Intelligent logistics solution system based on big data and block chain

Abstract

The invention discloses an intelligent logistics solution system based on big data and a block chain, and the system comprises a three-dimensional model building module, a three-dimensional model region division module, and a label and positioning module, and is characterized in that the three-dimensional model building module is used for obtaining the internal structure of a warehouse through a camera device, and building a three-dimensional model; the three-dimensional model region division module is used for realizing region division and cargo placement through a three-dimensional model; the labeling and positioning module is used for realizing rapid positioning of goods by placing labels, the labeling and positioning module comprises an article identification and label generation module, a label attaching and updating module and a visual interface and real-time interaction module, the label attaching and updating module is used for attaching generated labels to corresponding articles, and the visual interface and real-time interaction module is used for carrying out real-time interaction on the corresponding articles. The method and the system have the advantages that the space utilization rate and the operation efficiency of the warehouse are improved.

Description

Technical Field

[0001] The present invention relates to the field of warehouse management technology, and specifically to an intelligent logistics solution system based on big data and blockchain. Background Art

[0002] Currently, warehouse management suffers from irrationalities in zoning and locating goods, leading to wasted space and inefficient locating. Traditional warehouse management systems primarily rely on manual division of warehouse areas, then numbering or labeling each area to locate and manage goods. However, this approach has significant drawbacks that limit the efficiency and precision of warehouse management. First, traditional warehouse zoning is typically based on static, pre-set standards, lacking the flexibility to accommodate goods of varying sizes, shapes, and quantities. This results in significant wasted space, with some areas being wasted due to small size, while others may be unable to accommodate larger items. Second, due to the dynamic nature of goods, traditional warehouse management systems struggle to adapt quickly to changes in goods, especially with high-frequency warehousing and outbound operations, making it difficult to maintain a rational zoning system. This leads to inconvenience in locating goods, requiring workers to expend considerable time and effort maneuvering and searching for goods within the warehouse, reducing operational efficiency.

[0003] To sum up, the current warehouse management technology has obvious problems of unreasonable area division and inconvenience in finding goods. There is an urgent need for a more intelligent and flexible management system to improve warehouse space utilization and operational efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent logistics solution system based on big data and blockchain to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent logistics solution system based on big data and blockchain, comprising a three-dimensional model building module, a three-dimensional model area division module and a label and positioning module, characterized in that: the three-dimensional model building module is used to obtain the internal structure of the warehouse through a camera device and construct a three-dimensional model, the three-dimensional model area division module is used to realize area division and cargo placement through a three-dimensional model, the label and positioning module is used to realize rapid positioning of cargo by placing labels, and the three-dimensional model building module, the three-dimensional model area division module and the label and positioning module are electrically connected to each other.

[0006] According to the above technical solution, the three-dimensional model establishment module includes a camera device module, an image processing and feature extraction module, and a three-dimensional reconstruction module. The camera device module is used to arrange a high-resolution, wide-angle lens camera device inside the warehouse to obtain the structure and item information in the warehouse in all directions. The image processing and feature extraction module is used to extract features from the images obtained by the camera device, including the extraction of edges and corner points, to provide basic data for subsequent image matching and three-dimensional reconstruction. The three-dimensional reconstruction module is used to convert the key points extracted from the image into three-dimensional coordinates based on the results of feature extraction using triangulation to generate a three-dimensional model of the interior of the warehouse.

[0007] According to the above technical solution, the three-dimensional model area division module includes an area division module, a storage path planning module and an intelligent storage module. The area division module is used to divide the warehouse space based on the established three-dimensional model to ensure the rational use of space and select suitable areas for storage according to the size of the goods. The storage path planning module is used to plan the optimal storage path based on the selected storage area using a graph theory algorithm to minimize the transportation distance and time of the goods. The intelligent storage module is used to intelligently store goods according to the area division and path planning results, maximize the use of warehouse space, and improve storage efficiency.

[0008] According to the above technical solution, the labeling and rapid positioning module includes an item identification and label generation module, a label attachment and update module, and a visualization interface and real-time interaction module. The item identification and label generation module is used to use the object recognition algorithm to perform real-time identification of different areas and goods, and generate labels containing product name, volume, and weight. The label attachment and update module is used to attach the generated labels to the corresponding items and ensure that they are consistent with the position in the three-dimensional model. As the goods change, the label information is updated in time. The visualization interface and real-time interaction module is used to provide a visualization interface, display the three-dimensional model and item labels, and allow workers to interact with the three-dimensional model in real time through the interface to obtain detailed information about the goods and track their movement history.

[0009] According to the above technical solution, the operation method of the intelligent logistics solution system mainly includes the following steps: Step S1: Acquire the warehouse structure through a camera device to establish a three-dimensional model; Step S2: Divide the area based on the three-dimensional model and place the goods; Step S3: labeling different areas and goods to achieve rapid positioning of goods; Step S4: Record the goods in and out of the warehouse on the blockchain to achieve tracking and tracing of the goods.

[0010] According to the above technical solution, step S1 further includes the following steps: Step S11: Install high-resolution, wide-angle camera devices in the warehouse. Use these cameras to capture images of every corner of the warehouse, including goods, shelves, and equipment. The captured images are then uploaded to the system. For each image, the system uses a feature extraction algorithm to extract key points and their descriptors from the image. Subsequently, a descriptor-based matching algorithm is used to determine the corresponding key points in the two images, thereby establishing an association between different images. Step S12: For the matched key point pairs, false matches are eliminated through visual geometric verification. By using the RANSAC algorithm, the basic matrix or essential matrix is ​​calculated to verify whether the matched key point pairs meet the geometric constraints. Finally, the three-dimensional coordinates on the object surface are calculated using the matched key point pairs using camera calibration parameters and triangulation. Then, all the calculated three-dimensional coordinates are integrated to form a three-dimensional point cloud of the object. Through the three-dimensional point cloud, a three-dimensional reconstruction algorithm is used to generate a complete three-dimensional model of the object.

[0011] According to the above technical solution, step S2 further includes the following steps: Step S21: The system divides the three-dimensional space inside the warehouse into different areas. The system divides the space based on the density of the goods and the size of the area. The system then measures the volume of each item to be stored. The system selects the appropriate area for storage based on the volume of the goods and the availability of space inside the warehouse. Step S22: The system follows the principle of maximizing the use of warehouse space and avoiding regional congestion, and plans the optimal storage path according to the selected storage area to minimize the transportation distance and time of the goods.

[0012] According to the above technical solution, step S3 further includes the following steps: S31: Uses the YOLO target detection algorithm to achieve real-time object recognition. The system then generates a label containing the product name, volume, and weight for each successfully identified item. The generated label is attached to the corresponding item via a QR code or RFID. S32: The system provides a visual interface that displays the three-dimensional model and the labels of items in the corresponding area. Through the visual interface, workers can interact with the three-dimensional model in real time and obtain detailed information about the items, such as product name, volume, and weight, by clicking on the labels or using handheld devices. They can also track the movement history of the goods.

[0013] According to the above technical solution, step S4 further includes the following steps: Step S41: Implement a smart contract in the blockchain, and specify key information about the goods in the contract, including but not limited to the type, quantity, volume, weight, and entry and exit times of the goods. This information is stored in each block of the blockchain. Each time a goods entry or exit operation occurs, the relevant information is encapsulated into a new block and verified through the smart contract. After verification, the block will be added to the blockchain. By querying the blockchain, the complete historical record of the goods from entering the warehouse to leaving can be obtained, including the timestamp and related details of each operation.

[0014] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in step one, the present invention obtains the warehouse structure through a camera device to realize the establishment of a three-dimensional model, and provides accurate basic data for the subsequent intelligent management system on this basis; in step two, area division is carried out based on the three-dimensional model and goods are placed, and area selection and storage path planning are realized through intelligent algorithms to maximize the use of warehouse space and improve storage efficiency; then, in step three, by labeling different areas and goods, rapid positioning of goods is realized, and target detection algorithms and label generation technology are used to generate labels containing product name, volume, weight and other information for each item, providing a visual interface for workers to interact in real time, ensuring data consistency, and improving the efficiency and accuracy of logistics operations; finally, in step four, the goods in and out of the warehouse operations are recorded on the blockchain to realize the tracking and traceability of the goods, and the security and non-tamperability of the data are ensured through smart contracts and identity authentication mechanisms, providing reliable technical support for full-process tracking and traceability, and improving the transparency and security of the entire logistics system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See also Figure 1The present invention provides a technical solution: an intelligent logistics solution system based on big data and blockchain, comprising a three-dimensional model building module, a three-dimensional model area division module, and a labeling and positioning module, characterized in that: the three-dimensional model building module is used to obtain the internal structure of the warehouse through a camera device and construct a three-dimensional model; the three-dimensional model area division module is used to implement area division and cargo placement through the three-dimensional model; the labeling and positioning module is used to achieve rapid positioning of cargo by placing labels; the three-dimensional model building module, the three-dimensional model area division module, and the labeling and positioning module are electrically connected to each other; The 3D model building module includes a camera module, an image processing and feature extraction module, and a 3D reconstruction module. The camera module is used to arrange a high-resolution, wide-angle camera inside the warehouse to obtain all-round information about the structure and items inside the warehouse. The image processing and feature extraction module is used to extract features from the images captured by the camera, including extraction of edges and corners, to provide basic data for subsequent image matching and 3D reconstruction. The 3D reconstruction module is used to convert key points extracted from the images into 3D coordinates using triangulation based on the feature extraction results to generate a 3D model of the warehouse interior. The 3D model area division module includes an area division module, a storage path planning module, and an intelligent storage module. The area division module is used to divide the warehouse space based on the established 3D model to ensure rational use of space and select appropriate areas for storage according to the volume of the goods. The storage path planning module is used to plan the optimal storage path based on the selected storage area using a graph theory algorithm to minimize the distance and time of goods transportation. The intelligent storage module is used to intelligently store goods based on the area division and path planning results, maximize the use of warehouse space, and improve storage efficiency. The labeling and rapid positioning module includes an item identification and label generation module, a label attachment and update module, and a visualization interface and real-time interaction module. The item identification and label generation module is used to use the object recognition algorithm to perform real-time identification of different areas and goods, and generate labels containing product name, volume, and weight. The label attachment and update module is used to attach the generated labels to the corresponding items and ensure that they are consistent with the position in the three-dimensional model. As the goods change, the label information is updated in a timely manner. The visualization interface and real-time interaction module is used to provide a visualization interface, display the three-dimensional model and item labels, and allow workers to interact with the three-dimensional model in real time through the interface to obtain detailed information about the goods and track their movement history.

[0018] The operation method of the intelligent logistics solution system mainly includes the following steps: Step S1: Acquire the warehouse structure through a camera device to establish a three-dimensional model; Step S2: Divide the area based on the three-dimensional model and place the goods; Step S3: labeling different areas and goods to achieve rapid positioning of goods; Step S4: Record the goods in and out of the warehouse on the blockchain to achieve tracking and tracing of the goods.

[0019] Step S1 further includes the following steps: Step S11: Install high-resolution, wide-angle camera devices in the warehouse. Use these cameras to capture images of every corner of the warehouse, including goods, shelves, and equipment. The captured images are then uploaded to the system. For each image, the system uses a feature extraction algorithm to extract key points and their descriptors from the image. Subsequently, a descriptor-based matching algorithm is used to determine the corresponding key points in the two images, thereby establishing an association between different images. Step S12: For the matched key point pairs, false matches are eliminated through visual geometric verification. By using the RANSAC algorithm, the basic matrix or the essential matrix is ​​calculated to verify whether the matched key point pairs meet the geometric constraints. Finally, the three-dimensional coordinates on the surface of the object are calculated using the matched key point pairs using the camera calibration parameters and the triangulation method. Then, all the calculated three-dimensional coordinates are integrated to form a three-dimensional point cloud of the object. The three-dimensional point cloud is used to generate a complete three-dimensional model of the object using a three-dimensional reconstruction algorithm. Step S2 further includes the following steps: Step S21: Based on the 3D model of the warehouse interior, the system performs area division. The system divides the 3D space inside the warehouse into different areas. When dividing, the system divides the space according to the density of the goods and the size of the area. Then, the system measures the volume of each item to be stored. The system selects the appropriate area for storage based on the volume of the goods and the availability of the area inside the warehouse. Step S22: The system follows the principle of maximizing the use of warehouse space and avoiding regional congestion, and plans the optimal storage path according to the selected storage area to minimize the transportation distance and time of the goods.

[0020] Step S3 further includes the following steps: S31: Uses the YOLO object detection algorithm to achieve real-time object recognition. The system then generates a label for each successfully identified item containing information such as product name, volume, and weight. This information can be obtained from a database or measured in real time by sensors. The generated label is attached to the corresponding item using technologies such as QR codes and RFID to ensure that it is aligned with the position in the 3D model. S32: When new goods enter the warehouse or existing goods are moved, the label information needs to be updated accordingly. In addition, the system provides a visual interface that displays the three-dimensional model and the item labels in the corresponding area. Through the visual interface, workers can interact with the three-dimensional model in real time. By clicking on the label or using a handheld device, they can obtain detailed information about the item, such as product name, volume, weight, etc., and can track the movement history of the goods, integrate the labeled three-dimensional model into the system, ensure that the label information is synchronized with other system information, and maintain data consistency. Such a system improves the efficiency of logistics operations, reduces human errors, and ensures the accuracy of goods management.

[0021] Step S4 further includes the following steps: Step S41: A smart contract is implemented in the blockchain, which stipulates the key information of the goods, including but not limited to the type, quantity, volume, weight, entry and exit time of the goods. This information will be stored in each block of the blockchain, and an effective identity authentication mechanism will be implemented to ensure that only authorized participants can submit new blocks. Each time the goods are entered or exited, the relevant information will be encapsulated into a new block and verified through the smart contract. After the verification is passed, the block will be added to the blockchain to form an unalterable record. The characteristics of the blockchain enable each entry and exit operation to be tracked and traced throughout the network. By querying the blockchain, a complete historical record of the goods from entering the warehouse to leaving can be obtained, including the timestamp and related details of each operation. The decentralization and consensus mechanism of the blockchain are used to ensure the consistency and non-tamperability of the data. Each participant has a complete copy of the blockchain, and the synchronization of all copies is guaranteed by the consensus algorithm.

[0022] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0023] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An intelligent logistics solution system based on big data and blockchain, including a 3D model building module, a 3D model area division module, and a labeling and positioning module, characterized by: The three-dimensional model building module is used to obtain the internal structure of the warehouse through a camera device and construct a three-dimensional model. The three-dimensional model area division module is used to realize area division and cargo placement through the three-dimensional model. The label and positioning module is used to realize rapid positioning of cargo by placing labels. The three-dimensional model building module, the three-dimensional model area division module and the label and positioning module are electrically connected to each other.

2. The intelligent logistics solution system based on big data and blockchain according to claim 1 is characterized by: The three-dimensional model establishment module includes a camera device module, an image processing and feature extraction module, and a three-dimensional reconstruction module. The camera device module is used to arrange a high-resolution, wide-angle lens camera device inside the warehouse to obtain all-round structural and item information inside the warehouse. The image processing and feature extraction module is used to extract features from the images captured by the camera device, including extraction of edges and corner points, to provide basic data for subsequent image matching and three-dimensional reconstruction. The three-dimensional reconstruction module is used to convert the key points extracted from the image into three-dimensional coordinates based on the results of feature extraction using triangulation to generate a three-dimensional model of the interior of the warehouse.

3. The intelligent logistics solution system based on big data and blockchain according to claim 2 is characterized by: The three-dimensional model area division module includes an area division module, a storage path planning module and an intelligent storage module. The area division module is used to divide the warehouse space based on the established three-dimensional model to ensure the rational use of space and select suitable areas for storage according to the size of the goods. The storage path planning module is used to plan the optimal storage path based on the selected storage area using a graph theory algorithm to minimize the transportation distance and time of the goods. The intelligent storage module is used to intelligently store goods based on the area division and path planning results, maximize the use of warehouse space, and improve storage efficiency.

4. The intelligent logistics solution system based on big data and blockchain according to claim 3 is characterized by: The labeling and rapid positioning module includes an item identification and label generation module, a label attachment and update module, and a visualization interface and real-time interaction module. The item identification and label generation module is used to use an object recognition algorithm to perform real-time identification of different areas and goods, and generate labels containing product name, volume, and weight. The label attachment and update module is used to attach the generated labels to the corresponding items and ensure that they are consistent with the position in the three-dimensional model. As the goods change, the label information is updated in a timely manner. The visualization interface and real-time interaction module is used to provide a visualization interface, display the three-dimensional model and item labels, and allow workers to interact with the three-dimensional model in real time through the interface to obtain detailed information about the goods and track their movement history.

5. The intelligent logistics solution system based on big data and blockchain according to claim 4 is characterized by: The operation method of the intelligent logistics solution system mainly includes the following steps: Step S1: Acquire the warehouse structure through a camera device to establish a three-dimensional model; Step S2: Divide the area based on the three-dimensional model and place the goods; Step S3: labeling different areas and goods to achieve rapid positioning of goods; Step S4: Record the goods in and out of the warehouse on the blockchain to achieve tracking and tracing of the goods.

6. The intelligent logistics solution system based on big data and blockchain according to claim 5 is characterized by: The step S1 further comprises the following steps: Step S11: Install high-resolution, wide-angle camera devices in the warehouse. Use these cameras to capture images of every corner of the warehouse, including goods, shelves, and equipment. The captured images are then uploaded to the system. For each image, the system uses a feature extraction algorithm to extract key points and their descriptors from the image. Subsequently, a descriptor-based matching algorithm is used to determine the corresponding key points in the two images, thereby establishing an association between different images. Step S12: For the matched key point pairs, false matches are eliminated through visual geometric verification. By using the RANSAC algorithm, the basic matrix or essential matrix is ​​calculated to verify whether the matched key point pairs meet the geometric constraints. Finally, the three-dimensional coordinates on the object surface are calculated using the matched key point pairs using camera calibration parameters and triangulation. Then, all the calculated three-dimensional coordinates are integrated to form a three-dimensional point cloud of the object. Through the three-dimensional point cloud, a three-dimensional reconstruction algorithm is used to generate a complete three-dimensional model of the object.

7. The intelligent logistics solution system based on big data and blockchain according to claim 6 is characterized by: The step S2 further comprises the following steps: Step S21: The system divides the three-dimensional space inside the warehouse into different areas. The system divides the space based on the density of the goods and the size of the area. The system then measures the volume of each item to be stored. The system selects the appropriate area for storage based on the volume of the goods and the availability of space inside the warehouse. Step S22: The system follows the principle of maximizing the use of warehouse space and avoiding regional congestion, and plans the optimal storage path according to the selected storage area to minimize the transportation distance and time of the goods.

8. The intelligent logistics solution system based on big data and blockchain according to claim 7 is characterized by: The step S3 further comprises the following steps: S31: Uses the YOLO target detection algorithm to achieve real-time object recognition. The system then generates a label containing the product name, volume, and weight for each successfully identified item. The generated label is attached to the corresponding item via a QR code or RFID. S32: The system provides a visual interface that displays the three-dimensional model and the labels of items in the corresponding area. Through the visual interface, workers can interact with the three-dimensional model in real time and obtain detailed information about the items, such as product name, volume, and weight, by clicking on the labels or using handheld devices. They can also track the movement history of the goods.

9. The intelligent logistics solution system based on big data and blockchain according to claim 8 is characterized by: The step S4 further comprises the following steps: Step S41: Implement a smart contract in the blockchain, and specify key information about the goods in the contract, including but not limited to the type, quantity, volume, weight, and entry and exit times of the goods. This information is stored in each block of the blockchain. Each time a goods entry or exit operation occurs, the relevant information is encapsulated into a new block and verified through the smart contract. After verification, the block will be added to the blockchain. By querying the blockchain, the complete historical record of the goods from entering the warehouse to leaving can be obtained, including the timestamp and related details of each operation.

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