feature of the blockchain technology, the grain depot and the monitoring terminal are intelligently and uniquely bound to prevent hidden changes caused by system problems, human operations and other factors; according to the correspondence between the grain depot video and the grain depot and the first identification code, the grain depot video is verified to improve the validity of the grain depot video and the credibility of the grain video, which is helpful for effective supervision of the grain depot and avoids problems such as erroneous monitoring and unreliable monitoring data when the intelligent monitoring terminal is replaced and tampered with. Based on the intelligent monitoring terminal and the blockchain technology platform, the intelligent supervision of the grain depot is realized, the accuracy of the supervision of the grain depot is improved, and errors in the process data caused by human factors and non-human factors are prevented. At the same time, through the decentralized technology of blockchain, it can be traced and checked globally to ensure the accuracy of the data reported in the grain depot storage process. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0020] Figure 1 An application scenario diagram of a monitoring method for improving grain depot safety based on blockchain provided in an embodiment of this specification;

[0021] Figure 2A flowchart of a monitoring method for improving grain depot safety based on blockchain provided in an embodiment of this specification;

[0022] Figure 3 A schematic diagram of the structure of a monitoring device for improving grain storage safety based on blockchain provided in an embodiment of this specification. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0024] In order to better manage food security issues, the trend of combining grain depot monitoring and computer technology is becoming more and more obvious. Remote monitoring has also been widely used in grain depot security. The remote monitoring system can monitor the working conditions of some important places in the grain depot in real time, which not only reduces on-site inspections and the cost of manual management of grain depots, but also facilitates the management and data collection of grain storage work.

[0025] In the existing grain depot supervision field, multiple grain depots are often monitored simultaneously by remotely acquiring surveillance videos. The remote intelligent data collection devices are easily replaced or tampered with, which affects the security of the acquired surveillance videos. In addition, the surveillance videos collected by the acquisition devices that have been replaced manually cannot represent the current status of the grain depot, resulting in erroneous monitoring and unreliable monitoring data.

[0026] The embodiment of this specification provides a monitoring method for improving the safety of grain depots based on blockchain, which is applied to the intelligent monitoring system of grain depots. The intelligent monitoring system of grain depots includes a blockchain technology platform and multiple intelligent monitoring terminals, wherein the multiple intelligent monitoring terminals are respectively arranged in different grain depots. The blockchain technology platform includes a plurality of blockchain nodes, wherein the plurality of management nodes can be management nodes or service nodes corresponding to the plurality of intelligent monitoring terminals. The service nodes can upload data to the blockchain, and the grain depot managers can read the uploaded data of the service nodes through the management nodes for subsequent data processing. The specific application scenario schematic diagram is shown as follows: Figure 1 As shown, the method provided in the embodiments of this specification can be applied to grain depots in a certain area or to grain depots in multiple areas. Figure 2A flowchart of a monitoring method for improving grain depot safety based on blockchain provided in the embodiments of this specification, the execution subject can be a server, or any processing device or equipment with data processing capabilities, such as Figure 2 As shown, the method mainly includes the following steps:

[0027] Step S201, establishing a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored according to the terminal identifications of the plurality of intelligent monitoring terminals and the location information of the plurality of grain depots to be monitored.

[0028] When it is necessary to monitor a grain depot, an intelligent monitoring terminal is usually set in each grain depot. In one embodiment of the present specification, when an intelligent terminal is set in each grain depot, a terminal identifier is set for each intelligent terminal, and a corresponding relationship is established based on the terminal identifier of the intelligent monitoring terminal and the position relationship of the grain depot. For example, if the intelligent monitoring terminal A monitors the first grain depot in the first row (referred to as grain depot No. 1), then a corresponding relationship between the intelligent monitoring terminal A and grain depot No. 1 is established. Similarly, a corresponding relationship between each intelligent monitoring terminal and all grain depots to be monitored is established according to the above method.

[0029] Step S202: Encrypt the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored, generate corresponding multiple first identification codes, and send the multiple first identification codes to the blockchain technology platform for data storage.

[0030] In one embodiment of the present specification, after the correspondence between all intelligent monitoring terminals and grain depots is established, the correspondence between each intelligent monitoring terminal and the grain depot to be monitored is encrypted, multiple corresponding first identification codes are generated, and all identification codes are sent to the blockchain technology platform for data storage. It should be noted that the first identification code is used to identify the unique correspondence between the intelligent monitoring terminal and the grain depot to be monitored.

[0031] In addition, the identification code can be a barcode, a QR code, or an encrypted string. The intelligent monitoring terminal is equipped with an active identification chip, which supports a variety of encryption algorithm modules and covers the international mainstream encryption algorithms while supporting the national encryption algorithm, including symmetric algorithms, asymmetric algorithms and digest algorithms.

[0032] In one embodiment of the present specification, the first identification code is uploaded to the blockchain technology platform, and with the help of the anti-tampering feature of the blockchain technology, the grain depot and the monitoring terminal are intelligently and uniquely bound to prevent hidden changes caused by system problems, human operations and other factors.

[0033] In one embodiment of the present specification, the intelligent monitoring terminal includes an abnormal movement sensor, which monitors the abnormal movement data of the intelligent monitoring terminal in real time through the abnormal movement sensor, and obtains the latest position data of the intelligent monitoring terminal according to the abnormal movement data. The abnormal movement sensor can monitor the position change of the intelligent monitoring terminal in real time. According to the latest position data of the intelligent monitoring terminal, the current grain depot where the intelligent monitoring terminal is located is determined, and the corresponding relationship between the location information of the current grain depot and the intelligent monitoring terminal is generated. According to the identification key of the intelligent monitoring terminal, the corresponding relationship between the intelligent monitoring terminal and the current grain depot is encrypted, and the corresponding third identification code is generated, and the third identification code is sent to the blockchain technology platform. After that, according to the first identification code pre-stored in the blockchain technology platform, the third identification code is verified for correctness. If the correctness verification fails, it is determined that the position of the intelligent monitoring terminal has changed. Once the position changes, it means that the video collected by the terminal is unreliable. Therefore, the operation of shielding the video of the grain depot can be performed on the intelligent monitoring terminal, and an early warning is issued to inform the on-site staff to check. Through the above technical solution, the anti-tampering function of the intelligent monitoring terminal is guaranteed.

[0034] Step S203, collect the grain warehouse video of the grain warehouse to be monitored in real time through the intelligent monitoring terminal, encrypt the correspondence between the grain warehouse video and the grain warehouse to be monitored, generate a second identification code, and send the second identification code and the grain warehouse video to the blockchain technology platform for data storage.

[0035] In one embodiment of the present specification, the intelligent monitoring terminal also includes a video acquisition device, such as a camera, which collects the grain warehouse video of the grain warehouse to be monitored in real time through the video acquisition device, binds the collected grain warehouse video and the grain warehouse to be monitored, encrypts the correspondence between the two, and generates a second identification code, wherein the second identification code is used to identify the unique correspondence between the grain warehouse video and the grain warehouse to be monitored; and sends the second identification code to the blockchain technology platform for data storage, thereby ensuring the unique correspondence between the grain warehouse video and the grain warehouse to be monitored.

[0036] In one embodiment of the present specification, when tracing grain depot data, all grain depot videos of the grain depot to be monitored collected by the intelligent monitoring terminal can be obtained through the second identification code for tracing. The non-tamperable and non-forgeable nature of block technology ensures the accuracy of all grain depot videos, and grain depot data can be obtained using grain depot videos to trace food safety issues.

[0037] Step S204, verifying the video source of the grain warehouse video according to the first identification code and the second identification code.

[0038] During the video acquisition process, if the intelligent monitoring terminal is replaced or tampered with manually, the obtained grain warehouse video will not correspond to the grain warehouse, and the grain warehouse cannot be monitored through the grain warehouse video.

[0039] In one embodiment of the present specification, according to the grain depot to be monitored corresponding to the grain depot video, the current identification code corresponding to the grain depot to be monitored is determined from multiple first identification codes, and the current identification code is parsed through the blockchain technology platform to obtain the current intelligent monitoring terminal in the current identification code. Afterwards, the second identification code is parsed through the blockchain technology platform to obtain the grain depot video in the second identification code, and through the video acquisition parameters of the current intelligent terminal and the video parameters of the grain depot video, it is determined whether the designated intelligent terminal corresponding to the grain depot video is consistent with the current intelligent monitoring terminal. If the designated intelligent terminal is consistent with the current intelligent monitoring terminal, the video source verification of the grain depot video is passed.

[0040] The following example illustrates that, for example, under normal circumstances, grain depot No. 1 is monitored through terminal A, that is, terminal A and grain depot No. 1 are in a one-to-one correspondence. However, terminal A is replaced, and terminal B monitors grain depot No. 1. In this case, the grain depot video collected by terminal A is not the video of grain depot No. 1, and continuing to monitor the grain depot video will not achieve the purpose of monitoring grain depot No. 1. Therefore, when the grain depot video is received, according to the correspondence between the grain depot video and the grain depot, that is, the grain depot video corresponds to grain depot No. 1, the correspondence between grain depot No. 1 and terminal A is obtained from the pre-stored multiple first identification codes, that is, the current identification code, and the current identification code is parsed to obtain terminal A in the current identification code as the current intelligent monitoring terminal. The second identification code is parsed through the blockchain technology platform, and the monitoring video is obtained as video B. Since video B is collected by terminal B, the video parameters corresponding to video B should be the video collection parameters of terminal B. Therefore, the video collection parameters of terminal B are inconsistent with the video collection parameters corresponding to terminal A. In other words, terminal A, which should have collected the data of Grain Depot No. 1, has been replaced. Video B cannot monitor Grain Depot No. 1, and video B is unreliable.

[0041] Through the above methods, the effectiveness of grain warehouse videos and the credibility of grain videos can be improved, which is helpful for effective supervision of grain warehouses.

[0042] Step S205: If the verification is passed, the grain depot to be monitored is monitored.

[0043] When the grain depot video is verified, the grain depot can be monitored through the blockchain technology platform. Generally, due to the large amount of grain stored in the grain depot, and the accumulation of grain and temperature changes during the storage process, the grain in the grain depot will be too hot. In addition, when strangers enter and leave the grain depot, food safety cannot be guaranteed. For example, stealing, exchanging and destroying grain are not conducive to food safety.

[0044] In one embodiment of the present specification, since the captured grain video is a continuous video, the grain depot video can be processed first to convert the grain depot video into a grain depot image sequence. It should be noted that the grain image sequence can be a plurality of grain depot images captured according to the time of the video, or each frame of the video can be regarded as a grain depot image, which is not specifically limited in the embodiment of the present specification.

[0045] In actual surveillance videos, there may be scenes that remain unchanged within a period of time, or there may be scenes of human activity when a person enters. In one embodiment of the present specification, feature extraction may be performed on multiple grain depot images respectively, and the multiple grain depot images may be divided into two categories according to whether there are human figure features. The first category of grain depot images are images corresponding to human activities, that is, the first category of grain depot images include human figure features; the second category of grain depot images are images without human activities, that is, there are no human figure features in the second category of grain depot images.

[0046] In the obtained first-category grain depot images and second-category grain depot images, there may be identical or similar grain depot images at adjacent moments. Therefore, the first-category grain depot images are deduplicated, and identical grain depot images at adjacent moments are removed from the first-category grain depot images to obtain multiple designated grain depot images in the first-category grain depot images. The second-category grain depot images are deduplicated, and identical grain depot images at adjacent moments are removed from the second-category grain depot images to obtain multiple preset grain depot images in the second-category grain depot images. Through multiple designated grain depot images, the man-made hidden dangers in the grain depot to be monitored are monitored, and through multiple preset grain depot images, the environmental hidden dangers in the grain depot to be monitored are monitored.

[0047] In one embodiment of the present specification, the values ​​of the R channel, G channel and B channel at each pixel in each preset grain warehouse image are calculated, and based on the R channel average value, G channel average value and B channel average value of each pixel in all preset grain warehouse images, multiple preset grain warehouse images are merged into one environmental hazard monitoring image.

[0048] In one embodiment of the present specification, the three-channel ratio of each pixel in the environmental hazard monitoring image is input into a pre-trained temperature detection model to output the detected temperature of each pixel, wherein the three-channel ratio of each pixel includes the ratio of the R channel to the G channel, the ratio of the R channel to the B channel, and the ratio of the G channel to the B channel. It should be noted that temperature is a function of the grayscale values ​​of the three primary colors, and the neural network has a good effect on processing complex functions that are difficult to determine by conventional methods. Therefore, the temperature detection model in the embodiment of the present specification is a BP neural network model, which is pre-set on the blockchain technology platform.

[0049] In one embodiment of the present specification, the temperature at each position in the grain warehouse to be monitored is determined based on the detected temperature of each pixel point and the positional relationship between each pixel point and the grain warehouse to be monitored, thereby achieving the purpose of monitoring the temperature in the grain warehouse to be monitored.

[0050] In one embodiment of the present specification, a behavior feature library of man-made hidden dangers is pre-constructed. For example, man-made hidden dangers may be hidden dangers such as destroying grain, stealing grain, and exchanging grain. The behavior features of destroying grain and stealing grain are pre-stored in the behavior feature library. Man-made hidden dangers are identified by specifying grain warehouse images, and human features in multiple specified grain warehouse images are extracted to obtain multiple body movement features. The body movement features are generated according to the time data of multiple specified grain warehouse images to generate corresponding behavior videos. The behavior features in the behavior video are then extracted and compared with the features in the behavior feature library to determine whether the behavior of the human figure in the video is a hidden danger behavior.

[0051] In actual application scenarios, some human behaviors may be allowed. For example, the person in charge of the grain depot can allocate a small amount of grain according to the instructions of the superior. In addition, if a man-made hidden danger occurs, the person in charge of the grain depot is generally informed through an early warning. However, if the man-made hidden danger behavior is done by the person in charge of grain, the early warning needs to be sent to the superior department in charge.

[0052] In one embodiment of the present specification, the human figure features also include facial features. The facial information of the person in charge of the grain depot to be monitored is collected in advance through the intelligent monitoring terminal and uploaded to the blockchain technology platform; the facial features of the person in charge of the facial information of the person in charge are extracted and saved in the behavior feature library; the facial features of the human figure are compared with the facial features of the person in charge to identify the human figure;

[0053] If the person in charge of the grain depot to be monitored is found to be the person in charge of the potential danger behavior of the person in charge after verification, and it is not a normal grain dispatching behavior, then an early warning message is generated and sent to the management node, and a potential danger warning is issued to the supervision department, and the behavior is warned and stopped through the supervision department. If the person in charge of the grain depot is not the person in charge of the grain depot to be monitored, an early warning message is generated and sent to the corresponding intelligent monitoring terminal, and a potential danger warning is issued, and the behavior is warned and stopped through the person in charge of the grain depot.

[0054] By setting the first identification code, the one-to-one correspondence between the intelligent monitoring terminal and the grain depot is determined, and the first identification code is uploaded to the blockchain technology platform. With the help of the anti-tampering feature of the blockchain technology, the grain depot and the monitoring terminal are intelligently and uniquely bound to prevent hidden changes caused by system problems, human operations and other factors; according to the correspondence between the grain depot video and the grain depot and the first identification code, the grain depot video is verified to improve the validity of the grain depot video and the credibility of the grain video, which is helpful to effectively supervise the grain depot and avoid the problems of erroneous monitoring and unreliable monitoring data when the intelligent monitoring terminal is replaced and tampered with. Based on the intelligent monitoring terminal and the blockchain technology platform, the intelligent supervision of the grain depot is realized, the accuracy of the supervision of the grain depot is improved, and the errors of the process data caused by human factors and non-human factors are prevented. At the same time, through the decentralized technology of blockchain, it can be traced and checked globally to ensure the accuracy of the data reported in the grain depot storage process.

[0055] The embodiment of this specification also provides a monitoring device based on blockchain to improve the safety of grain depots, such as Figure 3 As shown, the device includes:

[0056] at least one processor; and,

[0057] a memory communicatively connected to at least one processor; wherein,

[0058] The memory stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can: establish a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored according to the terminal identifications of multiple intelligent monitoring terminals and the location information of multiple grain depots to be monitored; encrypt the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored, generate corresponding multiple first identification codes, and send the multiple first identification codes to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; collect grain depot videos of the grain depot to be monitored in real time through the intelligent monitoring terminal, encrypt the corresponding relationship between the grain depot video and the grain depot to be monitored, generate a second identification code, and send the second identification code and the grain depot video to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; verify the video source of the grain depot video according to the first identification code and the second identification code; if the verification passes, monitor the grain depot to be monitored.

[0059] The embodiment of the present specification also provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0060] According to the terminal identifications of multiple intelligent monitoring terminals and the location information of multiple grain depots to be monitored, a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is established; the corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is encrypted to generate corresponding multiple first identification codes, and the multiple first identification codes are sent to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; the grain depot video of the grain depot to be monitored is collected in real time through the intelligent monitoring terminal, the corresponding relationship between the grain depot video and the grain depot to be monitored is encrypted to generate a second identification code, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; according to the first identification code and the second identification code, the video source of the grain depot video is verified; if the verification passes, the grain depot to be monitored is monitored.

[0061] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0062] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0063] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A monitoring method for improving grain depot safety based on blockchain, characterized in that: Applied to a grain depot intelligent monitoring system, the grain depot intelligent monitoring system includes a blockchain technology platform and multiple intelligent monitoring terminals, and the method includes: According to the terminal identifications of the plurality of intelligent monitoring terminals and the location information of the plurality of grain depots to be monitored, a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is established; The corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is encrypted to generate a plurality of corresponding first identification codes, and the plurality of first identification codes are sent to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; The grain depot video of the grain depot to be monitored is collected in real time through the intelligent monitoring terminal, the corresponding relationship between the grain depot video and the grain depot to be monitored is encrypted, a second identification code is generated, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; Verifying the video source of the grain depot video according to the first identification code and the second identification code; If the verification is passed, the grain depot to be monitored will be monitored.

2. According to claim 1, a monitoring method for improving grain depot safety based on blockchain is characterized in that: The grain depot intelligent monitoring system includes a plurality of abnormal movement sensors, and the abnormal movement sensors are installed on the intelligent monitoring terminal; Before collecting the grain depot video of the grain depot to be monitored by the intelligent monitoring terminal, the method further includes: Monitor the abnormal data of the intelligent monitoring terminal in real time through the abnormal data sensor, and obtain the latest location data of the intelligent monitoring terminal according to the abnormal data; Determine the current grain depot where the intelligent monitoring terminal is located according to the latest location data of the intelligent monitoring terminal; Generate a corresponding relationship between the location information of the current grain depot and the intelligent monitoring terminal; According to the identification key of the intelligent monitoring terminal, the corresponding relationship between the intelligent monitoring terminal and the current grain depot is encrypted to generate a corresponding third identification code, and the third identification code is sent to the blockchain technology platform; According to the first identification code, the third identification code is verified for correctness. If the third identification code does not match the first identification code, the correctness verification fails, and it is determined that the position of the intelligent monitoring terminal has changed. If the position of the intelligent monitoring terminal changes, the operation of shielding the collected grain depot video is performed on the intelligent monitoring terminal.

3. According to a blockchain-based monitoring method for improving grain depot safety according to claim 1, it is characterized in that: The verifying the grain depot video according to the first identification code and the second identification code specifically includes: Determining a current identification code corresponding to the grain depot to be monitored from among the plurality of first identification codes; The current identification code is parsed through the blockchain technology platform to obtain a current intelligent monitoring terminal corresponding to the current identification code; The second identification code is parsed through the blockchain technology platform to obtain the grain depot video corresponding to the second identification code; Through the video acquisition parameters of the current intelligent monitoring terminal and the video parameters of the grain warehouse video corresponding to the second identification code, it is determined whether the designated intelligent terminal corresponding to the grain warehouse video corresponding to the second identification code is consistent with the current intelligent monitoring terminal. If the designated intelligent terminal is consistent with the current intelligent monitoring terminal, the grain warehouse video is verified.

4. According to a blockchain-based monitoring method for improving grain depot safety according to claim 1, it is characterized in that: The monitoring of the grain depot to be monitored specifically includes: Converting the grain depot video into a grain depot image sequence, wherein the grain depot image sequence includes a plurality of grain depot images and time data corresponding to the grain depot images; Extracting image features from the plurality of grain depot images, and classifying the grain depot images into first-category grain depot images and second-category grain depot images according to the extracted image features, wherein the first-category grain depot images include human features, and the second-category grain depot images do not include human features; Performing image deduplication on the first-category grain depot images, removing the same grain depot images at adjacent moments from the first-category grain depot images, and obtaining a plurality of designated grain depot images in the first-category grain depot images; and performing image deduplication on the second-category grain depot images, removing the same grain depot images at adjacent moments from the second-category grain depot images, and obtaining a plurality of preset grain depot images in the second-category grain depot images; The man-made hidden dangers in the grain warehouse to be monitored are monitored through the multiple designated grain warehouse images; and the environmental hidden dangers in the grain warehouse to be monitored are monitored through the multiple preset grain warehouse images.

5. According to claim 4, a monitoring method for improving grain depot safety based on blockchain is characterized in that: The monitoring of the environmental hazards of the grain depot to be monitored by using the plurality of preset grain depot images specifically includes: Calculate the values ​​of the R channel, G channel, and B channel at each pixel in each preset grain depot image; According to the R channel average value, the G channel average value and the B channel average value of each pixel point in all the preset grain depot images, the plurality of preset grain depot images are merged into one environmental hazard monitoring image; Input the environmental hazard monitoring image into a pre-trained temperature detection model, so that the temperature detection model outputs the detection temperature of each pixel point according to the three-channel ratio of each pixel point in the environmental hazard monitoring image, wherein the three-channel ratio of each pixel point includes the ratio of the R channel to the G channel, the ratio of the R channel to the B channel, and the ratio of the G channel to the B channel; According to the detected temperature of each pixel point, the temperature at each position in the grain depot to be monitored is determined, and the temperature in the grain depot to be monitored is monitored.

6. According to claim 4, a monitoring method for improving grain depot safety based on blockchain is characterized in that: The monitoring of the man-made hidden dangers of the grain depot to be monitored by using the multiple designated grain depot images specifically includes: Pre-build a behavioral feature library of man-made hidden dangers; Extracting human features from the plurality of designated grain depot images to obtain a plurality of body motion features; The body movement features are used to generate corresponding behavior videos according to the time data of the multiple designated grain depot images; The behavior features in the behavior video are extracted and compared with the features in the behavior feature library to identify whether the behavior of the human figure is a hidden danger behavior, so as to realize the monitoring of the man-made hidden dangers in the grain warehouse to be monitored.

7. A monitoring method for improving grain depot safety based on blockchain according to claim 6, characterized in that: The human figure feature also includes facial features, and the behavior of identifying the human figure is a hidden danger behavior. After that, the method further includes: The facial information of the person in charge of the grain depot to be monitored is collected in advance through the intelligent monitoring terminal and uploaded to the blockchain technology platform; Extracting facial features of the person in charge from the facial information of the person in charge, and saving the features to the behavior feature library; Comparing the facial features of the human figure with the facial features of the person in charge, and identifying the human figure; If the human figure is the person in charge of the grain depot to be monitored, an early warning message is generated and sent to the management node to warn the supervisory department of potential dangers; If the human figure is not the person in charge of the grain warehouse to be monitored, an early warning message is generated and sent to the corresponding intelligent monitoring terminal to issue a hidden danger warning.

8. According to claim 1, a monitoring method for improving grain depot safety based on blockchain is characterized in that: After monitoring the grain depot to be monitored, the method further includes: When a traceability query is performed on the grain depot monitoring data, all grain depot videos of the grain depot to be monitored collected by the intelligent monitoring terminal are obtained through the second identification code to perform traceability.

9. A monitoring device based on blockchain to improve the safety of grain depots, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: According to the terminal identifications of the plurality of intelligent monitoring terminals and the location information of the plurality of grain depots to be monitored, a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is established; The corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is encrypted to generate a plurality of corresponding first identification codes, and the plurality of first identification codes are sent to the blockchain technology platform for data storage, wherein the first identification code is used to identify the unique corresponding relationship between the intelligent monitoring terminal and the grain depot to be monitored; The grain depot video of the grain depot to be monitored is collected in real time through the intelligent monitoring terminal, the corresponding relationship between the grain depot video and the grain depot to be monitored is encrypted, a second identification code is generated, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; Verifying the video source of the grain depot video according to the first identification code and the second identification code; If the verification is passed, the grain depot to be monitored will be monitored.

10. A non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to: According to the terminal identifications of the plurality of intelligent monitoring terminals and the location information of the plurality of grain depots to be monitored, a corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is established; The corresponding relationship between each intelligent monitoring terminal and the grain depot to be monitored is encrypted to generate a plurality of corresponding first identification codes, and the plurality of first identification codes are sent to the blockchain technology platform for data storage, wherein: The first identification code is used to identify the unique correspondence between the intelligent monitoring terminal and the grain depot to be monitored; The grain depot video of the grain depot to be monitored is collected in real time through the intelligent monitoring terminal, the corresponding relationship between the grain depot video and the grain depot to be monitored is encrypted, a second identification code is generated, and the second identification code and the grain depot video are sent to the blockchain technology platform for data storage, wherein the second identification code is used to identify the unique corresponding relationship between the grain depot video and the grain depot to be monitored; Verifying the video source of the grain depot video according to the first identification code and the second identification code; If the verification is passed, the grain depot to be monitored will be monitored.

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