Whole-process monitoring and management method and system for grain reserve warehouse

Abstract

The invention relates to the technical field of grain reserve management, in particular to a full-process monitoring and management method and system for a grain reserve warehouse, and the method comprises the steps: carrying out warehousing registration when a grain transport vehicle passes through a gate sentry, making an IC card containing grain selling information, shooting a video of warehousing registration of the grain transport vehicle through a first video monitoring unit, and carrying out the sampling and quality inspection at a sampling and quality inspection position; carrying out quality inspection on the grains carried by the grain transport vehicle, obtaining a quality inspection result, and writing the quality inspection result into the IC card; the grain transporting vehicle enters a gross weight metering link, an analysis unit analyzes a third video in the shooting process of the third video, and early warning information is sent out when an illegal behavior is detected in the third video; verifying the grain transport vehicle and the IC card, and allowing the grain transport vehicle to enter a warehouse for unloading after verification is passed; and the fifth video monitoring unit monitors the warehouse in real time, and the sixth video monitoring unit shoots the whole grain delivery process, so that safety management of grain storage is realized, and remarkable improvement is brought to grain safety.

Description

Technical Field

[0001] The present invention relates to the technical field of grain reserve management, and more particularly to a full-process monitoring and management method and system for a grain reserve warehouse. Background Art

[0002] With the development of agricultural modernization, as an important infrastructure for food security, the management level of grain reserve warehouses directly affects the quality and safety of grains. Traditional grain reserve warehouse management methods have problems such as backward monitoring means, inaccurate data collection, and low management efficiency. These problems not only affect the efficiency of grain reserves but also pose potential threats to grain quality.

[0003] A similar prior art is a Chinese patent application with the publication number CN116205478A, which relates to a method and system for preventing and controlling grain reserve risks and belongs to the field of intelligent warehousing. The method includes: obtaining the types of grains in the granary; obtaining the inventory levels corresponding to each type of grain in real time; uploading the types of grains and the corresponding inventory levels of the quality inspection results obtained in real time to the blockchain module; generating a visual chart of inventory changes based on the quality inspection results blockchain module; when the inventory level of the quality inspection results changes, obtaining purchase and sale data; uploading the purchase and sale data of the quality inspection results to the quality inspection results blockchain module; generating a visual chart of purchase and sale based on the quality inspection results blockchain module. This application facilitates the background manager to timely understand the inventory level corresponding to each type of grain in the granary. At the same time, by uploading the purchase and sale data to the blockchain module, it is convenient for the background manager to timely understand the changes in the purchase and sale data of grains during the process of grain in and out based on the visual chart of purchase and sale, thereby facilitating the management of the granary.

[0004] Another similar prior art is a Chinese patent application with the publication number CN113807601A, which provides an efficient and intelligent grain depot logistics transfer system, including a material management system, and the quality inspection results material management system is used to manage and process the grains entering and leaving the transfer center; an intelligent grain depot management system, and the quality inspection results intelligent grain depot management system is used to adjust the grain depot environment of the grains stored in the transfer center; an intelligent driving system, and the quality inspection results intelligent driving system is used to send movement instructions according to road surface information to transport grains in the transfer center; the intelligent grain depot management system, the intelligent driving system, and the material management system are connected through a 5G communication network. The unmanned grain depot logistics transfer system of this invention schedules intelligent grain logistics special platform vehicles based on 5G communication technology, makes full use of each grain logistics special platform vehicle, greatly improves the transfer efficiency, and at the same time ensures the driving safety of the platform vehicles.

[0005] However, both of the above two applications only consider the management of granaries or grain depots and do not consider the food safety issues during the process of grain entering the warehouse. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides a full-process monitoring and management method and system for grain reserves, which can achieve efficient, safe and transparent management of grain reserves, bringing significant improvements to food security.

[0007] In order to achieve the above-mentioned discovery purpose, the present invention provides a full-process monitoring and management method and system for a grain reserve warehouse, wherein video monitoring units are respectively installed at multiple locations in each link of the grain reserve process, and the method and system are implemented by executing the following steps: Step S1: When a grain transport vehicle passes through a gate, it registers for entry into the warehouse, identifies and saves grain sale information, and produces an IC card containing the grain sale information based on the grain sale information. At the same time, a first video monitoring unit shoots a video of the grain transport vehicle registering for entry into the warehouse as a first video; Step S2: At the sampling and quality inspection location, the second video monitoring unit shoots a video of the sampling and quality inspection of the grain transport vehicle as a second video, performs quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection result, writes the quality inspection result into the IC card, determines whether the quality inspection result is qualified, and grants the IC card access to the warehouse if it is qualified, and executes step S3; Step S3: the grain transport vehicle enters the gross weight measurement phase and performs the first weight inspection. The third video monitoring unit shoots a video of the gross weight measurement of the grain transport vehicle as a third video. During the shooting of the third video, the analysis unit also analyzes the third video. When a violation is detected in the third video, an early warning message is issued, and the staff is reminded to adjust the grain transport vehicle. After the gross weight measurement of the grain transport vehicle passes, the IC card is updated. Step S4: verifying the grain transport vehicle and the IC card, and allowing the grain transport vehicle to enter the warehouse for unloading after the verification is passed. At the unloading and peeling place of the warehouse, the fourth video monitoring unit shoots the video of the grain transport vehicle unloading and peeling as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card, the grain transport vehicle is unloaded normally. After the second weight inspection, the increase and deduction amount of the grain is calculated, and the grain sales result is calculated. Otherwise, the grain transport vehicle is stopped from unloading, and an early warning message is issued to notify the staff to re-inspect the grain carried by the grain transport vehicle; Step S5: The fifth video surveillance unit monitors the warehouse in real time and records the process of grain condition detection, mechanical ventilation and fumigation. The sixth video surveillance unit shoots the entire process of grain leaving the warehouse, wherein each of the video records includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly stored and processed by the monitoring center.

[0008] As a preferred technical solution of the present invention, the step S1 further includes: The first video includes all video records of the grain transport vehicle from the start of warehousing registration to leaving the warehousing registration office. The grain sales information includes the identity information of the grain seller, the license plate number of the grain transport vehicle, and the corresponding vehicle type.

[0009] As a preferred technical solution of the present invention, after the step S2 and before the step S3, it further includes: At the gross weight measurement point, obtain the last time when the grain transport vehicle leaves the sampling and quality inspection point from the second video of the monitoring center as the first time, calculate the first time difference between the time when the grain transport vehicle arrives at the gross weight measurement point and the first time. When the first time difference is less than or equal to the first threshold and the grain transport vehicle has the permission to enter the warehouse, allow the grain transport vehicle to enter the gross weight measurement link and execute step S3. Otherwise, send a warning message to notify the staff for further inspection.

[0010] As a preferred technical solution of the present invention, in the step S4, verifying the grain transport vehicle and the IC card includes: Obtain the last time when the grain transport vehicle leaves the gross weight measurement point from the third video of the monitoring center as the second time, calculate the second time difference between the time when the grain transport vehicle arrives at the warehouse unloading and deweighting point and the second time. When the second time difference is less than or equal to the second threshold and the grain transport vehicle has the permission to enter the warehouse, obtain the quality inspection result and measurement result of the grain carried by the grain transport vehicle from the IC card and verify them with the management system. After the verification is passed, allow the grain transport vehicle to enter the warehouse for unloading.

[0011] As a preferred technical solution of the present invention, in the step S2, writing the quality inspection result of the grain carried by the grain transport vehicle into the IC card further includes: Obtain multiple quality inspection images of the grain transport vehicle through the second video, correspond the quality inspection images to the IC card, and record the corresponding relationship between the quality inspection images and the IC card in the storage unit.

[0012] As a preferred technical solution of the present invention, in the step S4, analyzing the third video includes: Collect a large number of illegal behavior images from historical images, mark the illegal behavior characteristics during measurement on the illegal behavior images as training data, construct a deep learning model, and use the training data to train the deep learning model; Identify the moving objects in the third video, obtain the images of each moving object, identify the images of the moving objects based on the deep learning model, and when it is identified that the images of the moving objects have illegal behaviors, determine that there are illegal behaviors in the third video.

[0013] As a preferred technical solution of the present invention, in step S4, analyzing the fourth video includes: Collecting grain sample images including different moisture and impurity contents, and annotating the grain sample images to determine the moisture and impurity contents of each grain sample image; Constructing a machine learning model, and training the machine learning model with the annotated grain sample images so that the machine learning model can predict the moisture and impurity contents of the grain based on the characteristics of the grain; Extracting the original grain images of each frame from the fourth video, adjusting the brightness and contrast of the original grain images using image processing techniques, extracting the characteristics of the grain from the original grain images, and inputting them into the machine learning model to obtain the moisture and impurity contents of the grain on the original grain images. The characteristics of the grain include the color, shape, and texture of the grain.

[0014] As a preferred technical solution of the present invention, analyzing the fourth video further includes: Comparing the moisture and impurity contents of the grain on the original grain image with the quality inspection results of the grain to obtain the differences between the two. If each of the differences is less than or equal to the third threshold, it is determined that the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card; otherwise, it is determined that the recognition result in the fourth video is inconsistent with the quality inspection result recorded in the IC card.

[0015] As a preferred technical solution of the present invention, in step S4, calculating the increase or deduction amount of the grain includes: Respectively calculating the increase or deduction amount of the grain according to the moisture content and impurity content; When the actual moisture content of the grain is less than the standard specified moisture content, based on the standard specified moisture content, for each first numerical point by which the actual moisture content is less than the standard, the grain increases by N%, where N is greater than 0 and less than 1. When the actual moisture content is lower than the standard specified moisture content by the second numerical point or more, the grain increase is calculated according to the grain increase corresponding to the second numerical point; When the actual moisture content of the grain is greater than the standard specified moisture content, based on the standard specified moisture content, for each first numerical point by which the actual moisture content is greater than the standard, the grain is deducted by M%, where M is greater than or equal to 1; When the actual impurity content of the grain is lower than the impurity content specified by the standard, based on the impurity content specified by the standard, the grain increase is N% for every time the actual impurity content is lower than a first numerical point. When the actual impurity content of the grain is higher than the impurity content specified by the standard, based on the impurity content specified by the standard, the grain deduction is K% for every time the actual impurity content is higher than a first numerical point. K is greater than or equal to 1.

[0016] The present invention also provides a full-process monitoring and management system for the grain reserve as described above, wherein video monitoring units are installed at multiple locations in each link of the grain reserve process, including the following modules: A registration unit is used to register the grain transport vehicle when it passes through the gate, identify and save the grain sale information, and produce an IC card containing the grain sale information based on the grain sale information. At the same time, the first video monitoring unit shoots a video of the grain transport vehicle entering the warehouse as the first video; The quality inspection unit is used for, at the sampling quality inspection location, the second video monitoring unit shoots the video of the sampling quality inspection of the grain transport vehicle as the second video, performs quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection result, writes the quality inspection result into the IC card, determines whether the quality inspection result is qualified, grants the IC card the right to enter the warehouse if it is qualified, and executes the metering unit; The metering unit is used for the grain transport vehicle to enter the gross weight measurement link and perform the first weight inspection. The third video monitoring unit shoots the video of the gross weight measurement of the grain transport vehicle as the third video. During the shooting of the third video, the analysis unit also analyzes the third video. When a violation is detected in the third video, an early warning message is issued, and the staff is reminded to adjust the grain transport vehicle. After the gross weight measurement of the grain transport vehicle is passed, the IC card is updated; The verification unit is used to verify the grain truck and the IC card, and allows the grain truck to enter the warehouse for unloading after the verification is passed. At the unloading and peeling place of the warehouse, the fourth video monitoring unit shoots the video of the grain truck unloading and peeling as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card, the grain truck is unloaded normally. After the second weight inspection, the increase and deduction of the grain is calculated, and the grain sales result is calculated. Otherwise, the grain truck is stopped from unloading, and an early warning message is issued to notify the staff to re-inspect the grain carried by the grain truck; The monitoring unit is used for the fifth video monitoring unit to monitor the warehouse in real time and record the process of grain condition detection, mechanical ventilation and fumigation. The sixth video monitoring unit shoots the whole process of grain leaving the warehouse, wherein each of the video records includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly stored and processed by the monitoring center.

[0017] Compared with the prior art, the beneficial effects of the present invention are at least as follows: 1. The technical solution of the present invention performs warehouse registration when the grain transport vehicle passes through the gate, identifies and saves the grain sales information, and produces an IC card containing the grain sales information based on the grain sales information. At the same time, the first video monitoring unit shoots the video of the grain transport vehicle entering the warehouse as the first video. It ensures that the source of each batch of grain is clear and traceable, and also lays a solid foundation for the subsequent grain management process. At the sampling and quality inspection department, the second video monitoring unit shoots the video of the grain transport vehicle sampling and quality inspection as the second video, conducts quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection results, writes the quality inspection results into the IC card, judges whether the quality inspection results are qualified, and grants the IC card access to the warehouse if qualified. It can ensure that the quality of grain is effectively controlled and prevent unqualified grain from entering the warehouse. The grain transport vehicle enters the gross weight measurement link and performs the first weight inspection. The third video monitoring unit shoots the video of the gross weight measurement of the grain transport vehicle as the third video. During the shooting process of the third video, the analysis unit also analyzes the third video, issues a warning message when a violation is detected in the third video, and reminds the staff to adjust the grain transport vehicle, and updates the IC card after the gross weight measurement of the grain transport vehicle passes. The data integrity and traceability of the entire measurement process are ensured, providing security for grain reserves.

[0018] 2. The technical solution of the present invention also verifies the grain transport vehicle and IC card, and allows the grain transport vehicle to enter the warehouse for unloading after verification. At the unloading and peeling point of the warehouse, it ensures that the unloaded grain is consistent with the quality inspection results, and at the same time prevents the unloading of unqualified grain, thereby protecting the safety of grain reserves. The fifth video surveillance unit monitors the warehouse in real time, records the process of grain condition detection, mechanical ventilation and fumigation, and the sixth video surveillance unit shoots the entire process of grain leaving the warehouse, which helps to timely discover and prevent potential safety issues. Through the coordination between the above steps, efficient, safe and transparent management of grain reserves is achieved, which brings significant improvements to food security. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0020] Figure 1 A flowchart of the steps of a full-process monitoring and management method of a grain reserve warehouse in the present invention; Figure 2 The present invention is a structural diagram of the whole process monitoring and management system of a grain reserve warehouse. DETAILED DESCRIPTION

[0021] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0022] It can be understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, the first xx script may be referred to as the second xx script, and similarly, the second xx script may be referred to as the first xx script.

[0023] Traditional methods for managing grain storage depots have problems such as backward monitoring means, inaccurate data collection, and low management efficiency. These problems not only affect the efficiency of grain storage but also pose a potential threat to grain quality.

[0024] In response to the above technical problems, the present invention proposes a full-process monitoring and management method for a grain storage depot as shown in Figure 1 which installs video monitoring units at multiple positions in each link during the grain storage process and is implemented by performing the following steps: Step S1: When the grain transport vehicle passes through the gatehouse, it conducts inbound registration, identifies and saves the grain sales information, makes an IC card containing the grain sales information based on the grain sales information, and at the same time, the first video monitoring unit takes a video of the inbound registration of the grain transport vehicle as the first video.

[0025] Specifically, after the grain transport vehicle arrives at the gatehouse, the driver presents relevant certificates, and the staff uses the registration system at the gatehouse to read the driver and vehicle information and generate a grain sales information form, including vehicle type, license plate number, driver's ID number, name, estimated grain load, and grain sales type, etc. Based on the grain sales information form, the system generates an IC card, which contains the basic information of the driver and the vehicle, as well as the estimated grain type and quantity, ensuring the accuracy and consistency of the information and reducing human operation errors. The IC card is given to the driver for identity verification and information recording in subsequent sampling quality inspection, gross weight measurement, and other links. The first video monitoring unit is installed above the gatehouse and automatically takes the whole process of inbound registration of each grain transport vehicle. The video content includes the vehicle's license plate number, the driver's facial features, and the external condition of the vehicle. The video monitoring provides security for the grain storage depot, prevents unauthorized vehicles from entering, and provides video evidence for subsequent security audits. At the same time, the video data is periodically uploaded to the monitoring center for easy tracing of the inbound situation of each grain transport vehicle when needed. Through this step, the source of each batch of grain can be clearly traced during the grain storage process, and a solid foundation is also laid for subsequent grain management processes.

[0026] Step S2: At the sampling and quality inspection area, the second video monitoring unit captures the video of the grain truck's sampling and quality inspection as the second video, conducts a quality inspection on the grain carried by the grain truck and obtains the quality inspection result, writes the quality inspection result into the quality inspection result IC card, determines whether the quality inspection result is qualified, and grants the IC card the permission to enter the warehouse in the case of qualification, and then executes Step S3.

[0027] Specifically, after the grain truck completes the warehousing registration and obtains the IC card containing the grain selling information, next, the vehicle will go to the sampling and quality inspection area for grain quality inspection. After the grain truck arrives at the sampling and quality inspection area, the quality inspection personnel use sampling tools to take out grain samples from the vehicle. This process is recorded by the second video monitoring unit throughout, ensuring the transparency and fairness of the sampling process. The second video monitoring unit is installed above and at other positions in the sampling and quality inspection area. The video captures the whole process from the arrival of the grain truck, sampling, sample sealing to the departure of the vehicle. Each video monitoring unit consists of multiple monitoring devices, which can comprehensively capture all operations in each grain selling link. The video content includes the license plate number of the vehicle, the operations of the sampling personnel, the sealing of the samples, and the departure of the vehicle. Through the video monitoring and the recording of the quality inspection results, the quality of the grain can be effectively controlled to prevent unqualified grain from entering the warehouse.

[0028] The sampled grain samples are sent to the laboratory for quality inspection, and the quality inspection includes the testing of key indicators such as moisture content, impurity ratio, and pesticide residues. The video monitoring provides a transparent sampling and quality inspection process to prevent fraud during the inspection process. After the quality inspection is completed, the quality inspection result is recorded in the system and simultaneously written into the IC card held by the driver. The IC card contains the quality inspection result information of the grain. The management system determines whether the grain is qualified according to the quality inspection result. If the grain quality meets the standard, the management system will grant the grain truck the permission to enter the warehouse. The driver swipes the IC card at the access control system. If the IC card shows that the quality inspection result is qualified, the access control system will allow the vehicle to enter the warehouse area and prepare for the next tare weighing.

[0029] Step S3: The grain truck enters the tare weighing process and conducts the first weighing. The third video monitoring unit captures the video of the grain truck's tare weighing as the third video. During the shooting of the third video, the analysis unit also analyzes the third video, issues a warning message when detecting violations in the third video, and reminds the staff to adjust the grain truck. After the tare weighing of the grain truck passes, the IC card is updated.

[0030] Specifically, in the gross weight measurement link of grain reserve, the grain transport vehicle will be weighed to determine the actual weight of the grain. After obtaining the permission to enter the warehouse, the grain transport vehicle drives into the gross weight measurement area, and the third video monitoring unit captures the whole process of vehicle weighing. The third video monitoring unit records the weighing process of the vehicle from the moment it enters the measurement area until it leaves the measurement area. The video content includes the license plate number of the vehicle, the position of the vehicle on the weighing platform, the weighing reading, and the situation of the vehicle leaving. The analysis unit analyzes the video captured by the third video monitoring unit in real time to monitor any possible violations, such as the vehicle not fully stopping on the weighing platform, the driver leaving the cab, the vehicle being overweight, etc. Through video monitoring and real-time analysis, the accuracy of gross weight measurement is ensured, and violations during the weighing process are avoided. If the analysis unit detects a violation, the system will immediately issue a warning message and display it on the screen of the monitoring center. The real-time video analysis and warning system helps to promptly detect and correct violations, maintaining the fairness and compliance of the measurement process. At the same time, the system will notify the on-site staff to remind them to adjust the grain transport vehicle or handle other violations. Automated monitoring and warning reduce manual supervision, can fully monitor every corner during measurement, and also prevent staff from assisting drivers in violating regulations. When the gross weight measurement of the grain transport vehicle is completed and there are no violations, the IC card is updated to record the result of the gross weight measurement. Video recording and IC card update ensure the data integrity and traceability of the entire measurement process, providing safety guarantee for grain reserve.

[0031] Step S4: Verify the grain transport vehicle and the IC card, and after passing the verification, allow the grain transport vehicle to enter the warehouse for unloading. At the warehouse unloading and tare removal area, the fourth video monitoring unit captures the video of the grain transport vehicle unloading and tare removal as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the record in the IC card, the grain transport vehicle unloads normally. After the second weighing is completed, the calculation of the increase or deduction of the grain quantity starts, and the selling result of the grain is calculated. Otherwise, the unloading of the grain transport vehicle is stopped, and a warning message is issued to notify the staff to re-inspect the grain carried by the grain transport vehicle.

[0032] Specifically, after the grain truck arrives at the unloading area of ​​the warehouse, the driver presents the IC card for staff verification. The staff uses a handheld device to read the information in the IC card, including vehicle information, driver information, quality inspection results, etc., to confirm the identity of the vehicle and driver and the eligibility of the grain. If the IC card verification is passed, the staff allows the grain truck to enter the warehouse for unloading. The specific verification process will be described in detail below. The fourth video surveillance unit is installed in the unloading area to automatically shoot the entire process of unloading and peeling of the grain truck. The video content includes the vehicle's license plate number, unloading operation, removal of the outer packaging of the grain, and net weight measurement of the grain. The analysis unit analyzes the video shot by the fourth video surveillance unit in real time, especially the key steps in the unloading and peeling process. The system will identify key information in the video, such as whether the peeling operation complies with regulations. The video is also analyzed and identified, and the identification results in the video are compared with the quality inspection results recorded in the IC card to ensure the consistency of grain quality. If the identification results in the video are consistent with the quality inspection results in the IC card, the grain truck can be unloaded normally, and then a second weight inspection is carried out, and the increase and deduction of grain is calculated to calculate the grain sales results. The first weight check is when the gross weight is measured, and the second weight check is to calculate the net weight of the grain after removing the skin; if there is a discrepancy, the system will stop the unloading operation of the grain truck and issue an early warning message to notify the staff to re-inspect or otherwise process the grain carried by the grain truck. This process is to prevent grain that has not passed the quality inspection from entering the warehouse. For example, the grain carried by vehicle A is qualified in the quality inspection, but the grain carried by vehicle B is unqualified. Vehicle B changes the license plate in other unmonitored areas (assuming that the models of vehicles A and B are the same). The driver of vehicle A drives the original vehicle B into the warehouse to unload. When the grain carried is the same, it is difficult to determine that the grain unloaded in the warehouse is unqualified. Therefore, at the beginning of unloading, the grain screen is captured again through video surveillance, and the moisture and impurity content in the grain is further identified through image analysis technology, and compared with the quality inspection results recorded in the IC card. Through video analysis and IC card information comparison, it is ensured that the unloaded grain is consistent with the quality inspection results, while preventing the unloading of unqualified grain and protecting the safety of grain reserves.

[0033] Step S5: The fifth video surveillance unit monitors the warehouse in real time and records the process of grain condition detection, mechanical ventilation and fumigation. The sixth video surveillance unit shoots the entire process of grain leaving the warehouse. Each video record includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly stored and processed by the monitoring center.

[0034] Specifically, during the monitoring and management of the grain reserve depot, the fifth and sixth video monitoring units are respectively responsible for monitoring the internal environment of the warehouse and the process of grain outbond. The fifth video monitoring unit is installed inside the warehouse to monitor the processes of grain condition detection, mechanical ventilation, and fumigation in real time. The fifth video monitoring unit can be a fixed camera or a mobile camera, and its monitoring angle and position can be adjusted as needed. Grain condition detection includes the monitoring of key parameters such as temperature, humidity, and grain quality. These data can be automatically collected by sensors and combined with video monitoring to provide comprehensive grain condition information. Video monitoring records the implementation processes of mechanical ventilation and fumigation to ensure that these operations are carried out in accordance with regulations, which helps to maintain the quality and safety of the grain reserve. The sixth video monitoring unit is installed in the outbond area to record the entire process of grain outbond, including the loading of grain, the entry and exit of transport vehicles, and the weighing of grain. Whether it is grain condition detection, mechanical ventilation, fumigation, or the outbond process, the video records will be automatically uploaded to the monitoring center. The monitoring center is responsible for receiving, storing, and processing all the uploaded video records. The video materials can be used for daily monitoring, problem troubleshooting, security audits, and archiving as historical data. At the same time, the monitoring center will implement strict data access control to ensure that only authorized personnel can access the video materials. Through the fifth and sixth video monitoring units, a comprehensive monitoring of the internal environment of the grain reserve depot and the outbond process is achieved. This helps to timely detect and prevent potential safety problems such as theft and fire.

[0035] Through the coordination among the above steps, the efficient, safe, and transparent management of the grain reserve depot is achieved, bringing significant improvements to grain security.

[0036] Furthermore, the above step S1 further includes: The first video includes all the video records of the grain transport vehicle from the start of the inbound registration to leaving the inbound registration area. The grain sales information includes the identity information of the grain seller, the license plate number of the grain transport vehicle, and the corresponding vehicle type.

[0037] Specifically, the first video monitoring unit records the entire process of the grain transport vehicle from arriving at the inbound registration area until leaving, including links such as vehicle queuing, communication between the driver and the staff, and information entry. At the same time, each video record will contain the specific shooting time to ensure the time accuracy and sequentiality of the video materials, which helps with subsequent audits and traceability. The grain sales information not only includes basic grain sales data but also covers the identity information of the grain seller, such as name, ID number, etc., as well as the license plate number and vehicle type of the grain transport vehicle, which helps to establish a complete grain sales archive, enhance the traceability of information. At the same time, the detailed video records and grain sales information help to identify and prevent illegal or suspicious grain inbound behaviors, improving the security of the grain reserve.

[0038] Furthermore, after the above step S2 and before step S3 are executed, it further includes: At the gross weight measurement point, obtain the last time when the grain transport vehicle leaves the sampling and quality inspection point from the second video of the monitoring center as the first time, calculate the first time difference between the time when the grain transport vehicle arrives at the gross weight measurement point and the first time. When the first time difference is less than or equal to the first threshold and the grain transport vehicle has the permission to enter the warehouse, allow the grain transport vehicle to enter the gross weight measurement link and execute step S3; otherwise, send a warning message to notify the staff to conduct further inspections.

[0039] Specifically, before gross weight measurement, it is necessary to ensure that the grain carried is qualified. Obtain the last time when the grain transport vehicle leaves the sampling and quality inspection point from the second video of the monitoring center and mark it as the first time, and calculate the time difference between the time when the grain transport vehicle arrives at the gross weight measurement point and the first time, that is, the first time difference. If the first time difference is less than or equal to the preset first threshold and the grain transport vehicle has the permission to enter the warehouse, allow the grain transport vehicle to enter the gross weight measurement link and continue to execute step S3. Controlling the time of the grain transport vehicle from the sampling and quality inspection point to the gross weight measurement point can effectively prevent the grain from being replaced during transportation. The first threshold is the average time from the last time when the grain transport vehicle leaves the sampling and quality inspection point to the gross weight measurement point obtained from multiple historical grain sales records. If the first time difference exceeds the first threshold or the grain transport vehicle does not have the permission to enter the warehouse, a warning message is sent and the staff is notified to conduct further inspections to ensure grain safety.

[0040] Furthermore, in the above step S4, verifying the grain transport vehicle and the IC card includes: Obtain the last time when the grain transport vehicle leaves the gross weight measurement point from the third video of the monitoring center as the second time, calculate the second time difference between the time when the grain transport vehicle arrives at the warehouse unloading and tare removal point and the second time. When the second time difference is less than or equal to the second threshold and the grain transport vehicle has the permission to enter the warehouse, obtain the quality inspection result and measurement result of the grain carried by the grain transport vehicle from the IC card and verify them with the management system. After the verification is passed, allow the grain transport vehicle to enter the warehouse for unloading.

[0041] Specifically, the above steps have detailed regulations on the verification process of the grain transport vehicle and the IC card to ensure the safety of the grain and the compliance of the process. Specifically, the last time when the grain transport vehicle leaves the gross weight measurement place is obtained from the third video of the monitoring center and marked as the second time. The time difference between the time when the grain transport vehicle arrives at the warehouse for unloading and tare removal and the second time is calculated, that is, the second time difference. If the second time difference is less than or equal to the preset second threshold and the grain transport vehicle has the permission to enter the warehouse, the next step is carried out. The quality inspection result and measurement result of the grain carried by the grain transport vehicle are obtained from the IC card and verified with the records in the control system. If the quality inspection result and measurement result are consistent with the records in the control system and the verification is passed, the grain transport vehicle is allowed to enter the warehouse for unloading. By controlling the time of the grain transport vehicle from the gross weight measurement place to the warehouse unloading place, it effectively prevents the grain from being replaced during transportation and allows unqualified grain to enter the warehouse.

[0042] Furthermore, in the above step S2, writing the quality inspection result of the grain carried by the grain transport vehicle into the IC card also includes: Obtaining multiple quality inspection images of the grain transport vehicle through the second video, corresponding the quality inspection images with the IC card, and recording the corresponding relationship between the quality inspection images and the IC card in the storage unit.

[0043] Specifically, in step S2, in addition to recording the quality inspection result of the grain transport vehicle, it also involves binding the image information related to the chemical analysis with the IC card. During the sampling and quality inspection process, multiple quality inspection links of the grain transport vehicle are monitored through the second video monitoring unit to obtain multiple quality inspection images, including key steps such as grain sample collection, chemical analysis process, and operation of the chemical analysis personnel. The obtained quality inspection images are associated with the IC card corresponding to the grain transport vehicle, and through image recognition technologies such as license plate recognition, barcode or QR code scanning, the images are automatically matched with specific IC cards. The corresponding relationship between the quality inspection images and the IC card is recorded in the storage unit. It provides more comprehensive information for the traceability of the grain. At the same time, in case of quality problems, the specific quality inspection images can be quickly traced through the IC card, ensuring the safety of the grain reserve and improving the efficiency of problem tracking and handling.

[0044] Furthermore, in the above step S4, analyzing the third video includes: Collecting a large number of illegal behavior images from historical images, marking the illegal behavior characteristics during measurement on the illegal behavior images as training data, constructing a deep learning model, and training the deep learning model with the training data; Identifying the moving objects in the third video, obtaining the images of each moving object, identifying the images of the moving objects based on the deep learning model, and determining that there is an illegal behavior in the third video when the images of the identified moving objects have illegal behaviors.

[0045] Specifically, the analysis ability of the third video is enhanced through deep learning technology to identify and prevent violations in the metering process. Specifically, a large number of violation images are collected from historical images, which may include violations such as drivers' illegal operations, and these violation images are labeled to identify and mark the violation characteristics in the images, such as vehicle position, driver behavior, etc. A deep learning model is constructed using the labeled violation images, and the model can be a convolutional neural network (CNN) or other deep learning architectures suitable for image recognition. The deep learning model can learn violation characteristics from a large amount of data, improving the accuracy of violation identification. The trained model learns the characteristics of violations from the images, enabling it to identify new violation images. In the third video, video analysis technology is used to identify moving objects and obtain images of each moving object. The moving objects include grain trucks and people. Based on the constructed deep learning model, the images of the moving objects in the third video are identified to determine whether there are violation characteristics. If the model identifies violation characteristics in the images of the moving objects, the system will determine that there are violations in the third video and take corresponding warning and handling measures. The automated violation identification enhances the response ability of the warning system and can quickly detect and handle violations.

[0046] Furthermore, in step S4 above, the analysis of the fourth video includes: Collect grain sample images with different moisture and impurity contents, and label the grain sample images to determine the moisture and impurity contents of each grain sample image.

[0047] Construct a machine learning model, and use the labeled grain sample images to train the machine learning model so that the machine learning model can predict the moisture and impurity contents of the grain based on the characteristics of the grain.

[0048] Extract the original grain images of each frame from the fourth video, and use image processing technology to adjust the brightness and contrast of the original grain images. Extract the characteristics of the grain from the original grain images and input them into the machine learning model to obtain the moisture and impurity contents of the grain on the original grain images. The characteristics of the grain include the color, shape, and texture of the grain.

[0049] Furthermore, the analysis of the fourth video also includes: Compare the moisture and impurity contents of the grain on the original grain images with those of the grain, obtain the differences between the two for each item. If each difference is less than or equal to the third threshold, it is determined that the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card; otherwise, it is determined that the recognition result in the fourth video is inconsistent with the quality inspection result recorded in the IC card.

[0050] Specifically, compare the predicted moisture and impurity contents with the quality inspection results recorded in the IC card to obtain the difference between the two. If each difference is less than or equal to a preset third threshold, it is determined that the recognition result in the fourth video is consistent with the quality inspection results recorded in the IC card; otherwise, it is determined to be inconsistent. By comparing the two, further identifying grain quality problems helps improve the safety of grain reserves.

[0051] Further, in step S4, perform the accounting of the increase or deduction of grain, including: Perform the increase or deduction of grain according to the moisture content and impurity content respectively; When the actual moisture content of the grain is less than the moisture content specified in the standard, based on the moisture content specified in the standard, for each first numerical point that the actual moisture content is less than, the grain increases by N%, where N is greater than 0 and less than 1. When the actual moisture content is below the second numerical point and above the moisture content specified in the standard, the grain increase is calculated according to the grain increase corresponding to the second numerical point. When the actual moisture content of the grain is greater than the moisture content specified in the standard, based on the moisture content specified in the standard, for each first numerical point that the actual moisture content is greater than, the grain is deducted by M%, where M is greater than or equal to 1. When the actual impurity content of the grain is less than the impurity content specified in the standard, based on the impurity content specified in the standard, for each first numerical point that the actual impurity content is less than, the grain increases by N%. When the actual impurity content of the grain is greater than the impurity content specified in the standard, based on the impurity content specified in the standard, for each first numerical point that the actual impurity content is greater than, the grain is deducted by K%, where K is greater than or equal to 1.

[0052] Specifically, for example, for grains and oils with an actual moisture content lower than the standard, based on the indicators specified in the standard, for each 0.5 (the first numerical value) percentage point lower, the increase is 0.75%, but when it is 2.5 percentage points or more lower than the standard specified indicator, there is no further increase. For grains and oils with an actual moisture content higher than the standard, based on the indicators specified in the standard, for each 0.5 (the first numerical value) percentage point higher, the deduction is 1.00%; if it is less than 0.5 percentage points lower or higher, the increase or deduction is not counted. Another example is that for grains and oils with an actual impurity content lower than the standard, based on the indicators specified in the standard, for each 0.5 (the first numerical value) percentage point lower, the increase is 0.75%. For grains and oils with an actual impurity content higher than the standard, based on the indicators specified in the standard, for each 0.5 (the first numerical value) percentage point higher, the deduction is 1.5%; if it is less than 0.5 percentage points lower or higher, the increase is not counted. When the actual moisture content of the grain is greater than P% of the moisture content specified in the standard or the actual impurity content is greater than L% of the impurity content specified in the standard, the grain sampled during quality inspection is unqualified grain, and the permission of the IC card cannot enter the warehouse to ensure the safety of grain reserves. At the same time, the above standards are also the basis for implementing the increase or deduction.

[0053] The present invention also provides a kind of asFigure 2 The whole process monitoring and management system of a grain reserve warehouse shown in the figure has video monitoring units installed at multiple locations in each link of the grain reserve process, including the following modules: The registration unit is used to register the grain truck entering the warehouse when passing through the gate, identify and save the grain sales information, and produce an IC card containing the grain sales information based on the grain sales information. At the same time, the first video monitoring unit shoots the video of the grain truck entering the warehouse as the first video; The quality inspection unit is used to, at the sampling quality inspection location, shoot the video of the sampling quality inspection of the grain transport vehicle as the second video by the second video monitoring unit, conduct quality inspection on the grain carried by the grain transport vehicle and obtain the quality inspection result, write the quality inspection result into the IC card, judge whether the quality inspection result is qualified, grant the IC card the right to enter the warehouse if it is qualified, and execute the metering unit; The metering unit is used for the first weight check when the grain truck enters the gross weight measurement link. The third video monitoring unit shoots the video of the gross weight measurement of the grain truck as the third video. During the shooting process of the third video, the analysis unit also analyzes the third video. When a violation is detected in the third video, an early warning message is issued, and the staff is reminded to adjust the grain truck. The IC card is updated after the gross weight measurement of the grain truck passes. The verification unit is used to verify the grain truck and IC card, and allows the grain truck to enter the warehouse for unloading after the verification is passed. At the unloading and skinning place of the warehouse, the fourth video monitoring unit shoots the video of the grain truck unloading and skinning as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card, the grain truck is unloaded normally. After the second weight inspection, the increase and deduction of grain is calculated and the grain sales result is calculated. Otherwise, the grain truck is stopped from unloading, and an early warning message is issued to notify the staff to re-inspect the grain carried by the grain truck; The monitoring unit is used for the fifth video monitoring unit to monitor the warehouse in real time and record the process of grain condition detection, mechanical ventilation and fumigation. The sixth video monitoring unit shoots the whole process of grain leaving the warehouse. Each video record includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly saved and processed by the monitoring center.

[0054] In summary, the present invention performs warehouse entry registration when the grain transport vehicle passes through the gate, identifies and saves grain sales information, and produces an IC card containing grain sales information based on the grain sales information. At the same time, the first video monitoring unit shoots the video of the grain transport vehicle entering the warehouse as the first video. It ensures that the source of each batch of grain is clear and traceable, and also lays a solid foundation for the subsequent grain management process. At the sampling and quality inspection department, the second video monitoring unit shoots the video of the grain transport vehicle sampling and quality inspection as the second video, conducts quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection results, writes the quality inspection results into the IC card, judges whether the quality inspection results are qualified, and grants the IC card access to the warehouse if qualified. It can ensure that the quality of grain is effectively controlled and prevent unqualified grain from entering the warehouse. The grain transport vehicle enters the gross weight measurement link and performs the first weight inspection. The third video monitoring unit shoots the video of the gross weight measurement of the grain transport vehicle as the third video. During the shooting process of the third video, the analysis unit also analyzes the third video, issues a warning message when a violation is detected in the third video, and reminds the staff to adjust the grain transport vehicle, and updates the IC card after the gross weight measurement of the grain transport vehicle passes. The data integrity and traceability of the entire measurement process are ensured, providing security for grain reserves.

[0055] The present invention also verifies the grain transport vehicle and IC card, and allows the grain transport vehicle to enter the warehouse for unloading after verification. At the unloading and peeling point of the warehouse, it ensures that the unloaded grain is consistent with the quality inspection results, and at the same time prevents the unloading of unqualified grain, thereby protecting the safety of grain reserves. The fifth video monitoring unit monitors the warehouse in real time, records the process of grain condition detection, mechanical ventilation and fumigation, and the sixth video monitoring unit shoots the entire process of grain leaving the warehouse, which helps to timely discover and prevent potential safety problems. Through the coordination between the above steps, efficient, safe and transparent management of grain reserves is achieved, which brings significant improvements to food security.

[0056] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0057] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The above program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0058] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0059] The above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the invention patent of the present invention should be subject to the appended claims.

[0060] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring and managing the entire process of a grain reserve, wherein video monitoring units are installed at multiple locations in each link of the grain reserve process, characterized in that: The method comprises: Step S1: When a grain transport vehicle passes through a gate, it registers for entry into the warehouse, identifies and saves grain sale information, and produces an IC card containing the grain sale information based on the grain sale information. At the same time, a first video monitoring unit shoots a video of the grain transport vehicle registering for entry into the warehouse as a first video; Step S2: At the sampling and quality inspection location, the second video monitoring unit shoots a video of the sampling and quality inspection of the grain transport vehicle as a second video, performs quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection result, writes the quality inspection result into the IC card, determines whether the quality inspection result is qualified, and grants the IC card access to the warehouse if it is qualified, and executes step S3; Step S3: the grain transport vehicle enters the gross weight measurement phase and performs the first weight inspection. The third video monitoring unit shoots a video of the gross weight measurement of the grain transport vehicle as a third video. During the shooting of the third video, the analysis unit also analyzes the third video. When a violation is detected in the third video, an early warning message is issued, and the staff is reminded to adjust the grain transport vehicle. After the gross weight measurement of the grain transport vehicle passes, the IC card is updated. Step S4: verifying the grain transport vehicle and the IC card, and allowing the grain transport vehicle to enter the warehouse for unloading after the verification is passed. At the unloading and peeling place of the warehouse, the fourth video monitoring unit shoots the video of the grain transport vehicle unloading and peeling as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card, the grain transport vehicle is unloaded normally. After the second weight inspection, the increase and deduction amount of the grain is calculated, and the grain sales result is calculated. Otherwise, the grain transport vehicle is stopped from unloading, and an early warning message is issued to notify the staff to re-inspect the grain carried by the grain transport vehicle; Step S5: The fifth video surveillance unit monitors the warehouse in real time and records the process of grain condition detection, mechanical ventilation and fumigation. The sixth video surveillance unit shoots the entire process of grain leaving the warehouse, wherein each of the video records includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly stored and processed by the monitoring center.

2. The method according to claim 1, characterized in that The step S1 further comprises: The first video includes all video records of the grain transport truck from the start of warehouse registration to leaving the warehouse registration office, and the grain sales information includes the identity information of the grain seller, the license plate number of the grain transport truck and the corresponding vehicle model.

3. The method according to claim 1, characterized in that: After step S2, before step S3 is performed, the following steps are further included: At the gross weight measurement point, the last time when the grain truck left the sampling and quality inspection point is obtained from the second video of the monitoring center as the first time, and the first time difference between the time when the grain truck arrived at the gross weight measurement point and the first time is calculated. When the first time difference is less than or equal to the first threshold and the grain truck has the authority to enter the warehouse, the grain truck is allowed to enter the gross weight measurement link and execute step S3; otherwise, an early warning message is issued to notify the staff to conduct further inspection.

4. The method according to claim 3, characterized in that In step S4, verifying the grain transport vehicle and the IC card includes: The last time when the grain truck left the gross weight measurement point is obtained from the third video of the monitoring center as the second time, and the second time difference between the time when the grain truck arrives at the warehouse for unloading and skin removal and the second time is calculated; when the second time difference is less than or equal to the second threshold and the grain truck has the authority to enter the warehouse, the quality inspection result and measurement result of the grain carried by the grain truck are obtained from the IC card and verified with the management system; after the verification is passed, the grain truck is allowed to enter the warehouse for unloading.

5. The method according to claim 2, characterized in that: In the step S2, writing the quality inspection result of the grain carried by the grain transport vehicle into the IC card further comprises: A plurality of quality inspection images of the grain transport vehicle are acquired through the second video, the quality inspection images are matched with the IC card, and the corresponding relationship between the quality inspection images and the IC card is recorded in a storage unit.

6. The method according to claim 1, characterized in that In step S4, analyzing the third video includes: Collect a large number of violation images from historical images, and mark the violation features during measurement on the violation images as training data, build a deep learning model, and use the training data to train the deep learning model; Identify the moving objects in the third video, obtain images of each of the moving objects, identify the images of the moving objects based on the deep learning model, and when it is identified that the images of the moving objects have violations, determine that there are violations in the third video.

7. The method according to claim 1, characterized in that In the step S4, analyzing the fourth video includes: Collecting grain sample images with different moisture and impurity contents, and marking the grain sample images to determine the moisture and impurity content of each grain sample image; Constructing a machine learning model, and using the labeled grain sample images to train the machine learning model, so that the machine learning model can predict the moisture and impurity content of the grain based on the characteristics of the grain; The original grain image of each frame is extracted from the fourth video, and the brightness and contrast of the original grain image are adjusted using image processing technology. The characteristics of the grain are extracted from the original grain image and input into the machine learning model to obtain the moisture and impurity content of the grain in the original grain image. The characteristics of the grain include the color, shape and texture of the grain.

8. The method according to claim 7, characterized in that Analyzing the fourth video further includes: The moisture and impurity content of the grain on the original grain image is compared with the quality inspection result of the grain to obtain the difference between the two items. If each of the differences is less than or equal to a third threshold, it is determined that the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card; otherwise, it is determined that the recognition result in the fourth video is inconsistent with the quality inspection result recorded in the IC card.

9. The method according to claim 1, characterized in that: In step S4, the calculation of the increase and deduction amount of the grain is performed, including: Add or subtract the amount of the grain according to its moisture content and impurity content; When the actual moisture content of the grain is less than the moisture content specified in the standard, based on the moisture content specified in the standard, the grain increment is N% for each time the actual moisture content is less than a first numerical point. When the actual moisture content is lower than a second numerical point of the moisture content specified in the standard and above, the grain increment is calculated according to the grain increment corresponding to the second numerical point, and N is greater than 0 and less than 1. When the actual moisture content of the grain is greater than the moisture content specified in the standard, based on the moisture content specified in the standard, the grain deduction amount M% is made for each time the actual moisture content is greater than one of the first numerical points, where M is greater than or equal to 1; When the actual impurity content of the grain is lower than the impurity content specified by the standard, based on the impurity content specified by the standard, the grain increase is N% for every time the actual impurity content is lower than a first numerical point. When the actual impurity content of the grain is higher than the impurity content specified by the standard, based on the impurity content specified by the standard, the grain deduction is K% for every time the actual impurity content is higher than a first numerical point. K is greater than or equal to 1.

10. A full-process monitoring and management system for a grain reserve, wherein video monitoring units are installed at multiple locations in each link of the grain reserve process, for implementing the method according to any one of claims 1 to 9, characterized in that: The system includes the following modules: A registration unit is used to register the grain transport vehicle when it passes through the gate, identify and save the grain sale information, and produce an IC card containing the grain sale information based on the grain sale information. At the same time, the first video monitoring unit shoots a video of the grain transport vehicle entering the warehouse as the first video; The quality inspection unit is used for, at the sampling quality inspection location, the second video monitoring unit shoots the video of the sampling quality inspection of the grain transport vehicle as the second video, performs quality inspection on the grain carried by the grain transport vehicle and obtains the quality inspection result, writes the quality inspection result into the IC card, determines whether the quality inspection result is qualified, grants the IC card the right to enter the warehouse if it is qualified, and executes the metering unit; The metering unit is used for the grain transport vehicle to enter the gross weight measurement link and perform the first weight inspection. The third video monitoring unit shoots the video of the gross weight measurement of the grain transport vehicle as the third video. During the shooting of the third video, the analysis unit also analyzes the third video. When a violation is detected in the third video, an early warning message is issued, and the staff is reminded to adjust the grain transport vehicle. After the gross weight measurement of the grain transport vehicle is passed, the IC card is updated; The verification unit is used to verify the grain truck and the IC card, and allows the grain truck to enter the warehouse for unloading after the verification is passed. At the unloading and peeling place of the warehouse, the fourth video monitoring unit shoots the video of the grain truck unloading and peeling as the fourth video, and also analyzes the fourth video. When the recognition result in the fourth video is consistent with the quality inspection result recorded in the IC card, the grain truck is unloaded normally. After the second weight inspection, the increase and deduction of the grain is calculated, and the grain sales result is calculated. Otherwise, the grain truck is stopped from unloading, and an early warning message is issued to notify the staff to re-inspect the grain carried by the grain truck; The monitoring unit is used for the fifth video monitoring unit to monitor the warehouse in real time and record the process of grain condition detection, mechanical ventilation and fumigation. The sixth video monitoring unit shoots the whole process of grain leaving the warehouse, wherein each of the video records includes the video shooting time and is periodically uploaded to the monitoring center, which is uniformly stored and processed by the monitoring center.

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