Low-temperature image recognition method applied to cold-chain industry

Abstract

The invention discloses a low-temperature image recognition method applied to the cold chain industry, and the method comprises the steps: obtaining first image information of a cargo through a security inspection machine, and carrying out the preprocessing of the first image information, so as to generate second image information with enhanced definition; determining cargo identification features according to the second image information, and comparing and matching the cargo identification features with cargo standard identification features in a preset database to confirm the identity of the cargo; carrying out position information recording on the goods of which the identities are confirmed, and associating the position information with the identities of the goods; in the cargo moving process, automatically triggering video monitoring equipment to capture third image information according to the position information; verifying goods identity information by using the third image information, and recording an operation process to form an operation record; through integration of operation records and a business management system, tracing of the whole process of cold chain cargo operation is realized. According to the invention, the problems of cargo identification and tracking in a low-temperature environment are solved, the identification precision is obviously improved, and the transparency and safety of cold-chain logistics operation are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of cold chain logistics monitoring, and specifically relates to a low-temperature image recognition method applied to the cold chain industry. Background Art

[0002] In the cold chain logistics industry, ensuring the safety and traceability of goods is crucial. Traditional methods of cargo inspection and tracking usually rely on manual operations, which are not only inefficient but also prone to human errors. With the development of technology, it is possible to use image recognition technology to improve the intelligence level of cold chain logistics. However, image recognition in low temperature environments faces many challenges, such as image quality degradation and feature blurring caused by frost on the surface of goods.

[0003] Existing image recognition methods are often unable to effectively extract clear features of goods in low-temperature environments, resulting in reduced recognition accuracy, which in turn affects the safety inspection and full traceability of goods. Summary of the invention

[0004] The purpose of the present invention is to provide a low-temperature image recognition method applied to the cold chain industry, which can significantly improve the recognition accuracy of goods under low-temperature conditions. By using a security inspection machine to obtain goods images and pre-process them, the clarity of the image can be enhanced, and the identification features of the goods can be accurately identified to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention adopts the following technical solution: a low temperature image recognition method applied to the cold chain industry, comprising the following steps:

[0006] Use a security inspection machine to obtain first image information of the goods to be inspected; pre-process the first image information to generate second image information with enhanced clarity; determine the goods identification features based on the second image information; compare and match the goods identification features with the standard goods identification features in a preset database to confirm the identity of the goods, record the location information of the goods after the identity is confirmed, and associate the location information with the identity of the goods; during the movement of the goods, automatically trigger the video surveillance equipment to capture third image information based on the location information; use the third image information to verify the identity information of the goods, and record the operation process, combine the operation process with the identity information of the goods to form an operation record; by integrating the operation record with the business management system, the entire operation process of cold chain goods can be traced.

[0007] Preferably, after using the security inspection machine to obtain the first image information of the goods to be inspected, it also includes: applying image enhancement means to the first image information to obtain an optimized image; extracting contour features of the goods from the optimized image, and comparing the contour features with data in a known goods contour feature library to identify the type of goods; recording the identification result of the goods type, and combining it with the location information of the goods, and updating the goods tracking database according to the identification result and the location information.

[0008] Preferably, the first image information is preprocessed to generate second image information with enhanced clarity, including: adjusting the brightness of the first image information to obtain an image with uniform brightness; performing denoising on the image after brightness adjustment to remove disordered pixels to obtain a pure image; using edge enhancement technology to enhance the boundaries of objects in the denoised image, and refining the shape of the goods according to the result of edge enhancement to obtain second image information with enhanced clarity; storing and marking the second image information with enhanced clarity for use in the process of goods identification and tracking.

[0009] Preferably, determining the cargo identification features based on the second image information includes: extracting significant visual elements of the cargo from the second image information with enhanced clarity as cargo identification features; establishing a feature template based on the cargo identification features for subsequent cargo comparison; using the feature template to match and confirm the cargo in the second image information to verify the identity of the cargo; based on the result of the match confirmation, recording the location information and timestamp of the cargo to maintain continuous tracking of the cargo in the cold chain logistics; integrating the location information and timestamp with other relevant information of the cargo to form a complete cargo tracking record for querying the cargo status at any time.

[0010] Preferably, the confirmation of the cargo identity comprises: searching for corresponding cargo standard identification features in a preset database according to the cargo identification features; comparing the cargo identification features with the found cargo standard identification features to confirm the identity of the cargo; if the cargo identification features match the cargo standard identification features, recording the cargo identity information; combining the cargo identity information with the cargo location information to form a cargo status record; and updating the cargo status record to the business management system to achieve real-time tracking of the cargo status.

[0011] Preferably, associating the location information with the identity of the goods includes: obtaining geographic coordinate information of the current location of the goods, combining the geographic coordinate information with the identity information of the goods to form a location identifier; associating the location identifier with the operation record of the goods to record the movement trajectory of the goods; updating the status information of the goods according to the location identifier to reflect the latest location of the goods, and synchronizing the status information of the goods to the business management system.

[0012] Preferably, the video surveillance device is automatically triggered to capture the third image information based on the location information, including: when the location information of the goods changes, the video surveillance device is triggered to start; the video surveillance device captures the real-time image of the environment around the goods according to the location information as the third image information; the third image information is saved and combined with the location information to form a dynamic monitoring record; the dynamic monitoring record is merged with the operation record of the goods to realize comprehensive monitoring of the goods movement process, and the merged record is sent to the business management system to realize real-time visualization of the goods movement process.

[0013] Preferably, using the third image information to verify the identity information of the goods includes: analyzing the goods features in the third image information to verify the identity information of the goods; comparing the goods features in the third image information with the identity information of the goods to confirm the consistency of the goods, and recording the comparison result; combining the comparison result with the operation record of the goods to form an operation verification record, and sending the operation verification record to the business management system to achieve traceability of the goods operation process.

[0014] Preferably, the operation process is combined with the identity information of the goods to form an operation record, including: integrating the operation verification record with the identity information of the goods to form operation record entries, arranging the operation record entries in chronological order to show the operation history of the goods; combining the operation record entries with the location information of the goods to form a comprehensive operation record, and updating the comprehensive operation record to the business management system; providing a query interface for the comprehensive operation record through the business management system to achieve transparent management of the goods operation process.

[0015] Preferably, the operation records are integrated with the business management system, including: integrating the comprehensive operation records with other relevant information in the business management system to form a complete cargo file; retrieving the operation records in the cargo file through the query function provided by the business management system; reconstructing the movement path and operation process of the cargo based on the timestamp and location information of the operation records; generating a full-process visualization report of the cargo from warehousing to delivery, and utilizing the full-process visualization report to achieve traceability and management of the entire cold chain cargo operation process.

[0016] Technical effects and advantages of the present invention: Compared with the prior art, the low-temperature image recognition method applied to the cold chain industry proposed by the present invention has the following advantages:

[0017] The present invention proposes a low-temperature image recognition method suitable for cold chain logistics, which can significantly improve the recognition accuracy of goods under low-temperature conditions. By using a security inspection machine to obtain the image of the goods and perform preprocessing, the clarity of the image can be enhanced, and the identification characteristics of the goods can be accurately identified. In addition, combined with video monitoring and business management systems, the operation record and traceability of the entire process from warehousing to outbound delivery of goods are realized, which improves the transparency and security of cold chain logistics operations. This method can effectively solve the problem of cargo identification and tracking in low-temperature environments and improve the efficiency and reliability of the entire cold chain management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is a flow chart of a low-temperature image recognition method applied to the cold chain industry. DETAILED DESCRIPTION

[0019] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0020] The present invention provides a low temperature image recognition method applied to the cold chain industry, such as Figure 1 As shown, the following steps are included:

[0021] Step 1: using a security inspection machine to obtain first image information of the goods to be inspected; further comprising:

[0022] Applying image enhancement means to the first image information to obtain an optimized image; extracting contour features of the goods from the optimized image, comparing the contour features with data in a known goods contour feature library to identify the type of goods; recording the identification result of the type of goods and combining it with the location information of the goods, and updating the goods tracking database according to the identification result and the location information.

[0023] Specifically, the first image information is obtained by using a security inspection machine: the first image information of the goods to be inspected is obtained by using security inspection machines installed at key locations in each link of the cold chain logistics. These security inspection machines can be fixed or mobile, and the appropriate type can be selected according to the actual application scenario.

[0024] The acquired first image information is preprocessed, including but not limited to image enhancement means such as brightness adjustment, denoising and edge enhancement, so as to improve the quality and clarity of the image.

[0025] Brightness adjustment: Make the details in the image more obvious by increasing the overall brightness or local brightness of the image.

[0026] Denoising: Use appropriate algorithms to remove noise from images and improve image purity.

[0027] Edge enhancement: The algorithm strengthens the boundaries of objects in the image, making the outline of the goods more clearly visible.

[0028] Extract the contour features of the goods from the preprocessed images. These features include the shape, size, texture, etc. of the goods for the subsequent recognition process. Use computer vision algorithms, such as edge detection algorithms and contour extraction algorithms, to automatically extract these features.

[0029] The extracted contour features are compared with the data in the pre-established known cargo contour feature library to identify the type of cargo. The feature library contains standard contour features of different types of cargo for comparison.

[0030] The identified type of goods is recorded and combined with the location information of the goods to form the status information of the goods. The location information of the goods can be obtained through RFID tags, GPS positioning or other location tracking technologies.

[0031] Update the cargo tracking database based on the cargo type identification results and location information to ensure that the database contains the latest cargo status information. This information will be used for subsequent cargo tracking and management.

[0032] Through the above steps, goods can be accurately identified and their location can be tracked in a low-temperature environment, improving the transparency and safety of cold chain logistics operations. This method significantly improves the accuracy of goods identification and, through integration with the business management system, enables visual management of the entire process from warehousing to delivery.

[0033] Step 2: preprocessing the first image information to generate second image information with enhanced definition;

[0034] Further including: adjusting the brightness of the first image information to obtain an image with uniform brightness; performing denoising on the image after brightness adjustment to remove disordered pixels to obtain a pure image; using edge enhancement technology to strengthen the boundary of the object in the denoised image, and refining the shape of the goods according to the result of edge enhancement to obtain a second image information with enhanced clarity; storing and marking the second image information with enhanced clarity for use in the process of goods identification and tracking. The details are as follows:

[0035] Adjust the brightness of the first image information: obtain the first image information captured by the security inspection machine.

[0036] Use image processing software or algorithms to adjust the brightness of the image to ensure uniform brightness across the entire image and improve overall image visibility. The brightness and contrast of the image can be adjusted automatically or manually. Considering the changing light conditions in low-temperature environments, it may be necessary to dynamically adjust the brightness to accommodate different lighting conditions.

[0037] De-noising the image after brightness adjustment: After brightness adjustment, denoise the image to remove random pixels in the image to reduce interference factors. Use appropriate denoising algorithms, such as median filtering, Gaussian filtering, or more complex deep learning-based methods to remove noise from the image.

[0038] Use edge enhancement technology to strengthen the boundaries of objects in the denoised image: Apply edge detection algorithms, such as Canny edge detection, Sobel operator, etc., to strengthen the boundaries of objects in the image. Edge enhancement helps to highlight the outline of the object, which is crucial for subsequent cargo shape recognition.

[0039] Refine the shape of the goods based on the results of edge enhancement: Based on the enhanced boundary information, refine the shape features of the goods to obtain a clearer and more accurate outline of the goods. Morphological operations (such as dilation and erosion) may be used to further optimize the outline.

[0040] Obtaining second image information with enhanced clarity: After the above steps, second image information with uniform brightness, denoised and clear edges is obtained. These processed images will serve as the basis for subsequent image analysis.

[0041] Store and mark the second image information with enhanced clarity: Save the processed second image information to the designated data storage area and mark it for subsequent identification and tracking. The mark can include information such as the source of the image, processing date and time, and processing steps to facilitate management and tracking.

[0042] Through the above steps, high-quality images can be obtained in a low-temperature environment, which provides a solid foundation for subsequent cargo identification and tracking. This image processing method helps to improve the clarity and contrast of the image, thereby improving the extraction of cargo identification features, and ultimately improving the safety and efficiency of the entire cold chain logistics process.

[0043] Step 3: determining the identification features of the goods according to the second image information;

[0044] Further comprising: extracting significant visual elements of the goods from the second image information with enhanced clarity as goods identification features; establishing a feature template based on the goods identification features for subsequent goods comparison; using the feature template to match and confirm the goods in the second image information to verify the identity of the goods; based on the result of the matching confirmation, recording the location information and timestamp of the goods to maintain continuous tracking of the goods in the cold chain logistics; integrating the location information and timestamp with other relevant information of the goods to form a complete goods tracking record for querying the status of the goods at any time.

[0045] The details are as follows:

[0046] Extracting the significant visual elements of the goods from the second image information with enhanced clarity: Using image processing technology and machine learning algorithms, extract the significant visual elements of the goods from the pre-processed second image information. These significant visual elements may include but are not limited to the color, shape, barcode, QR code, printed text, trademark pattern, etc. of the goods. Use feature detectors (such as SI FT, SURF, ORB, etc.) to locate these feature points and extract their descriptors.

[0047] Based on the identification features of the goods, a feature template is established: a feature template is constructed based on the extracted significant visual elements, and the template is used to describe the unique appearance features of the goods. The feature template can be a set of feature vectors, or a specific feature representation form, such as a hash table or a feature tree. In order to improve the accuracy of matching, multiple feature extraction methods can be used and combined to create a comprehensive feature template.

[0048] Using the feature template, matching and confirming the goods in the second image information: applying the feature template to the subsequently captured images to identify and confirm the identity of the goods. This process usually involves feature matching algorithms:

[0049] For example, FLANN (Fast Library for Approximate Nearest Ne i ghbors) or brute force matching algorithm. For each newly acquired image, its features are extracted and compared with the existing feature templates to find the closest match.

[0050] According to the result of the matching confirmation, the location information and timestamp of the goods are recorded: when the goods are successfully matched, the location coordinates of the goods in the current image and the timestamp of the captured image are recorded. The location information can be pixel coordinates or converted into actual spatial coordinates. The timestamp is used to record the moment when the goods are identified, which is very important for tracking the movement trajectory of the goods.

[0051] Integrate the location information and timestamp with other relevant information about the goods: Integrate the location information, timestamp and other relevant information about the goods (such as the goods ID, consignor information, destination, etc.). This information can be stored in a database or data structure for easy query and management.

[0052] Form a complete cargo tracking record for querying cargo status at any time: Establish a tracking system that can generate a complete cargo tracking record based on the above information. The tracking record should contain the complete path of the cargo from the starting point to the end point, including the status updates of all intermediate nodes. Users can query the system to obtain the current location of the cargo, the estimated arrival time, and other relevant information.

[0053] Through the above steps, image processing technology can be effectively used to identify and track goods, ensuring the continuity and safety of goods in the cold chain logistics process. Such a system can not only improve logistics efficiency, but also reduce human errors and increase the transparency of the entire supply chain.

[0054] Step 4: Compare and match the cargo identification features with the cargo standard identification features in the preset database to confirm the cargo identity, record the location information of the cargo after the identity is confirmed, and associate the location information with the cargo identity;

[0055] The above-mentioned confirmation of the identity of the goods further includes: searching for corresponding standard identification features of the goods in a preset database according to the identification features of the goods; comparing the identification features of the goods with the found standard identification features of the goods to confirm the identity of the goods; if the identification features of the goods match the standard identification features of the goods, recording the identity information of the goods; combining the identity information of the goods with the location information of the goods to form a record of the status of the goods; updating the record of the status of the goods to the business management system to realize real-time tracking of the status of the goods.

[0056] The above-mentioned associating the location information with the cargo identity further includes: obtaining the geographic coordinate information of the current location of the cargo, combining the geographic coordinate information with the cargo identity information to form a location identifier; associating the location identifier with the cargo operation record to record the cargo movement track; updating the cargo status information according to the location identifier to reflect the latest location of the cargo, and synchronizing the cargo status information to the business management system. The details are as follows:

[0057] According to the cargo identification features, the corresponding cargo standard identification features are searched in the preset database:

[0058] The cargo identification features extracted from the cargo image are input into a preset database for query. The preset database stores standard identification features of various cargoes, such as barcodes, QR codes, trademark patterns, colors, shapes, etc. The database query process may require the use of an efficient indexing mechanism to quickly locate similar feature templates.

[0059] Compare the cargo identification features with the found cargo standard identification features to confirm the cargo's identity:

[0060] The extracted cargo identification features are compared with the standard identification features stored in the database using a feature matching algorithm (such as FLANN or brute force matching algorithm). If the feature matching score exceeds a predetermined threshold, it is considered that a matching cargo has been found. Other information, such as the size and weight of the cargo, may also need to be combined to improve the accuracy of the match.

[0061] If the cargo identification features match the cargo standard identification features, the cargo identity information is recorded:

[0062] Once the identity of the goods is confirmed, the identity information of the goods is recorded, such as the goods number, batch number, production date, etc. The identity information can be directly obtained from the database or a pre-defined field.

[0063] The identity information of the goods is combined with the location information of the goods to form a goods status record:

[0064] Get the geographic coordinates of the cargo's current location, which can be obtained through GPS or other positioning technology. Combine the geographic coordinates with the cargo's identity information to form a location identifier. The location identifier should contain enough information to uniquely identify the cargo's current location.

[0065] The location identifier is associated with the operation record of the goods to record the movement track of the goods:

[0066] Record every movement operation of the goods, including loading, unloading, transportation, etc., and associate it with the location identifier. The operation record should include timestamp, operation type, operator information, etc. The movement track can help trace the historical location and status changes of the goods.

[0067] Update the status information of the goods according to the location identifier to reflect the latest location of the goods:

[0068] Update the cargo status information regularly or as needed to ensure that the latest recorded location is accurate. The status information should also include additional information such as the temperature condition of the cargo and whether it is damaged.

[0069] Synchronize the status information of the goods to the business management system:

[0070] Synchronize the status records of goods to the business management system to achieve real-time tracking of the status of goods. The business management system should have permission control functions to ensure that only authorized users can access sensitive information. Through the business management system, users can check the status, location and history of goods at any time.

[0071] Through the above steps, effective management and monitoring of goods in cold chain logistics can be achieved to ensure the safety and quality of goods. In addition, such a system can also help logistics companies improve efficiency, reduce losses, and meet customers' real-time tracking needs.

[0072] Step 5: During the movement of the goods, the video surveillance device is automatically triggered to capture the third image information according to the location information;

[0073] Further including: when the location information of the goods changes, the video monitoring device is triggered to start; the video monitoring device captures the real-time image of the environment around the goods according to the location information as the third image information; the third image information is saved and combined with the location information to form a dynamic monitoring record; the dynamic monitoring record is merged with the operation record of the goods to achieve comprehensive monitoring of the goods movement process, and the merged record is sent to the business management system to achieve real-time visualization of the goods movement process. The details are as follows:

[0074] When the location information of the goods changes, the video surveillance equipment is triggered to start:

[0075] Monitor the location information of the goods. Once the location information changes, it is considered that the goods have started to move. Use RFID tags, GPS positioning or other location tracking technologies to obtain the real-time location information of the goods. When the location information changes, send a trigger signal to the video surveillance device through the Internet of Things (I oT) technology or wireless communication protocols (such as Wi-Fi, Bluetooth, LoRaWAN, etc.).

[0076] The video surveillance device captures a real-time image of the surrounding environment of the cargo according to the location information as the third image information:

[0077] The video surveillance equipment starts immediately after receiving the trigger signal and captures real-time images of the environment around the cargo. These monitoring devices can be fixed-mounted cameras or mobile monitoring devices, such as drones or mobile robots with cameras. Image capture should ensure that the entire area around the cargo is covered to capture the complete environment.

[0078] The third image information is saved and combined with the location information to form a dynamic monitoring record:

[0079] The captured real-time images are stored locally or on a cloud server with timestamps and location information. Dynamic monitoring records should include but are not limited to image files, timestamps, location coordinates, etc. These records can be stored in a standard format for subsequent processing and retrieval.

[0080] The dynamic monitoring records are combined with the cargo operation records to achieve comprehensive monitoring of the cargo movement process:

[0081] Combine dynamic monitoring records with previously recorded cargo operation records (such as loading, unloading, transshipment, etc.). This creates a complete cargo movement history record, including cargo location changes, operation details, and their corresponding real-time images. The combined records should be able to clearly show the status and location of the cargo at every stage of the cold chain logistics process.

[0082] Send the combined records to the business management system to achieve real-time visualization of the cargo movement process:

[0083] The merged records are sent to the business management system through the network to ensure real-time update of the status and location information of the goods. The business management system should have a user-friendly interface so that managers can view the real-time location, historical trajectory and related operation records of the goods. Visualization functions such as map view and timeline view should be implemented to intuitively understand the status and movement of the goods.

[0084] Through the above steps, comprehensive monitoring and real-time visualization of the cargo movement process in cold chain logistics can be achieved, which helps to improve logistics efficiency, ensure cargo safety, and meet customers' real-time tracking needs for cargo status.

[0085] Step 6: Verify the identity information of the goods using the third image information, record the operation process, and combine the operation process with the identity information of the goods to form an operation record;

[0086] The above-mentioned use of the third image information to verify the identity information of the goods further includes: analyzing the goods characteristics in the third image information to verify the identity information of the goods; comparing the goods characteristics in the third image information with the identity information of the goods to confirm the consistency of the goods, and recording the comparison result; combining the comparison result with the operation record of the goods to form an operation verification record, and sending the operation verification record to the business management system to achieve traceability of the goods operation process.

[0087] The above-mentioned combining the operation process with the identity information of the goods to form an operation record further includes: integrating the operation verification record with the identity information of the goods to form an operation record entry, arranging the operation record entries in chronological order to show the operation history of the goods; combining the operation record entries with the location information of the goods to form a comprehensive operation record, updating the comprehensive operation record to the business management system; providing a query interface for the comprehensive operation record through the business management system to realize transparent management of the goods operation process. The details are as follows:

[0088] Analyze the cargo features in the third image information:

[0089] Analyze the cargo features in the third image information captured by the video surveillance equipment, which may include the cargo shape, color, barcode, QR code, etc. Use image processing algorithms, such as edge detection, color segmentation, etc., to extract these features.

[0090] Compare the features of the goods in the third image information with the identity information of the goods:

[0091] Compare the cargo features extracted from the third image information with the previously confirmed cargo identity information to verify the consistency of the cargo. Use a feature matching algorithm (such as SI FT, SURF, ORB, etc.) to compare the feature points in the image with the features recorded in the cargo identity information.

[0092] Record the comparison results:

[0093] Record the results of the comparison process, including the number of successfully matched feature points, matching scores, and other information. If any inconsistencies are found, they should also be recorded for subsequent analysis. Combine the comparison results with the operation records of the goods to form an operation verification record.

[0094] Integrate the comparison results with the cargo operation records:

[0095] Combine the comparison results with the cargo operation records to form an operation verification record. The operation record should include detailed information on cargo loading, unloading, transportation, etc.

[0096] Forming an Operation Verification Record:

[0097] The operation verification record should include the comparison results, the operation time and location of the goods, the operator's information, etc. The record should be clear and easy to access.

[0098] Send operation verification records to the business management system:

[0099] The operation verification records are sent to the business management system through the network to ensure real-time update of the status of the goods and the operation history. The business management system should support real-time update and storage of historical records.

[0100] Realize the traceability of cargo operation process:

[0101] The business management system should provide a query interface to allow users to query the operation records and comparison results of goods to achieve traceability of the goods operation process.

[0102] Integrate the operation verification record with the identity information of the goods to form an operation record entry:

[0103] Integrate the operation verification record with the identity information of the goods to form a detailed operation record entry. The operation record entry should include the identity information of the goods, operation records, comparison results, etc.

[0104] Arrange the operation record entries in chronological order to show the operation history of the goods:

[0105] Arrange the operation record entries in chronological order to form a historical record of the goods. In this way, the entire operation process from the goods entering the warehouse to leaving the warehouse can be clearly seen. Combine the operation record entries with the location information of the goods to form a comprehensive operation record: Combine the operation record entries with the location information of the goods to form a comprehensive operation record. The comprehensive operation record should include information such as the movement trajectory and location changes of the goods.

[0106] Update the comprehensive operation record to the business management system:

[0107] Update the comprehensive operation records to the business management system regularly or as needed to ensure the timeliness and accuracy of the records. Provide a query interface for the comprehensive operation records through the business management system to achieve transparent management of the cargo operation process: The business management system should provide an easy-to-use query interface so that users can easily query the comprehensive operation records of the cargo. The query interface should support multi-condition query, such as filtering information by time, location, operation type, etc.

[0108] Through the above steps, the comprehensive monitoring and real-time visualization of the cargo operation process in cold chain logistics can be achieved, which helps to improve logistics efficiency, ensure cargo safety, and meet customers' real-time tracking needs for cargo status. At the same time, such a system can also provide traceability of the cargo operation process, which helps to improve the transparency and reliability of the entire logistics chain.

[0109] Step 7: By integrating the operation records with the business management system, the whole process of cold chain cargo operation can be traced. Further steps include:

[0110] Integrate the comprehensive operation records with other relevant information in the business management system to form a complete cargo file; retrieve the operation records in the cargo file through the query function provided by the business management system; reconstruct the movement path and operation process of the cargo based on the timestamp and location information of the operation records; generate a full-process visualization report of the cargo from warehousing to delivery, and use the full-process visualization report to achieve traceability and management of the entire cold chain cargo operation process. The details are as follows:

[0111] Integrate the comprehensive operation records with other relevant information in the business management system to form a complete cargo file and collect relevant data:

[0112] Collect basic information about the goods, such as the name, specifications, production date, shelf life, etc. Integrate the comprehensive operation records obtained from step 6, including the operation record entries, location information, comparison results, etc. Obtain status information of the goods at different stages, such as environmental parameters such as temperature and humidity, and possible quality inspection reports.

[0113] Establish cargo files: Create a file for each cargo in the business management system and integrate all the relevant information collected above. The cargo file should have a good organizational structure so that the information is easy to find and manage.

[0114] Develop query function: Develop query function in the business management system to allow users to query cargo files according to different conditions. The query conditions can include cargo number, batch number, operation date range, etc.

[0115] Retrieve operation records: Users can enter the corresponding conditions through the query function to retrieve the operation records of specific goods. The query results should display all operation record entries of the goods, including timestamp, operation type, operator and other information.

[0116] Reconstruct movement paths: Use the timestamp and location information in the operation records to draw the movement path of goods in the supply chain. GIS (Geographic Information System) technology can be used to assist in building a visual display of the movement path.

[0117] Reconstruct the operation process: According to the chronological order and specific content of the operation records, sort out the complete operation process from the goods entering the warehouse to leaving the warehouse. It should include the operation of all key nodes, such as receiving, storing, picking, packaging, shipping, etc.

[0118] Design a visual report template: Design a template that shows the entire operation process and movement path of the goods. The report template should include charts, maps and other graphical elements to visually display the information.

[0119] Generate visual report: Use the above data and information to automatically generate a visual report of the entire process. The report should include the operation flow chart of the goods, the movement path map, the timeline of important operations, etc.

[0120] Traceability management: With the full visual report, you can clearly understand the status of goods in every link of the supply chain. Once any problem occurs, you can quickly locate the specific time and place of the problem and take appropriate measures.

[0121] Optimized management: Based on the full-process visual report, potential problem points and improvement opportunities can be identified to help optimize the overall process. Improvement plans can be formulated for certain links where problems frequently occur to improve the efficiency and quality of the entire cold chain process.

[0122] Through the above steps, the effective traceability and management of the entire cold chain cargo operation process can be achieved. Specifically, the business management system can not only store and manage detailed information on the cargo, but also provide powerful query and analysis functions to help managers grasp the status of the cargo in real time, discover problems in time and respond quickly. In addition, the full-process visual report plays an important role in improving the transparency of the entire supply chain, enhancing customer trust, and reducing risks. Such a system not only helps to meet regulatory requirements, but also helps companies improve operational efficiency and service levels.

[0123] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A low-temperature image recognition method applied to the cold chain industry, characterized in that: The following steps are involved: Using a security inspection machine to obtain first image information of the goods to be inspected; Preprocessing the first image information to generate second image information with enhanced definition; determining a cargo identification feature according to the second image information; Compare and match the cargo identification features with the cargo standard identification features in a preset database to confirm the cargo identity, record the location information of the cargo after the identity is confirmed, and associate the location information with the cargo identity; During the movement of the goods, automatically triggering the video surveillance device to capture the third image information according to the location information; Verifying the identity information of the goods by using the third image information, and recording the operation process, combining the operation process with the identity information of the goods to form an operation record; By integrating the operation records with the business management system, the entire cold chain cargo operation process can be traced.

2. A low temperature image recognition method applied to the cold chain industry according to claim 1, characterized in that: After using the security inspection machine to obtain the first image information of the goods to be inspected, the method further includes: Applying an image enhancement method to the first image information to obtain an optimized image; Extracting contour features of the goods from the optimized image, and comparing the contour features with data in a known goods contour feature library to identify the type of the goods; The identification result of the cargo type is recorded and combined with the location information of the cargo, and the cargo tracking database is updated according to the identification result and the location information.

3. A low temperature image recognition method applied to the cold chain industry according to claim 2, characterized in that: Preprocessing the first image information to generate second image information with enhanced definition includes: Adjusting the brightness of the first image information to obtain an image with uniform brightness; De-noising is performed on the image after brightness adjustment to remove disordered pixels and obtain a pure image. Using edge enhancement technology to strengthen the boundary of the object in the denoised image, and refining the shape of the goods according to the result of edge enhancement to obtain second image information with enhanced clarity; The second image information with enhanced clarity is stored and marked for use in cargo identification and tracking processes.

4. A low-temperature image recognition method applied to the cold chain industry according to claim 3, characterized in that: Determining the identification feature of the goods according to the second image information includes: Extracting significant visual elements of the goods from the second image information with enhanced clarity as identification features of the goods; Based on the cargo identification features, a feature template is established for subsequent cargo comparison; Using the feature template, matching and confirming the goods in the second image information to verify the identity of the goods; According to the result of the matching confirmation, the location information and timestamp of the goods are recorded to maintain the continuous tracking of the goods in the cold chain logistics; The location information and timestamp are integrated with other relevant information of the goods to form a complete cargo tracking record for querying the status of the goods at any time.

5. A low temperature image recognition method applied to the cold chain industry according to claim 4, characterized in that: The confirmation of the cargo identity includes: According to the cargo identification feature, searching for the corresponding cargo standard identification feature in a preset database; Comparing the cargo identification features with the found cargo standard identification features to confirm the identity of the cargo; If the cargo identification feature matches the cargo standard identification feature, the cargo identity information is recorded; The identity information of the goods is combined with the location information of the goods to form a goods status record; the goods status record is updated to the business management system to achieve real-time tracking of the goods status.

6. A low temperature image recognition method applied to the cold chain industry according to claim 5, characterized in that: Associating the location information with the cargo identity includes: Obtaining geographic coordinate information of the current location of the cargo, and combining the geographic coordinate information with the identity information of the cargo to form a location identifier; The location identifier is associated with the operation record of the goods to record the movement trajectory of the goods; the status information of the goods is updated according to the location identifier to reflect the latest location of the goods, and the status information of the goods is synchronized to the business management system.

7. A low temperature image recognition method applied to the cold chain industry according to claim 6, characterized in that: Automatically triggering a video surveillance device to capture third image information according to the location information includes: When the location information of the goods changes, the video monitoring device is triggered to start; The video monitoring device captures a real-time image of the surrounding environment of the cargo according to the location information as the third image information; Saving the third image information and combining it with the location information to form a dynamic monitoring record; The dynamic monitoring records are combined with the cargo operation records to achieve comprehensive monitoring of the cargo movement process, and the combined records are sent to the business management system to achieve real-time visualization of the cargo movement process.

8. A low-temperature image recognition method applied to the cold chain industry according to claim 7, characterized in that: Verifying the identity information of the goods using the third image information includes: Analyzing features of the goods in the third image information to verify identity information of the goods; Comparing the features of the goods in the third image information with the identity information of the goods, confirming the consistency of the goods, and recording the comparison result; The comparison result is combined with the operation record of the goods to form an operation verification record, and the operation verification record is sent to the business management system to achieve traceability of the goods operation process.

9. A low temperature image recognition method applied to the cold chain industry according to claim 8, characterized in that: The operation process is combined with the identity information of the goods to form an operation record, including: Integrate the operation verification record with the identity information of the goods to form operation record entries, and arrange the operation record entries in chronological order to display the operation history of the goods; combining the operation record entries with the location information of the goods to form a comprehensive operation record, and updating the comprehensive operation record to the business management system; The business management system provides a query interface for the comprehensive operation records to achieve transparent management of the cargo operation process.

10. A low temperature image recognition method applied to the cold chain industry according to claim 9, characterized in that: By integrating the operation record with the business management system, including: Integrate the comprehensive operation records with other relevant information in the business management system to form a complete cargo file; Retrieving the operation records in the cargo file through the query function provided by the business management system; Reconstructing the movement path and operation process of the goods based on the timestamp and location information of the operation record; Generate a visual report of the entire process from the goods entering the warehouse to leaving the warehouse, and use the visual report to achieve traceability and management of the entire process of cold chain goods operation.

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