Intelligent access information management system of express station

Abstract

The invention relates to an intelligent access information management system for an express delivery post, and the system comprises a pre-layout unit which is used for presetting different goods shelves in a room of the express delivery post according to the building number layout of a community, each goods shelf represents a building number, and the gaps between the goods shelves represent different floors; the three-dimensional modeling unit is used for carrying out accurate modeling on goods shelves established according to community building numbers in rooms by utilizing a three-dimensional imaging technology to form a virtual goods shelf layout map, and marking floor information represented by each goods shelf and gaps thereof in the virtual layout map; according to the express delivery post intelligent access information management system applied to the community, the defects in the prior art can be comprehensively overcome, automation, intelligentization and high efficiency of express delivery management are achieved, more convenient and efficient express delivery taking service is provided for residents, and meanwhile the efficiency and accuracy of the whole express delivery processing flow are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent storage and access information management systems, and in particular to an intelligent storage and access information management system for express delivery stations. Background Art

[0002] At present, express delivery management in residential areas mainly relies on traditional express delivery rooms or manually managed express delivery cabinets. These methods may meet basic needs when the express delivery volume is small, but with the rapid development of e-commerce, the express delivery volume has increased dramatically, and traditional management methods have gradually exposed many problems. Traditional express delivery rooms require manual sorting, recording and management of express delivery, which is not only inefficient but also prone to errors; and although manually managed express delivery cabinets have improved the degree of automation to a certain extent, they are limited by the number and size of cabinets and are difficult to cope with large and diverse express delivery storage needs, such as:

[0003] (1) Traditional express delivery management methods require a lot of manual participation, resulting in slow processing speed, especially during peak express delivery periods, when residents often have to wait for a long time or face express delivery backlogs.

[0004] (2) Manual classification and recording of express delivery information is prone to errors, such as the express delivery being placed in the wrong place, inaccurate information being recorded, etc., causing inconvenience to residents when picking up their parcels.

[0005] (3) Residents often have to wait for staff to find the courier, so it takes a long time for them to get their parcels, which results in a poor experience.

[0006] Therefore, we propose an intelligent storage and retrieval information management system for express delivery stations, which uses technical means such as unit modules and express delivery robots to achieve fast and accurate classification and storage of express deliveries, as well as a convenient and efficient pickup process. Summary of the invention

[0007] The purpose of the present invention is to overcome the shortcomings of the prior art, adapt to actual needs, and provide an intelligent storage and access information management system for express delivery stations to solve the problem that the current traditional express delivery management method requires a large amount of manual participation, resulting in slow processing speed, especially during the peak period of express delivery, residents often need to wait for a long time or face express backlogs; manual classification and recording of express delivery information are prone to errors, such as misplacement of express delivery, inaccurate information records, etc., which brings inconvenience to residents in picking up items; since residents need to wait for staff to find the express delivery when picking up items, they often need to spend a long time to pick up their own express delivery, experiencing poor technical problems.

[0008] In order to achieve the purpose of the present invention, the technical solution adopted by the present invention is: designing an intelligent access information management system for express delivery stations, including:

[0009] A pre-layout unit is used to pre-set different shelves inside the express station room according to the building number layout of the community, each shelf represents a building number, and the gaps between the shelves represent different floors;

[0010] The 3D modeling unit uses 3D imaging technology to accurately model the shelves in the room according to the building numbers of the community, forming a virtual shelf layout diagram, and marking the floor information represented by each shelf and its gap in the virtual layout;

[0011] The express information entry unit is set in the express delivery area, including an image recognition module and a barcode / QR code scanning module, which is used to scan and recognize the building number, floor number, express delivery order number and other information on the express delivery when the express delivery is delivered to the warehouse, and bind this information with the information of the express delivery itself;

[0012] The intelligent express delivery robot is equipped with lifting, moving and positioning functions, and is used to move the express delivery from the storage area to the shelf representing the corresponding building number according to the information entered by the express delivery information entry unit, and accurately place the express delivery in the gap of the corresponding floor of the shelf according to the floor number information;

[0013] Large express handling unit: when the size of the express is larger than the gap between shelves on the corresponding floor, the intelligent express robot will move the express to the large express storage area, which is equipped with freely addable modules and automatically height-adjustable shelves to accommodate large express storage of different sizes and quantities;

[0014] The data processing and control unit is connected to the express information entry unit and the intelligent express robot for receiving and processing express information, planning the moving path and lifting height of the intelligent express robot, controlling the intelligent express robot to move and place the express, monitoring the use of the large express storage area, and prompting to add or remove modules as needed;

[0015] The user interaction interface provides residents with the function of querying the express delivery storage location and pickup code, and supports multiple query methods such as mobile phone APP, web page or on-site touch screen;

[0016] Security protection units, including surveillance cameras, intrusion detection sensors and emergency stop buttons, are used to ensure the safe operation of the express delivery station and prevent the loss or damage of express parcels;

[0017] The system expansion interface allows the free addition of additional intelligent express robots, large express storage area modules, computing resources of the data processing and control unit, etc. according to the growth of express delivery volume in the community, so as to improve the processing power and flexibility of the system.

[0018] Preferably, the three-dimensional modeling unit also includes a virtual navigation module for displaying the position and movement path of the intelligent express robot, as well as the occupancy status of shelves and gaps in real time on a virtual shelf layout diagram so that managers can monitor and manage.

[0019] Preferably, the intelligent express delivery robot is equipped with obstacle avoidance sensors and path planning algorithms to detect and avoid obstacles during movement, optimize the movement path, and ensure safe and efficient movement of express delivery.

[0020] Preferably, the large express storage area is equipped with an automatic sorting module and intelligent handling equipment, which are used to further classify, store and transport large express items according to their size, weight and type, so as to improve the efficiency of picking up items and the utilization rate of storage space.

[0021] Preferably, the data processing and control unit is also used to record and analyze residents' pickup behavior data, including pickup time, frequency, preferences, etc., to optimize the storage location and pickup process of the express and improve overall service efficiency.

[0022] Preferably, the user interaction interface also provides value-added service functions such as appointment pickup, express storage, and collection and delivery on behalf of others to meet the diverse express delivery needs of community residents.

[0023] Preferably, the security protection unit also includes a smart door lock and an identity authentication module, which are used to control the opening and closing of the storage and retrieval window to ensure that only authenticated community residents or authorized personnel can take away the express delivery.

[0024] Preferably, the system expansion interface also includes an integrated interface with other intelligent systems (such as community access control systems, smart home systems, etc.) to achieve interconnection and data sharing between the smart express station and other intelligent systems in the community.

[0025] Preferably, the intelligent express robot is also equipped with a size recognition module, which determines whether it exceeds the ordinary shelf gap. If it exceeds, the robot will automatically move it to a large express storage area.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. The present invention realizes the efficient and accurate classification, handling and storage functions of express delivery through the collaborative operation of the intelligent express robot and the data processing and control unit. The system can directly and accurately deliver the express delivery to the shelf of the corresponding building number and the designated location between the floors, ensuring that each express delivery has a fixed and clear location, thereby greatly improving the overall processing efficiency. In addition, since each express delivery has a fixed and clear location, the recipient only needs to find the shelf and floor gap corresponding to his or her building number by himself or herself, and can quickly locate the location of his or her express delivery, without wasting time waiting for the staff to search, thereby enhancing the convenience of picking up the items, and also greatly optimizing the express delivery collection experience of the residents.

[0028] 2. The present invention uses three-dimensional modeling and virtual navigation technology to achieve accurate planning and dynamic adjustment of shelf layout corresponding to community building numbers and floors, as well as flexible expansion of large express storage areas, thereby improving space utilization.

[0029] 3. The present invention can quickly and accurately move express parcels to shelves with corresponding building numbers and floors through intelligent express robots, greatly improving processing efficiency and reducing express backlogs and waiting time for pickup.

[0030] To sum up, the intelligent storage and access information management system for express delivery stations applied in residential communities proposed in the present invention can comprehensively overcome the shortcomings of the existing technology, realize the automation, intelligence and efficiency of express delivery management, provide residents with more convenient and efficient pickup services, and at the same time improve the efficiency and accuracy of the entire express delivery processing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is an overall schematic diagram of the present invention;

[0032] Figure 2 It is a schematic diagram of a three-dimensional modeling unit of the present invention;

[0033] Figure 3 Schematic diagram of the intelligent express robot of the present invention. DETAILED DESCRIPTION

[0034] The present invention is further described below in conjunction with the accompanying drawings and embodiments:

[0035] An intelligent storage and access information management system for express delivery stations, see Figures 1 to 3 ,include:

[0036] A pre-layout unit is used to pre-set different shelves inside the express station room according to the building number layout of the community, each shelf represents a building number, and the gaps between the shelves represent different floors;

[0037] The 3D modeling unit uses 3D imaging technology to accurately model the shelves in the room according to the building numbers of the community, forming a virtual shelf layout diagram, and marking the floor information represented by each shelf and its gap in the virtual layout;

[0038] The express information entry unit is set in the express delivery area, including an image recognition module and a barcode / QR code scanning module, which is used to scan and recognize the building number, floor number, express delivery order number and other information on the express delivery when the express delivery is delivered to the warehouse, and bind this information with the information of the express delivery itself;

[0039] The intelligent express delivery robot is equipped with lifting, moving and positioning functions, and is used to move the express delivery from the storage area to the shelf representing the corresponding building number according to the information entered by the express delivery information entry unit, and accurately place the express delivery in the gap of the corresponding floor of the shelf according to the floor number information;

[0040] Large express handling unit: when the size of the express is larger than the gap between shelves on the corresponding floor, the intelligent express robot will move the express to the large express storage area. The large express storage area is equipped with freely addable modules and automatically height-adjustable shelves to accommodate large express storage of different sizes and quantities.

[0041] The data processing and control unit is connected to the express information entry unit and the intelligent express robot for receiving and processing express information, planning the moving path and lifting height of the intelligent express robot, controlling the intelligent express robot to move and place the express, monitoring the use of the large express storage area, and prompting to add or remove modules as needed;

[0042] The user interaction interface provides residents with the function of querying the express delivery storage location and pickup code, and supports multiple query methods such as mobile phone APP, web page or on-site touch screen;

[0043] Security protection units, including surveillance cameras, intrusion detection sensors and emergency stop buttons, are used to ensure the safe operation of the express delivery station and prevent the loss or damage of express parcels;

[0044] The system expansion interface allows the free addition of additional intelligent express robots, large express storage area modules, computing resources of the data processing and control unit, etc. according to the growth of express delivery volume in the community, so as to improve the processing power and flexibility of the system.

[0045] For details, see Figure 2 The 3D modeling unit also includes a virtual navigation module, which is used to display the position and movement path of the intelligent express robot, as well as the occupancy of shelves and gaps in real time on a virtual shelf layout map, so that managers can monitor and manage.

[0046] For more details, see Figure 3,The intelligent express robot is equipped with obstacle avoidance sensors and ,path planning algorithms to detect and avoid obstacles during movement, ,optimize the movement path, and ensure the safe and efficient movement of ,express.

[0047] For further information, see Figure 1 The large express storage area is equipped with automatic sorting modules and intelligent handling equipment, which are used to further classify, store and transport large express items according to their size, weight and type, so as to improve the efficiency of picking up items and the utilization of storage space.

[0048] Further, see Figure 1 ,The data processing and control unit is also used to record and analyze residents’ ,pickup behavior data, including pickup time, frequency, preferences, etc., in order to optimize the storage location and ,pickup process of the express and improve the overall service efficiency.

[0049] It is worth noting that see Figure 1 The user interaction interface also provides value-added service functions such as appointment pickup, temporary storage of express delivery, and collection and delivery on behalf of others to meet the diverse express delivery needs of community residents.

[0050] It is worth noting that see Figure 1 ,The security protection unit also includes a smart door lock and identity authentication module, which is used to control the opening and closing of the storage and retrieval windows, ensuring that only authenticated community residents or authorized personnel can pick up the express.

[0051] It is worth mentioning that see Figure 1 The system expansion interface also includes integration interfaces with other intelligent systems (such as community access control systems and smart home systems) to achieve interconnection and data sharing between smart express stations and other intelligent systems in the community.

[0052] It is worth emphasizing that see Figure 3 The intelligent express delivery robot is also equipped with a size recognition module, which determines whether it exceeds the gap between ordinary shelves. If so, the robot will automatically move it to a large express storage area.

[0053] Embodiment 1

[0054] Smart Express Access

[0055] Shelf layout and modeling

[0056] The pre-layout unit is arranged according to the building numbers of the community, with 10 shelves set up, each shelf representing a building number.

[0057] The 3D modeling unit uses 3D imaging technology to accurately model the shelves and form a virtual shelf layout diagram. In the virtual layout, each shelf and its gap are marked with the floor information they represent, such as the 1st floor of Building 1 and the 3rd floor of Building 2.

[0058] Express delivery information entry

[0059] When the express arrives at the station, the staff will place the express on the express information entry unit.

[0060] The express information entry unit automatically enters the building number (such as Building 3), floor number (such as Floor 5) and express order number of the express by scanning the barcode / QR code on the express and the image recognition module. This information is bound with the information of the express itself (such as weight, size, sender, recipient) to form a complete express information record.

[0061] Intelligent delivery robot movement and placement

[0062] After receiving the information from the express information entry unit, the intelligent express robot uses the data processing and control unit to automatically plan the route and move the express from the warehousing area to the shelf of the corresponding building number.

[0063] The robot uses the lifting function to accurately place the express delivery in the gap between the corresponding floors of the shelves according to the floor number information. For example, if a package is sent to the 5th floor of Building 3, the robot will move it to the gap between the 5th floor of the shelf in Building 3.

[0064] Resident pickup

[0065] Residents log in to the user interface through the mobile phone APP, enter their mobile phone number or express delivery number, and check the pickup code and delivery location.

[0066] According to the guidance provided by the system, residents go to the corresponding shelves and floor gaps to find and pick up their express deliveries. After residents are familiar with the location of the shelves on their floors, they only need to move to the location of the shelf and choose the corresponding floor gap to pick up the express delivery.

[0067] System expansion and upgrade

[0068] The system expansion interface reserves space for adding additional robots and shelves to accommodate future growth in express delivery volume.

[0069] When the volume of express delivery increases, the station can expand the system's processing capacity by adding more intelligent delivery robots and shelves.

[0070] Numerical Example

[0071] Shelf quantity and layout

[0072] Total number of shelves: 10

[0073] Each shelf represents a building number: Building 1 to Building 10

[0074] The number of gaps on each shelf: Determined by the number of floors. Assuming there is one gap on each floor, each shelf has a certain number of gaps (the specific number depends on the number of floors)

[0075] Express delivery information entry

[0076] Daily express delivery volume: 500 pieces

[0077] Entry time for each express delivery: about 5 seconds (including scanning barcode / QR code, image recognition, etc.)

[0078] Total input time: 500 items x 5 seconds / item = 2500 seconds (about 41.67 minutes)

[0079] Intelligent delivery robot movement and placement

[0080] Robot moving speed: about 1 m / s

[0081] Shelf spacing: about 2 meters

[0082] Robot lifting height: Determined by the floor clearance height, each floor height is 2.5 meters

[0083] The robot moves and places each time: including path planning, movement, lifting, and placement; 30 seconds

[0084] Total moving and placement time: 500 pieces x 30 seconds / piece = 15,000 seconds (approximately 4.17 hours)

[0085] Resident pickup

[0086] Average pickup time: 2 minutes / item (including steps such as querying the pickup code, going to the shelf, finding the courier, and picking it up)

[0087] Total pickup time: 500 pieces x 2 minutes / piece = 1000 minutes (about 16.67 hours)

[0088] System expansion and upgrade

[0089] The number of additional robots will be determined based on the growth of express delivery volume. Assuming the volume of express delivery increases by 10% each year, a corresponding number of robots will need to be added each year.

[0090] Shelf expansion: This will also be determined based on the growth in express delivery volume, ensuring that the gaps in each shelf can be fully utilized.

[0091] By introducing an intelligent express storage and retrieval information management system, the community express station has achieved fast and accurate storage and retrieval of express parcels. The system has greatly improved storage and retrieval efficiency and service quality through the collaborative work of multiple modules such as the pre-layout unit, 3D modeling unit, express information entry unit, and intelligent express robot. At the same time, the system expansion interface reserves space for adding additional robots and shelves, providing sufficient guarantee for the future growth of express delivery volume.

[0092] Embodiment 2

[0093] Large courier handling

[0094] In express delivery stations, it is common to encounter situations where the size of large express items (such as furniture, electrical appliances, etc.) exceeds the clearance of ordinary shelves. In order to efficiently handle these large express items, express delivery stations have introduced large express storage areas and are equipped with shelves that automatically adjust the height, modules that can be added freely, automatic sorting modules, and intelligent handling equipment. These devices work together to achieve rapid sorting, storage, and pickup of large express items.

[0095] Large courier identification and transfer

[0096] When the intelligent delivery robot receives a large package, it first uses the size recognition module to determine whether it exceeds the normal shelf gap.

[0097] If it exceeds the limit, the robot will automatically move it to a large express storage area.

[0098] Automatically adjust shelf height and module addition

[0099] The large express storage area is equipped with automatically height-adjusting shelves and freely addable modules.

[0100] After the robot transfers the large express to the storage area, the system will automatically detect the height of the express and adjust the height of the shelf to accommodate the size of the express.

[0101] If the current shelf space is insufficient, the system will automatically prompt managers to add additional modules to expand storage space.

[0102] Automatic sorting and classification storage

[0103] The automatic sorting module classifies the express items according to their size, weight, type and other information and stores them in the most suitable location.

[0104] For example, for express parcels that are more than 1.5 meters tall, the system will store them in a higher position of the height-adjustable module; for express parcels that are heavier, the system will store them close to the ground for easy handling.

[0105] Residents' appointment for pick-up and intelligent transportation

[0106] Residents make an appointment to pick up their parcels through a mobile app or user interface and enter information such as the courier number or mobile phone number.

[0107] Based on the appointment information, the system automatically locates the storage location of large express parcels and dispatches intelligent handling equipment to deliver them to the pickup area.

[0108] Residents wait in the pickup area for the smart handling equipment to deliver the express and then pick up their own express.

[0109] Numerical Example

[0110] Large Courier Dimensions and Weights

[0111] Height: The height of large couriers ranges from 1 meter to 2 meters.

[0112] Weight: Large couriers can range in weight from 20kg to 100kg.

[0113] Shelf height adjustment and module addition

[0114] Automatically adjust shelf height range: 0.5m to 2.5m.

[0115] Number of height-adjustable modules installed: 3.

[0116] Maximum load-bearing capacity of each module: 100 kg.

[0117] Module adding frequency: Determined based on the growth of express delivery volume, modules are checked and added once a month.

[0118] Automatic sorting module

[0119] Sorting speed: 10 large express parcels per minute.

[0120] Sorting accuracy: more than 99%.

[0121] Intelligent handling equipment

[0122] Handling speed: One large express parcel is carried to the pickup area every minute.

[0123] Handling accuracy: 100%.

[0124] Residents make appointments to pick up items

[0125] Average pickup booking time: 5 minutes (including inputting information, waiting for system confirmation, etc.).

[0126] Average waiting time for intelligent handling equipment: 2 minutes (determined by the current location of the handling equipment and the express storage location).

[0127] By introducing large express storage areas, automatically height-adjustable shelves, freely addable modules, automatic sorting modules, and intelligent handling equipment, the express station has achieved efficient processing of large express deliveries. These devices work together to not only improve the efficiency of picking up items and space utilization, but also reduce the cost and risk of manual operations. At the same time, the system is also scalable and can flexibly add modules and equipment according to the growth of express delivery volume, ensuring the continued efficiency of large express delivery processing.

[0128] Embodiment 3

[0129] Intelligent path planning and obstacle avoidance algorithm

[0130] During the peak period of express delivery, intelligent express delivery robots need to frequently shuttle in complex warehouse environments to ensure fast and accurate delivery of express parcels. Warehouses are densely packed with shelves, and there may be dynamic obstacles such as temporarily stacked items and walking people. To meet this challenge, the robot is equipped with advanced obstacle avoidance sensors and path planning algorithms.

[0131] Algorithm description and specific process

[0132] Environmental Perception and Modeling

[0133] The robot uses obstacle avoidance sensors such as lidar, visual cameras and ultrasonic sensors to scan the surrounding environment in real time and build a dynamic environmental model.

[0134] The environment model includes the location of the shelf, the location of obstacles (such as temporarily stacked items, people, etc.), and the current location of the robot.

[0135] Path Planning

[0136] The robot uses the A* algorithm to calculate the shortest path from the starting point A (warehouse area) to the end point B (shelf on the second floor of Building 5) in the constructed environmental model.

[0137] When calculating the path, the algorithm takes into account the location of obstacles to ensure that the robot can avoid them.

[0138] Dynamic obstacle avoidance

[0139] As the robot moves, sensors continuously monitor changes in the surrounding environment.

[0140] If a new obstacle is detected (such as temporarily stacked objects or walking people), the robot will immediately stop moving and replan the path.

[0141] When replanning the path, the robot considers the current position, the target position, and the position of new obstacles to select a feasible detour.

[0142] Path Optimization

[0143] During obstacle avoidance, the robot will consider path optimization to reduce driving time and energy consumption.

[0144] For example, the robot will choose a shorter detour or use the gaps between shelves to move quickly.

[0145] The path optimization algorithm takes into account factors such as the robot's speed, acceleration, and the distance between shelves to ensure that the robot can complete its tasks efficiently and safely.

[0146] Execution and Feedback

[0147] The robot moves along the replanned path while continuously monitoring changes in the surrounding environment.

[0148] If the robot encounters an obstacle again during movement, it will repeat the above obstacle avoidance and path optimization process.

[0149] When the robot successfully reaches the target location (shelf on the 2nd floor of Building 5), the mission is completed and the robot places the express at the designated location.

[0150] Specific case description

[0151] In one mission, the robot's original path from point A (warehouse entry area) to point B (2nd floor shelf in Building 5) was blocked by a temporary obstacle (such as a pile of temporarily stacked items).

[0152] Environmental perception: The robot detects the location and shape of obstacles through lidar and visual cameras.

[0153] Path replanning: The robot uses the A* algorithm to replan the path and chooses to bypass point C (an empty aisle between shelves) to avoid obstacles.

[0154] Dynamic obstacle avoidance: During the detour, the robot continuously monitors the surrounding environment to ensure that it does not collide with other obstacles or people.

[0155] Path optimization: The robot chooses a shorter detour route to reduce travel time and energy consumption.

[0156] Mission accomplished: The robot successfully reached the shelf on the second floor of Building 5 and placed the express at the designated location, mission accomplished.

[0157] Numerical Example

[0158] Environmental model: The warehouse size is 100x100 meters, and the shelf spacing is 2 meters.

[0159] Sensor performance: The laser radar has a measurement distance of 30 meters and a resolution of 0.1 meters; the visual camera has an obstacle recognition accuracy of 98%; the ultrasonic sensor has a measurement distance of 10 meters and an accuracy of ±0.2 meters.

[0160] Path planning: A* algorithm heuristic function uses Euclidean distance, open list size is 50, and closed list size is 100.

[0161] Dynamic obstacle avoidance: After the robot detects an obstacle, it takes less than 1 second to replan the path.

[0162] Path optimization: Through path optimization, the robot reduced travel time and energy consumption by about 10%.

[0163] Through the above algorithms and numerical examples, we can clearly see the path planning and obstacle avoidance process of the intelligent express delivery robot in a complex environment. The robot can perceive environmental changes in real time and dynamically adjust the path to ensure the safe and efficient delivery of the express.

[0164] Embodiment 4

[0165] Resident behavior analysis and service optimization

[0166] Data collection and preprocessing

[0167] The data processing and control unit continuously collects residents' pickup behavior data through smart express cabinet systems, mobile phone apps and other channels, including pickup time, pickup building number, and pickup method.

[0168] The collected data is preprocessed to remove duplicate and invalid data, and the time data is converted into a standard format to ensure the accuracy and consistency of the data.

[0169] Behavioral analysis

[0170] Using clustering algorithms, the preprocessed data is deeply analyzed to identify residents’ pickup behavior patterns.

[0171] The clustering algorithm calculates the similarity between the pickup behaviors of different residents and divides the residents with similar pickup behaviors (such as pickup time, pickup building number, etc.) into the same group.

[0172] Through cluster analysis, we focus on the express pickup volume of each building number and determine the popular building numbers; at the same time, we analyze the distribution of pickup time and determine the peak hours.

[0173] Strategy adjustment and optimization

[0174] Based on the results of behavioral analysis, the system automatically adjusts the express storage strategy.

[0175] Before the peak period, express deliveries for popular buildings will be placed on the shelves of the corresponding buildings first to reduce the time residents spend traveling between different buildings and improve the efficiency of picking up items.

[0176] At the same time, based on residents' preferences for pickup methods, the operating interface of express lockers and the design of mobile APP are optimized, such as adding real-time updates of express status, one-click pickup, and intelligent navigation to the corresponding building number shelf to enhance user experience.

[0177] Effect evaluation and feedback

[0178] After implementing strategy adjustments, continue to monitor and evaluate the effectiveness of the adjustments.

[0179] The effectiveness of strategy adjustments is evaluated through indicators such as resident satisfaction surveys, improved pickup efficiency, and shelf turnover rate.

[0180] Based on the evaluation results, timely adjust and optimize strategies to form a closed-loop feedback mechanism to ensure continuous optimization and upgrading of the system.

[0181] Numerical Example

[0182] Data collection and preprocessing

[0183] A community’s smart express locker system collected 12,000 pieces of residents’ pickup behavior data within a week.

[0184] After data cleaning, 11,500 valid data were obtained, and 500 duplicate and invalid data were removed.

[0185] Behavioral analysis

[0186] The results of the clustering algorithm analysis show that the express pickup volumes of Building 1 and Building 2 account for 30% and 25% of the total, respectively, making them popular buildings.

[0187] Residents’ parcel pickup time is mainly concentrated between 6pm and 8pm, accounting for 45%, which is the peak period.

[0188] Strategy adjustment and optimization

[0189] Based on the results of cluster analysis, the system prioritizes the express deliveries from Building 1 and Building 2 on the shelves of the corresponding building numbers between 5pm and 5:30pm.

[0190] At the same time, in view of the fact that residents prefer to use mobile APP to make inquiries, the design of the mobile APP has been optimized to add functions such as real-time update of express status, one-click pickup, and intelligent navigation to the corresponding building number shelf to enhance the user experience.

[0191] Effect evaluation and feedback

[0192] After implementing the strategy adjustment, residents’ efficiency in picking up items increased by 30% and the average waiting time was shortened by 8 minutes.

[0193] Shelf turnover rate increased by 25%, and shelf space utilization in popular floors became more reasonable.

[0194] The residents’ satisfaction survey showed that satisfaction with the express locker system and mobile APP increased by 20% and 25% respectively.

[0195] Based on the evaluation results, the system will further optimize the express storage strategy and user interaction interface design, such as adding an intelligent recommendation function to intelligently recommend the optimal pickup route and shelf location based on residents' pickup history and behavior patterns, further improving the user experience.

[0196] Clustering algorithm detailed explanation:

[0197] Clustering algorithm is an unsupervised learning method used to divide a data set into several groups (or clusters) so that the data points in the same group are similar to each other, while the data points in different groups are quite different. In this embodiment, clustering algorithm is used to identify the behavior pattern of residents' pickup.

[0198] In the above-mentioned resident behavior analysis and service optimization embodiment, the clustering algorithm is a key step in identifying the resident pickup behavior pattern. In order to more specifically illustrate the working principle of the clustering algorithm, specific numerical values ​​are used to demonstrate its application process.

[0199] Specific values ​​of clustering algorithm

[0200] Distance Metrics

[0201] Select Euclidean distance as the distance measurement method. For two-dimensional data (pickup time and pickup building number), the calculation formula of Euclidean distance is:

[0202] d(x,y)=(x1-y1)2+(x2-y2)2

[0203] Among them, x and y are two data points, x1, x2 and y1, y2 are their pickup time and pickup building number respectively.

[0204] It should be noted that since the pickup building number is a discrete value (such as 1, 2, 3, etc.), it needs to be converted into a form that can calculate the distance. Map each building number to a unique value (such as building 1 is mapped to 1, building 2 is mapped to 2, and so on).

[0205] Clustering process

[0206] initialization:

[0207] Set the number of clusters k (to 2, i.e. divide the data into two clusters).

[0208] Randomly select k data points as initial cluster centers.

[0209] Allocate clusters:

[0210] Calculate the distance from each data point to the cluster center and assign it to the cluster with the closest cluster center.

[0211] Update cluster centers:

[0212] Recalculate the cluster center of each cluster (that is, the average value of all data points in the cluster).

[0213] Iteration:

[0214] Repeat steps 2 and 3 until the cluster center no longer changes or the preset number of iterations is reached.

[0215] result

[0216] After the above clustering process, the following two clusters are obtained:

[0217] Cluster 1: contains data points where the pickup time is mainly concentrated between 6pm and 8pm, and the pickup building numbers are mainly Building 1 and Building 2.

[0218] Cluster 2: contains data points with other pickup times and building numbers.

[0219] Behavioral analysis

[0220] According to the clustering results, the following behavioral analysis can be obtained:

[0221] Popular building numbers: Building 1 and Building 2 are popular building numbers because they account for a large proportion of cluster 1.

[0222] Peak Hours: 6pm to 8pm is the peak hour because the data points in cluster 1 are mainly concentrated in this time period.

[0223] Strategy adjustment and optimization

[0224] Based on the above behavior analysis results, the express delivery storage strategy can be adjusted, such as placing express deliveries from popular buildings on the shelves of corresponding buildings before peak hours.

[0225] Through the above workflows and numerical examples, we can clearly see that by accurately identifying residents' pickup behavior patterns and adjusting the express storage strategy and user interaction interface design accordingly, we can significantly improve pickup efficiency, shelf turnover rate and resident satisfaction, providing strong support for the continuous optimization and upgrading of the smart express cabinet system.

[0226] In addition, the components designed in the present invention are all universal standard parts or components known to technical personnel in this field. Their structures and principles can be known to technical personnel through technical manuals or through conventional experimental methods. They can be fully implemented by technical personnel in this field. Needless to say, the content protected by the present invention does not involve improvements to internal structures and methods.

[0227] The embodiments of the present invention disclose preferred embodiments, but are not limited thereto. A person skilled in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not deviate from the spirit of the present invention, they are all within the protection scope of the present invention.

Claims

1. An intelligent access information management system for express delivery stations, characterized in that: include: A pre-layout unit is used to pre-set different shelves inside the express station room according to the building number layout of the community, each shelf represents a building number, and the gaps between the shelves represent different floors; The 3D modeling unit uses 3D imaging technology to accurately model the shelves in the room according to the building numbers of the community, forming a virtual shelf layout diagram, and marking the floor information represented by each shelf and its gap in the virtual layout; The express information entry unit is set in the express delivery area, including an image recognition module and a barcode / QR code scanning module, which is used to scan and recognize the building number, floor number, express delivery order number and other information on the express delivery when the express delivery is delivered to the warehouse, and bind this information with the information of the express delivery itself; The intelligent express delivery robot is equipped with lifting, moving and positioning functions, and is used to move the express delivery from the storage area to the shelf representing the corresponding building number according to the information entered by the express delivery information entry unit, and accurately place the express delivery in the gap of the corresponding floor of the shelf according to the floor number information; Large express handling unit: when the size of the express is larger than the gap between shelves on the corresponding floor, the intelligent express robot will move the express to the large express storage area, which is equipped with freely addable modules and automatically height-adjustable shelves to accommodate large express storage of different sizes and quantities; The data processing and control unit is connected to the express information entry unit and the intelligent express robot for receiving and processing express information, planning the moving path and lifting height of the intelligent express robot, controlling the intelligent express robot to move and place the express, monitoring the use of the large express storage area, and prompting to add or remove modules as needed; The user interaction interface provides residents with the function of querying the express delivery storage location and pickup code, and supports multiple query methods such as mobile phone APP, web page or on-site touch screen; Security protection units, including surveillance cameras, intrusion detection sensors and emergency stop buttons, are used to ensure the safe operation of the express delivery station and prevent the loss or damage of express parcels; The system expansion interface allows the free addition of additional intelligent express robots, large express storage area modules, computing resources of the data processing and control unit, etc. according to the growth of express delivery volume in the community, so as to improve the processing power and flexibility of the system.

2. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The three-dimensional modeling unit also includes a virtual navigation module for displaying the position and movement path of the intelligent express robot, as well as the occupancy of shelves and gaps in real time on a virtual shelf layout diagram to facilitate monitoring and management by managers.

3. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The intelligent express delivery robot is equipped with obstacle avoidance sensors and path planning algorithms to detect and avoid obstacles during movement, optimize the movement path, and ensure the safe and efficient movement of express delivery.

4. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The large express storage area is equipped with automatic sorting modules and intelligent handling equipment, which are used to further classify, store and transport large express items according to their size, weight and type, so as to improve the efficiency of picking up items and the utilization rate of storage space.

5. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The data processing and control unit is also used to record and analyze residents' pickup behavior data, including pickup time, frequency, preferences, etc., to optimize the express storage location and pickup process and improve overall service efficiency.

6. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The user interaction interface also provides value-added service functions such as appointment pickup, express storage, and collection and delivery on behalf of others to meet the diverse express delivery needs of community residents.

7. The intelligent storage and access information management system for express delivery stations as claimed in claim 1, characterized in that: The security protection unit also includes an intelligent door lock and an identity authentication module, which are used to control the opening and closing of the storage and retrieval windows to ensure that only authenticated community residents or authorized personnel can take away the express delivery.

8. The intelligent storage and access information management system for express delivery stations as claimed in claim 1, characterized in that: The system expansion interface also includes an integration interface with other intelligent systems to achieve interconnection and data sharing between the intelligent express station and other intelligent systems in the community.

9. The intelligent storage and access information management system of the express delivery station as claimed in claim 1, characterized in that: The intelligent express delivery robot is also equipped with a size recognition module, which determines whether it exceeds the ordinary shelf gap. If it does, the robot will automatically move it to a large express delivery storage area.

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