Intelligent express sorting machine system and sorting method based on'end-edge-cloud 'collaboration

Abstract

The invention discloses an intelligent express sorting machine system based on'end-edge-cloud 'cooperation and a sorting method, and relates to the technical field of logistics automation. According to the system, the multi-mode recognition device, the intelligent self-adaptive regulation and control device, the equipment connection and management module, the self-adaptive sorting execution mechanism and the logistics data intelligent analysis system work cooperatively. The multi-modal identification device integrates image identification and radio frequency identification technologies, so that the parcel identification accuracy is improved; the intelligent self-adaptive regulation and control device monitors and adjusts the working states of the conveyor belt and the sorting port in real time; the equipment connection and management module realizes deep connection between the equipment and the cloud, thereby facilitating remote monitoring and management; the self-adaptive sorting execution mechanism flexibly processes different types of packages; and the logistics data intelligent analysis system mines data value to optimize operation. The problems that an existing express sorting technology is low in efficiency, poor in accuracy, weak in adaptability and the like are solved, efficient, accurate and intelligent express sorting is achieved, and the requirements of the modern logistics industry are met.

Description

Technical Field

[0001] The present invention relates to the field of logistics automation technology, and in particular to an intelligent express sorting machine system and a sorting method based on "end-edge-cloud" collaboration. Background Art

[0002] With the rapid development of the e-commerce industry, express delivery business has seen explosive growth. According to relevant statistics, express delivery business volume continues to grow significantly. Traditional express delivery sorting methods rely primarily on manual operations, which are not only inefficient, prone to errors, and have high labor costs.

[0003] Large express delivery and sorting centers process tens of thousands, or even hundreds of thousands, of parcels daily. Manual identification and sorting, one by one, requires long, intensive hours, easily leading to fatigue and increased sorting errors. Furthermore, manual sorting costs represent a significant expense for logistics companies.

[0004] Later, some automated sorting equipment emerged, such as simple conveyor belt sorters, which used fixed scanners to identify express delivery label information and then routed packages to the appropriate sorting slots based on pre-set rules. However, these devices had many limitations.

[0005] On the one hand, its recognition capabilities are limited. It is often unable to accurately identify express parcels with blurred, damaged, or irregularly pasted labels, resulting in misclassification or omission of parcels, affecting the accuracy and timeliness of logistics distribution. On the other hand, existing automated sorting equipment lacks intelligent control capabilities, and the speed of the conveyor belt is usually fixed. When packages are unevenly weighted or stacked, it is easy to cause mechanical vibration, affecting the accuracy of sorting and the stability of the equipment. It may also cause equipment failure and increase maintenance costs. Moreover, most of these devices operate independently and lack effective connection to the cloud. Real-time data upload and remote monitoring and management are impossible, making it difficult to meet the needs of logistics companies for real-time monitoring and remote control of equipment operating status.

[0006] Furthermore, traditional express sorting equipment has poor adaptability when dealing with packages of varying types, sizes, and weights. For example, existing sorting equipment may be unable to properly handle unusually shaped or overweight packages, requiring manual secondary sorting. This undoubtedly increases the complexity and time cost of the sorting process, reducing logistics efficiency. Furthermore, traditional sorting equipment has weak data collection and analysis capabilities, making it unable to conduct in-depth mining of logistics data and unable to meet the demands of modern logistics for intelligent and refined management. In today's logistics industry, which pursues efficiency, precision, and intelligence, existing express sorting technology can no longer meet the growing business needs, and a more advanced and intelligent express sorting solution is urgently needed.

[0007] The patent with publication number CN109961242A discloses a logistics plan determination method and device, including: obtaining product information corresponding to the goods, and determining the logistics plan corresponding to the goods based on the logistics attributes, logistics categories and logistics plan correspondence of the goods, accurately determining the logistics attributes of newly-entered goods through massive historical data, and determining a preset logistics plan based on the logistics attributes, to solve the technical problem that the accuracy of manual identification of product attributes in the existing technology is poor, and when facing large-scale product distribution, a high rate of damage to the products will occur during the distribution process. The existing shortcomings of this technology are: a large amount of product information needs to be entered into the database, which increases the tediousness of manual labor in another way.

[0008] Patent publication number CN102974548A provides an automatic sorting machine, a control method, and a control device thereof, which can extend the service life of the automatic sorting machine and reduce its power consumption. The control method of the automatic sorting machine includes: detecting the number of parcels to be sorted on the conveyor line of the automatic sorting machine; when the number reaches a preset value, starting the automatic sorting machine for sorting. The existing shortcomings of this technology are: when the number of express parcels is small or in a small sorting center, the suspension of the automatic sorting machine will cause the delivery time of the express parcels to be extended, and the express parcel sorting machine is large in size and requires more funds to deploy. Summary of the Invention

[0009] The purpose of this invention is to provide an intelligent express sorting machine system and sorting method based on "end-edge-cloud" collaboration to solve the problems of low efficiency, poor accuracy, weak adaptability and lack of intelligent management of existing express sorting technology, and to achieve efficient, accurate and intelligent express sorting to meet the needs of the modern logistics industry.

[0010] To achieve the above objectives, the present invention adopts the following technical solutions.

[0011] An intelligent express sorting machine system based on "end-edge-cloud" collaboration includes the following devices.

[0012] This multimodal recognition device integrates an image recognition module and an RFID recognition module. When a package enters the sorting process, it first passes through the RFID recognition area. If the package is tagged with an RFID tag, the RFID recognition module quickly reads the tag's logistics information, including the delivery address and courier type, and transmits the data to the central control system.

[0013] Preferably, if the RFID tag is not detected or the reading fails, the package enters the image recognition area. The image recognition module uses a high-definition camera to capture images of the package from multiple angles. The image recognition algorithm, based on a deep learning model, analyzes the package face label area and overall appearance features. The algorithm first locates the face label. If the face label is blurred or damaged, the text information is repaired by analyzing the text outline and color features and comparing it with standard face label samples in the database. At the same time, the overall appearance of the package, such as shape, color, and special markings, is extracted and matched with a massive package sample library to further confirm the package information. The identified information is also transmitted to the central control system.

[0014] The intelligent adaptive control device features weight sensors, dimension sensors, and position sensors at regular intervals along the entire conveyor belt. Speed ​​and acceleration sensors are also installed at the conveyor belt drive motor. The weight sensor monitors the package weight in real time, the dimension sensor uses laser ranging and other technologies to obtain the package's length, width, and height, and the position sensor determines the package's position on the conveyor belt. These sensor data are transmitted in real time to the intelligent control unit.

[0015] Preferably, when the weight sensor detects a large weight difference between adjacent packages, potentially causing conveyor belt imbalance, or when the size sensor detects an abnormal package size, potentially causing congestion, the intelligent control unit, based on a preset algorithm, sends instructions to the conveyor belt drive motor to adjust the conveyor belt speed and acceleration. For example, if the package ahead is detected to be larger, the speed of subsequent packages will be appropriately reduced to avoid collisions. Furthermore, flow sensors are installed at each sorting port to count the number of packages entering the port in real time. The intelligent control unit dynamically adjusts the operating frequency of each sorting port based on its flow data. If the flow at a particular port is excessive, its open time will be appropriately increased to ensure efficient and balanced operation of the sorting ports.

[0016] The device connection and management module connects the sorting equipment to the cloud server through the IoT communication module. The IoT communication module uses high-speed network protocols such as 5G or Wi-Fi 6 to ensure stable and real-time data transmission.

[0017] Preferably, equipment operating status data, such as motor speed, equipment temperature, and the operating status of each module, as well as sorting data, such as the number of packages and sorting accuracy, are regularly uploaded to the cloud server. Managers can log in to the cloud server through a mobile app or a computer-based management platform to view the equipment's real-time operating data and status monitoring screen. The cloud server uses big data analysis technology to analyze equipment operating data and predict equipment failures. For example, by analyzing data such as motor temperature and vibration frequency, it can determine in advance whether the motor is likely to fail and send an early warning message to the manager. At the same time, based on historical sorting data and real-time package traffic, the cloud server provides managers with sorting strategy optimization suggestions, such as adjusting sorting port allocation rules.

[0018] The adaptive sorting actuator features a conveyor designed for packages of varying weights. For packages of average weight, a standard belt conveyor with a non-slip surface ensures stable transport. For overweight packages, the conveyor utilizes a thicker, higher-strength belt with multiple reinforced support rollers underneath to increase load capacity.

[0019] Preferably, an adjustable elastic clamping device replaces the traditional fixed structure in the sorting process. This device consists of multiple elastic clamping arms, whose force can be adjusted by a motorized telescopic rod. When a package arrives at the sorting location, a central control system controls the motorized telescopic rod to adjust the force and angle of the clamping arms based on the package's size and shape, ensuring a stable grip and delivery to the appropriate sorting port. For example, for spherical packages, the clamping arms are adjusted to an inward curve, increasing the contact area with the package for stable grip.

[0020] The intelligent logistics data analysis system runs on a cloud server. It first collects sorting data from various devices and modules through a data acquisition interface. The data preprocessing module cleans, de-duplicates, and standardizes the collected data to ensure data quality.

[0021] Preferably, the data analysis module uses big data analysis algorithms, such as cluster analysis and association rule mining, to analyze the processed data. For example, cluster analysis can be used to analyze package traffic in different regions and time periods, dividing traffic peak and trough periods and regions, providing a basis for logistics resource allocation. Association rule mining can be used to analyze the relationship between package damage and factors such as packaging type and transportation route, optimizing packaging and transportation plans. Finally, the analysis results are displayed in the form of visual charts on the management platform, allowing managers to intuitively understand the information behind the data and make scientific decisions. At the same time, the optimization strategies derived from the analysis are fed back to the central control system to achieve continuous optimization of the sorting system.

[0022] A sorting method based on the above-mentioned intelligent express sorting machine system includes the following steps.

[0023] Step 1: When a parcel enters the sorting process, the multimodal recognition device first attempts to read the parcel's RFID tag information through the RFID recognition module. If the read is successful, the information is transmitted to the central control system. If the read fails, the parcel enters the image recognition area, and the image recognition module obtains and analyzes the parcel image, and transmits the identification information to the central control system.

[0024] Step 2: Various sensors of the intelligent adaptive control device monitor the status of packages and conveyor belts in real time, and transmit the data to the intelligent control unit. The intelligent control unit adjusts the conveyor belt speed, acceleration and sorting port operating frequency based on the data.

[0025] Step 3: The device connection and management module uploads the device operation status data and sorting data to the cloud server through the IoT communication module. The manager views the device data and status through the terminal device. The cloud server analyzes the data and provides feedback on fault warnings and sorting strategy optimization suggestions.

[0026] Step 4: The central control system controls the conveying device and elastic clamping device of the adaptive sorting actuator according to the package information to accurately sort the package to the corresponding location.

[0027] Step 5: The logistics data intelligent analysis system collects sorting data, displays the results in visual charts after processing and analysis, and feeds back the optimization strategy to the central control system to achieve continuous optimization of the sorting system.

[0028] Preferably, the deep learning algorithm of the image recognition module improves the accuracy of package information recognition by analyzing the text contour and color features of the package label and repairing the text information by comparing it with a standard package label sample, and extracting the overall appearance features of the package and matching them with the sample library to confirm the package information.

[0029] Preferably, when the weight sensor detects that the weight difference between adjacent packages is too large or the size sensor detects that the package size is abnormal, the intelligent control unit sends instructions to the conveyor drive motor according to a preset algorithm to adjust the conveyor speed and acceleration to ensure smooth transmission of the packages and reduce the impact of mechanical vibration on sorting accuracy.

[0030] Preferably, the elastic clamping device of the adaptive sorting actuator is composed of a plurality of elastic clamping arms, and the elastic force of the clamping arms is adjusted by an electric telescopic rod. The elastic force and angle of the clamping arms can be adjusted according to the size and shape of the package, thereby achieving stable grasping and accurate sorting of different types of packages.

[0031] The intelligent express sorting machine system and sorting method based on "end-edge-cloud" collaboration described in this invention improves the accuracy and efficiency of package information recognition through a multimodal recognition device. An intelligent adaptive control device enables intelligent control of the conveyor belt and sorting port, ensuring the efficient operation of the sorting process. The device connection and management module achieves a deep connection between the device and the cloud, facilitating remote monitoring and management. The adaptive sorting actuator improves the device's adaptability to different types of packages. The logistics data intelligent analysis system mines data value and optimizes logistics operations. This invention comprehensively improves the efficiency, accuracy, and adaptability of express sorting, meets the modern logistics industry's urgent need for intelligent and refined management, and has significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0033] Figure 1 It is a structural diagram of the intelligent express sorting machine system of the present invention.

[0034] Figure 2 It is a workflow diagram of the multimodal recognition device of the present invention.

[0035] Figure 3 It is a flow chart of the sorting method of the present invention. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other implementations obtained by those skilled in the art without making any creative work shall fall within the scope of protection of the present application.

[0037] In the embodiments of the present application, the word "exemplary" is used to mean "used as an example, illustration or description". Any embodiment described in the present application as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. In order to enable any technician in this field to implement and use the present application, the following description is given. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details that make the description of the embodiments of the present application obscure. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest scope of the principles and features disclosed in the embodiments of the present application.

[0038] like Figures 1 to 3 The figure shows an intelligent express sorting machine system based on "end-edge-cloud" collaboration, including a multimodal recognition device, an intelligent adaptive control device, an equipment connection and management module, an adaptive sorting execution mechanism, and a logistics data intelligent analysis system.

[0039] When a package enters the sorting process, it first passes through the RFID recognition area. If the package is tagged with an RFID tag, the RFID recognition module quickly reads the tag's logistics information, including the delivery address and courier type, and transmits the data to the central control system. If the RFID tag is not detected or the read fails, the package enters the image recognition area.

[0040] The image recognition module uses a high-definition camera to capture images of packages from multiple angles. The image recognition algorithm, based on a deep learning model, analyzes the package's face label area and overall appearance. The algorithm first locates the face label. For blurred or damaged face labels, it analyzes the text outline and color characteristics, then repairs the text by comparing it with standard face label samples in a database. Simultaneously, it extracts overall package appearance features such as shape, color, and special markings, and matches them against a vast library of package samples. For example, when encountering an irregularly shaped package with a severely damaged face label, the image recognition algorithm first uses edge detection technology to outline the package. Then, based on the color distribution characteristics, it filters similar package types from the sample library. Next, based on the format of common express delivery numbers and any remaining text, it infers and repairs the face label information, ultimately transmitting the accurate package information to the central control system.

[0041] The intelligent adaptive control device uses sensors to continuously monitor the status of packages and conveyor belts in real time. The weight sensor samples 10 times per second, rapidly capturing changes in package weight. Once the weight difference between two adjacent packages exceeds a preset threshold (e.g., 5kg), the intelligent control unit rapidly calculates the appropriate conveyor belt speed adjustment parameters and sends a command to the conveyor belt drive motor within 0.5 seconds, reducing the conveyor belt speed to ensure smooth package delivery.

[0042] The dimension sensor uses laser ranging technology to accurately capture the length, width, and height of a package. If a package's dimensions are detected, potentially causing conveyor congestion, the intelligent control unit promptly adjusts the conveyor's operating strategy. At the sorting ports, flow sensors count incoming packages once a minute. If the number of packages accumulated at a particular port reaches a preset upper limit (e.g., 50), the intelligent control unit immediately increases the operating frequency of that port by 20%, accelerating the sorting process and ensuring an efficient and orderly process.

[0043] The device connection and management module and IoT communication module utilize 5G network protocols, achieving data transmission rates exceeding 1Gbps. This ensures that device operating status data and sorting data are quickly and stably uploaded to the cloud server. The cloud server then uses machine learning algorithms to conduct in-depth analysis of device operating data.

[0044] Taking motors as an example, a fault prediction model was established by training data on temperature, current, and vibration frequency over the past week. If the system detects a short-term rise in motor temperature of 5°C or abnormal current fluctuations, it can issue a fault warning 1-2 hours in advance, notifying maintenance personnel for prompt action and effectively preventing sorting interruptions caused by sudden equipment failures. Managers can also view a 3D model of the equipment on a mobile app, gaining an intuitive understanding of the operating status of each component and optimizing sorting strategies through comparative analysis of historical data.

[0045] The adaptive sorting actuator uses a standard belt conveyor with a non-slip surface for normal-weight packages, ensuring stable and non-slip transport. For overweight packages (over 15kg), a specially designed, thickened, high-strength belt with five evenly distributed reinforced support rollers can withstand weights up to 50kg, ensuring smooth transport.

[0046] When encountering unusually shaped packages, such as spherical or conical ones, the central control system uses the package size and shape information provided by the image recognition module to control the electric telescopic rod of the elastic gripping device to adjust the force and angle of the gripping arm. For example, for a spherical package, the gripping arm will adjust to an inward arc, increasing the contact area with the package, achieving stable grip and delivering it to the corresponding sorting port with precise angle and force, with an error of less than ±5mm throughout the entire process.

[0047] During the data preprocessing phase, the intelligent logistics data analysis system uses regular expressions and machine learning algorithms to clean collected package data. This system automatically identifies and corrects over 95% of incorrect data formats, ensuring data quality. During data analysis, a cluster analysis algorithm was used to analyze package flow in a specific area over a month. Peak flow periods were found between 10:00 AM and 12:00 PM and between 3:00 PM and 5:00 PM each day, with significant differences in package flow distribution across different streets.

[0048] Based on this, logistics companies can rationally allocate transport vehicles and sorting personnel, increase transport capacity and manpower during peak hours, and significantly improve logistics efficiency. Through association rule mining, it was found that the damage rate of a certain type of fragile goods was reduced by 40% when using a specific packaging method. Based on this, companies can optimize packaging solutions and reduce economic losses.

[0049] A sorting method based on the above-mentioned intelligent express sorting machine system includes the following steps.

[0050] Step 1: When a parcel enters the sorting process, the multimodal recognition device first attempts to read the parcel's RFID tag information through the RFID recognition module. If the read is successful, the information is transmitted to the central control system. If the read fails, the parcel enters the image recognition area, and the image recognition module obtains and analyzes the parcel image, and transmits the identification information to the central control system.

[0051] Step 2: Various sensors of the intelligent adaptive control device monitor the status of packages and conveyor belts in real time, and transmit the data to the intelligent control unit. The intelligent control unit adjusts the conveyor belt speed, acceleration and sorting port operating frequency based on the data.

[0052] Step 3: The device connection and management module uploads the device operation status data and sorting data to the cloud server through the IoT communication module. The manager views the device data and status through the terminal device. The cloud server analyzes the data and provides feedback on fault warnings and sorting strategy optimization suggestions.

[0053] Step 4: The central control system controls the conveying device and elastic clamping device of the adaptive sorting actuator according to the package information to accurately sort the package to the corresponding location.

[0054] Step 5: The logistics data intelligent analysis system collects sorting data, displays the results in visual charts after processing and analysis, and feeds back the optimization strategy to the central control system to achieve continuous optimization of the sorting system.

[0055] Preferably, the deep learning algorithm of the image recognition module improves the accuracy of package information recognition by analyzing the text contour and color features of the package label and repairing the text information by comparing it with a standard package label sample, and extracting the overall appearance features of the package and matching them with the sample library to confirm the package information.

[0056] Preferably, when the weight sensor detects that the weight difference between adjacent packages is too large or the size sensor detects that the package size is abnormal, the intelligent control unit sends instructions to the conveyor drive motor according to a preset algorithm to adjust the conveyor speed and acceleration to ensure smooth transmission of the packages and reduce the impact of mechanical vibration on sorting accuracy.

[0057] Preferably, the elastic clamping device of the adaptive sorting actuator is composed of a plurality of elastic clamping arms, and the elastic force of the clamping arms is adjusted by an electric telescopic rod. The elastic force and angle of the clamping arms can be adjusted according to the size and shape of the package, thereby achieving stable grasping and accurate sorting of different types of packages.

[0058] In this embodiment, the cloud platform is a cloud computing platform created by Huawei Cloud, which provides safe and reliable computing power and data processing capabilities. Users connect the cloud platform and each module through the control system. The cloud platform can transmit commands to the control system in real time, and the control system controls the operation of sensors and motors. At the same time, it can transmit data in real time and store the data in the cloud platform. Real-time update of information facilitates the control of the lower-level sorting vehicle system. The cloud platform can update and store sorting data in real time, making the sorting process more transparent and efficient. Sorters can instantly obtain the latest order information and sorting instructions, improving operational efficiency. The cloud platform can be flexibly expanded according to needs to support different scales and needs. The express sorting center does not require additional hardware investment, and only needs to adjust the usage of cloud resources according to actual needs. The cloud platform provides powerful data analysis and processing capabilities, which can monitor and analyze the sorting process in real time. By analyzing the data, opportunities for optimizing the sorting process can be discovered to improve sorting efficiency and accuracy. The cloud platform can realize cross-regional collaborative operations, and different sorting centers can share data and resources in real time to achieve unified management and collaborative sorting, thereby improving overall operational efficiency. Cloud platforms usually have strict security and backup mechanisms to ensure data security and reliability. Even in the event of hardware failure or unexpected situation, data can be restored and protected in time.

[0059] In this embodiment, the express sorting machine adopts a mobile carriage design, which allows the sorting machine to be easily moved to different locations when needed, adapting to sorting centers of different sizes and needs. Through the automated sorting process, the sorting speed and accuracy can be greatly improved, and human errors can be reduced. The carriage design can maximize the use of space in the warehouse or sorting center, and does not require large fixed equipment to occupy a large amount of space. The modular design makes the sorting machine easy to maintain and upgrade, and it can be partially replaced or upgraded as needed without replacing the entire system. Through the integrated data management system, the sorting process can be tracked and managed in real time, providing more accurate transportation information and data analysis.

[0060] In summary, through the collaborative operation of various modules and innovative design, the present invention not only effectively solves the problems of low efficiency, poor accuracy, weak adaptability, and lack of intelligent management in existing express sorting technologies, but also provides strong support for the intelligent development of the logistics industry. It has extremely high practical value and broad prospects for promotion and application. At the same time, with the continuous development of the logistics industry and the continuous advancement of technology, the intelligent express sorting machine system and sorting method of the present invention can be further optimized and upgraded to better meet market demand.

[0061] The above describes in detail the method, apparatus, device, and storage medium for generating a sorting strategy provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only intended to help understand the method and core concept of the present application. At the same time, those skilled in the art may vary the specific implementation methods and application scope based on the concept of the present application. In summary, the contents of this specification should not be construed as limiting the present application.

Claims

1. An intelligent express sorting machine system based on "end-edge-cloud" collaboration, characterized by: The steps include: A multimodal recognition device integrates an image recognition module and an RFID recognition module to identify package information. When a package enters the sorting process, it first passes through the RFID recognition area. If an RFID tag is present, the information is read and transmitted to the central control system. If the tag is absent or the reading fails, the package enters the image recognition area. The image recognition module uses a high-definition camera and deep learning algorithms to analyze the package image, obtain information, and transmit it to the central control system. The intelligent adaptive control device is equipped with weight sensors, size sensors, and position sensors on the conveyor belt, speed and acceleration sensors on the conveyor belt drive motor, and a flow sensor at the sorting port. The sensor data is transmitted in real time to the intelligent control unit, which adjusts the conveyor belt speed, acceleration, and sorting port operating frequency based on the sensor data. The device connection and management module establishes a connection with the cloud server through the IoT communication module using high-speed network protocols such as 5G or Wi-Fi 6. The device operation status data and sorting data are uploaded to the cloud server on a regular basis. Managers can log in to the cloud server through terminal devices to view the device data and status. The cloud server analyzes the device data and provides fault warnings and sorting strategy optimization suggestions. The adaptive sorting actuator and conveyor are designed for packages of varying weights. Standard-weight packages are conveyed using a standard belt with a non-slip surface to ensure stable transport. Overweight packages are transported using a thickened, high-strength belt with reinforced support rollers to increase load capacity. The sorting section utilizes an adjustable elastic clamping device, which is controlled by a central control system based on package size and shape to grab the package and deliver it to the appropriate sorting port. The intelligent logistics data analysis system runs on a cloud server. Sorting data is collected through a data acquisition interface. After being cleaned, deduplicated, and standardized by the data preprocessing module, it is analyzed using big data analysis algorithms by the data analysis module. The analysis results are displayed as visual charts on the management platform, and optimization strategies are fed back to the central control system.

2. The intelligent express sorting machine system based on "end-edge-cloud" collaboration as claimed in claim 1 is characterized in that: The deep learning algorithm of the image recognition module analyzes the text contours and color features of the package label and repairs the text information by comparing it with standard package labels, and extracts the overall appearance features of the package and matches them with the sample library to confirm the package information.

3. The intelligent express sorting machine system based on "end-edge-cloud" collaboration as claimed in claim 1 is characterized in that: When the weight sensor detects that the weight difference between adjacent packages is too large or the size sensor detects that the package size is abnormal, the intelligent control unit sends instructions to the conveyor belt drive motor according to a preset algorithm to adjust the conveyor belt speed and acceleration.

4. The intelligent express sorting machine system in "end-edge-cloud" collaboration according to claim 1, characterized in that: The elastic clamping device of the adaptive sorting actuator is composed of multiple elastic clamping arms. The elastic force of the clamping arms is adjusted by an electric telescopic rod. The elastic force and angle of the clamping arms can be adjusted according to the size and shape of the package.

5. The sorting method of the intelligent express sorting machine system according to any one of claims 1 to 4, characterized in that: The steps include: Step 1: When a package enters the sorting process, the multimodal recognition device first attempts to read the package's RFID tag information through the RFID recognition module. If the read is successful, the information is transmitted to the central control system. If the read fails, the package enters the image recognition area, where the image recognition module obtains and analyzes the package image and transmits the identification information to the central control system. Step 2: Various sensors in the intelligent adaptive control device monitor the status of packages and conveyor belts in real time, and transmit the data to the intelligent control unit. The intelligent control unit adjusts the conveyor belt speed, acceleration, and sorting port operating frequency based on the data. Step 3: The device connection and management module uploads the device operation status data and sorting data to the cloud server through the IoT communication module. The manager views the device data and status through the terminal device. The cloud server analyzes the data and provides feedback on fault warnings and sorting strategy optimization suggestions. Step 4: The central control system controls the conveying device and elastic clamping device of the adaptive sorting actuator according to the package information to accurately sort the package to the corresponding location; Step 5: The logistics data intelligent analysis system collects sorting data, displays the results in visual charts after processing and analysis, and feeds back the optimization strategy to the central control system to achieve continuous optimization of the sorting system.

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