38 results about "Delivery efficiency" patented technology

The invention discloses a causal evaluation method for advertisement putting. The method comprises the following steps: acquiring a plurality of data sets of advertisements put on a take-out platform by merchants operating on the take-out platform; inputting the plurality of data sets into a causal graph mining model set to obtain a first candidate causal graph set; filtering the first candidate causal graph set based on an expert knowledge base to obtain a second candidate causal graph set; obtaining the weight of the path according to the relationship between the node and the path of each second candidate causal graph in the second candidate causal graph set, and aggregating the plurality of second candidate causal graphs based on the weight of the path to obtain a causal assessment large graph; and based on the causal evaluation large graph, evaluating the causal relationship between the advertising parameters and the effect indexes of the merchant advertising. According to the method, the accuracy of advertisement effect evaluation can be improved through accurate causal relationship analysis, the advertisement putting efficiency can be improved, and the putting strategy can be optimized.

The application relates to the technical field of intelligent robots, and provides a service type water delivery robot, which comprises a universal chassis and a delivery support, the delivery support is arranged on the universal chassis, one side of the delivery support is provided with a touch screen and a visual identification module; the delivery support is further provided with a top plate and a water storage layer, the top plate is arranged above the delivery support, and the water storage layer is provided with a plurality of placing barrels which are arranged in an inclined mode and face the outer side of the delivery support. Based on this, the problem of jolting of bottled water during delivery can be solved, the delivery efficiency is improved, and the user experience is improved.

This invention discloses a goods delivery vehicle and an unmanned delivery system, relating to the field of vehicle technology. The specific implementation of the method includes: a cargo compartment having one or more cargo channels; a first conveyor belt installed in each cargo channel for transporting goods; and a transfer mechanism for receiving goods from the first conveyor belt and transferring the goods outside the cargo compartment. This implementation uses the cargo channels within the cargo compartment and the first conveyor belt within those channels to transport goods from the cargo compartment to the transfer mechanism, and then the transfer mechanism transfers the goods outside the cargo compartment, thereby achieving automatic unloading of goods from the cargo compartment of the goods delivery vehicle. This saves a significant amount of manual operation, reduces delivery costs, and improves delivery efficiency.

The invention discloses a method for predicting the delivery efficiency of an LNP delivery carrier based on data enhancement and an integrated learning model, and the method comprises the steps: collecting test data, carrying out the enhancement of the test data, and forming a data set of the delivery efficiency of the LNP delivery carrier; dividing a data set; building a model; model training and evaluation; predicting delivery efficiency; according to the method, through data enhancement, the diversity of a data set and the generalization ability of a model are remarkably improved; due to the application of the integrated learning model, the prediction accuracy and robustness are improved; the optimization of the feature engineering enables the model to more accurately capture the rule of the delivery efficiency of the LNP delivery carrier.

The present application relates to a kind of meal delivery device and its meal delivery method, meal delivery device includes meal delivery track and meal delivery trolley, the meal delivery track is arranged with several groups of positioning chip at interval inside, the bottom of the meal delivery trolley is equipped with the electromagnetic sensor matched with several groups of the positioning chip.Meal delivery method includes: waiter places meal on meal delivery trolley, then control computer sends out the dispatching instruction;Meal delivery trolley departs, and the electromagnetic sensor in the bottom of meal delivery trolley transmits the position data of meal delivery trolley to control computer after scanning the positioning chip on meal delivery track;The position where meal delivery trolley is currently located is judged by control computer, and path planning instruction is sent to meal delivery trolley;Meal delivery trolley is parked according to path planning instruction and travels to specified table.The position information where meal delivery trolley is located is obtained by electromagnetic sensor and positioning chip in the present application, and preset planning meal delivery path is avoided to collide with multiple vehicles, to improve meal delivery efficiency and reduce failure rate.

This application provides a method, system, and device for sending parcels. The method belongs to the field of logistics technology. The method includes: obtaining the parcel code information corresponding to the delivery order sent by the business system; after receiving a successful pickup notification from a smart locker, sending a takeoff command to a drone and locking the smart locker; when the drone is preparing to land, sending a landing request to the smart locker; after receiving a landing permission message from the smart locker, landing in the smart locker; after completing the loading according to the loading request sent by the smart locker, sending a loading result success message to the smart locker, so that the smart locker performs calibration and repositioning operations based on the loading result success message and then sends a takeoff notification to the drone; and flying away from the smart locker according to the received takeoff notification. According to this application, by using a drone and smart locker collaborative parcel sending mode, time and resources are fully utilized, improving delivery efficiency and user experience.

This invention discloses a real-time masking system and method for scenes inside windows during drone delivery, belonging to the fields of video processing, artificial intelligence, and drone delivery technology. The system comprises eight modules: drone mounting, video acquisition, AI target detection, masking parameter configuration, masking processing, edge optimization, data storage, and control. The method, based on this system, achieves fully automated masking throughout the entire process. It can accurately distinguish between areas inside and outside the window, masking private areas inside the window in real time with a masking response time ≤0.5 seconds and a transmission delay ≤1 second. Edge feathering optimization eliminates abruptness, supports original video restoration and private storage, balancing privacy protection, delivery efficiency, and compliance requirements. It is applicable to various drone last-mile delivery scenarios, demonstrating strong practicality and scalability.

This invention relates to the field of intelligent delivery and autonomous navigation technology, specifically to an intelligent delivery vehicle. It includes a vehicle body assembly and a charging pile assembly. A transmission assembly is installed at the bottom of the vehicle body assembly, and a top-mounted temperature control and insulation device is installed inside the roof at the top of the vehicle body assembly. A binocular camera and millimeter-wave radar are installed at the front upper part of the roof. A food dispensing port is located at the rear of the vehicle body assembly. A transmission-driven food storage device is installed inside the vehicle body assembly, and temperature sensors and Hall effect sensors are installed on the food storage unit. The transmission-driven food storage device is driven by a drive mechanism. A main control chip is also installed inside the vehicle body assembly. The top-mounted temperature control and insulation device, temperature sensors, Hall effect sensors, transmission assembly, binocular camera, millimeter-wave radar, and drive mechanism are all controlled by the main control chip. This invention achieves full-process automation from order receiving, intelligent loading, dynamic route planning, precise delivery, seamless food dispensing to autonomous charging, adapting to complex campus scenarios, reducing operating costs, and significantly improving delivery efficiency and safety.

The present application relates to the technical field of low-altitude aircraft scheduling, and particularly relates to a low-altitude aircraft cluster task scheduling method and system based on big data, which comprises the following steps: generating a predicted delivery time length through a time sequence feature hybrid model based on historical data of a low-altitude aircraft distribution big data platform, wherein the time sequence feature hybrid model is constructed based on LSTM and Transformer network architecture; constructing an operational decision model with the optimization objective of minimizing the average of multiple predicted delivery time lengths and the decision variable of order allocation mode; and solving the operational decision model based on a multi-objective search strategy to determine the order allocation mode of the low-altitude aircraft cluster. The present application realizes the balance between instant response and global efficiency in low-altitude aircraft cluster scheduling, improves the adaptability of dynamic delay scheduling strategy, and improves the delivery efficiency and reduces the overtime rate.

This invention discloses a drone-vehicle collaborative delivery route planning method considering dynamic requests. It employs a two-stage solution process based on clustering-based scenario prediction, comprising: Stage 1: Generating initial delivery routes for predetermined static demands, and then delivering goods according to these routes; Stage 2: Continuously monitoring for newly generated demands during the delivery process. For new demands, the current drone and truck positions are evaluated, and the demands are inserted into unexecuted routes using an insertion algorithm. This process continues until the end of the work cycle, forming the final delivery plan. This invention can solve collaborative path planning for trucks and drones in dynamic scenarios, thereby improving overall delivery efficiency and reducing overall delivery distance.

The utility model relates to automatic equipment technical field, concretely is a kind of automatic delivery equipment, including delivery warehouse, multiple load plate and drive delivery warehouse reciprocating motion's delivery unit;The in-warehouse transfer mechanism is provided in the delivery warehouse;The feeding connection unit and at least one feeding transfer unit are provided in the feeding place of the delivery unit, and the delivery unit is provided with the unloading connection unit and at least one unloading transfer unit;This automatic delivery equipment can improve delivery efficiency, carry out automatic transfer transport, split transfer and handling work, reduce failure risk, can be quickly maintained and replaced, reduce artificial waiting time;The feeding transfer unit and the unloading transfer unit of multiple groups are combined with the in-warehouse transfer mechanism, avoid goods more when waiting for goods and frequent manual handling;Overall split transfer and handling position, realize automatic delivery, reduce waiting for goods loading time, improve overall delivery efficiency.

A secure storage system featuring enhancements for simplified and cost-effective tethering, user convenience, and aesthetic appeal. The system includes innovative tethering methods and mechanisms for securely attaching the storage system to external structures, ensuring ease of use and robust security at a low cost. Additional features focus on improving user experience, including simplified operation, enhanced delivery efficiency, and real-time monitoring of storage capacity and system status. The disclosed methods and systems enable secure and efficient access while providing valuable feedback and capacity information to users and delivery services. In some embodiments, the system supports coordinated aerial delivery in which access to a storage compartment is controlled in coordination with an aerial delivery device, including embodiments in which a delivery opening is physically covered during package transfer.

This application provides an adaptive path planning method and system for urban distribution networks based on spatiotemporal correlation prediction, relating to the field of urban logistics and distribution technology. First, it obtains a set of constraint parameters for delivery tasks and a set of basic traffic parameters for the urban road network structure. Then, it constructs an initial solution space set for delivery paths based on these parameters. Next, it analyzes the travel time dependency relationship of road segment allocation sequences, generating travel time correlation parameters and travel time impact propagation parameters. Finally, it performs structural redundancy identification and dynamic response integration processing based on these parameters to generate a path decision set responding to real-time traffic events. This invention can perceive traffic conditions in real time and dynamically optimize delivery paths, improving delivery efficiency, accuracy, and reliability, reducing delivery costs, and enhancing customer satisfaction.

This invention discloses a data transmission method, apparatus, electronic device, and storage medium. The method includes: receiving a target data request from a target object and determining whether the target data corresponding to the request is stored in a cache; if the target data is stored in the cache, then providing the target data to the target object; if the target data is not stored in the cache, then acquiring the target data and storing it in the cache, and finally sending the target data to the target object after caching. By adopting the technical solution of this application, by receiving a target data request from a target object and determining whether the target data corresponding to the request is stored in a cache; if the target data is stored in the cache, then providing the target data to the target object; if the target data is not stored in the cache, then acquiring the target data and storing it in the cache, and finally sending the target data to the target object after caching, delivery efficiency is improved when dealing with batch data delivery.

This invention discloses a multi-objective vehicle routing optimization method that considers both loading rate and transportation mileage. The method involves: acquiring order data of orders to be delivered and vehicle rated load and current location data; constructing an order load feature vector based on cargo weight and volume; clustering orders according to load differences to form multiple order clusters; assigning an initial priority label to each order cluster; sorting the order clusters according to the initial priority labels; merging the order clusters based on their spatial location information and loading rate constraints to generate an initial vehicle route; constructing a multi-objective collaborative optimization route evaluation model to optimize the initial vehicle route, generating a set of alternative route schemes; and selecting the route scheme with the highest comprehensive score as the final route scheme output. This invention can effectively reduce scheduling complexity, improve vehicle loading and delivery efficiency, and enhance the stability and practical feasibility of route decisions.

This invention relates to the field of logistics route planning technology, and more particularly to a logistics route dynamic planning system based on reinforcement learning, including a logistics planning and management center, a data acquisition module, a processing and acquisition module, a delivery access module, a verification and optimization module, a dynamic planning module, and a feedback module. This invention achieves dynamic perception and real-time adaptation of logistics scenarios through multi-dimensional data acquisition and fusion processing. It also constructs an initial route framework based on road network topology, reducing subsequent adjustment costs, and builds a region-weight-timeliness coordinated delivery access sequence to avoid time waste caused by cross-regional round trips. Furthermore, through time chain verification, it can quickly resolve conflicts and inefficient route problems without disrupting the overall sequence. In addition, for the optimal selection of multiple candidate planned routes, a weighted scoring method is used to achieve a dynamic balance of time, cost, and reliability, significantly improving delivery efficiency, reducing operating costs, and ensuring delivery reliability.

The embodiment of the application provides a data service method and equipment, wherein the data service method comprises the following steps: obtaining a service creation request corresponding to a data label; determining a data source of the data label and a destination address used for realizing data service based on the service creation request; and performing data service processing based on the data source and the destination address to obtain a target service corresponding to the data label. The technical scheme provided by the embodiment performs data service processing based on the determined data source and destination address to obtain a target service corresponding to the data label, effectively realizing automatic data service operation. Since collaborative operation is not required during the data service process, the delivery time of the data service is effectively shortened, the delivery efficiency of the target service is improved, and the quality and efficiency of the data service are further ensured.

The application discloses an intelligent cabinet control method based on intention recognition, an intelligent cabinet and a storage medium, relates to the technical field of intention recognition and intelligent cabinet control, and comprises the following steps: identifying whether a user in the vicinity of a smart cabinet in a sensing range of the smart cabinet is an authorized user; if the user in the vicinity of the smart cabinet is an authorized user, obtaining behavior characteristic information and movement trajectory data of the authorized user; generating an open-door intention signal according to the behavior characteristic information and the movement trajectory data; obtaining a current service state of the smart cabinet; and based on the current service state and the open-door intention signal, controlling opening and closing of a cabinet door of a corresponding target compartment of the smart cabinet, so as to complete a delivery process or a pick-up process. The scheme solves the problem that the overall operation process of an existing intelligent cabinet is relatively complicated, realizes safe, efficient and non-sensitized intelligent package delivery and pick-up, and improves the delivery efficiency of a logistics terminal and the user experience.

This invention discloses a standardized delivery method and system for BIM model data during the design phase of high-speed railway simply supported beam bridges, belonging to the technical field of design data for high-speed railway simply supported beam bridges. The method includes: a processing module splitting the initial BIM model of the high-speed railway simply supported bridge to obtain multiple first sub-models; a collaborative terminal performing spatial position calibration and design on the first sub-models to obtain second sub-models; edge nodes retrieving the second sub-models and performing basic verification processing, sending them as third sub-models to a cloud server; the cloud server integrating all third sub-models to obtain an overall BIM model and performing compliance verification on it to obtain a first verification result, uploading the first verification result and each third sub-model to the processing module; and the processing module correcting each third sub-model based on the first verification result to form a standard BIM model for the high-speed railway simply supported beam bridge. This method can improve the delivery efficiency of BIM model data during the design phase of high-speed railway simply supported beam bridges.

The utility model provides a new energy raw material storehouse ton bag stack package receiving and dispatching system, including many wear storehouse, two layer straight line shuttle vehicle, two layer conveying line, unstacking and stacking part, AGV connection conveyer, AGV lurk robot, one layer straight line shuttle vehicle, one layer conveying line, this system divides two layers, two layer straight line shuttle vehicle, two layer conveying line, unstacking and stacking part, AGV connection conveyer, AGV lurk robot set up in two layers, one layer straight line shuttle vehicle, one layer conveying line set up in one layer, this application can solve the problem that new energy raw material storehouse ton bag delivery exists, improves warehouse use efficiency and delivery efficiency, increases the loading capacity of single vehicle, saves the cost for enterprise.

This invention relates to the field of intelligent logistics technology, and in particular to a dynamic tag data management method, apparatus, device, and storage medium. The method first acquires the logistics trajectory data of the current parcel order and a preset similarity threshold. The logistics trajectory data undergoes data filtering processing. Based on the obtained target data, scanning station codes and terminal station codes are acquired. A list of outlet codes is obtained based on the terminal station codes. The similarity value between the scanning station code and each outlet code in the list is calculated. Based on the multiple similarity values, a highest similarity value is determined. This highest similarity value is compared with a similarity threshold. When the highest similarity value is less than or equal to the similarity threshold, it is determined whether the current parcel order has a misdelivery tag. Based on the determination result, the current parcel order is tagged to obtain a tagged parcel order. This aims to improve the accuracy of misdelivery identification and increase last-mile delivery efficiency.

This invention relates to the field of IoT mobile delivery technology, and in particular to an IoT-based mobile shopping cart collaborative delivery method and system. The method includes: collecting shopping cart status, delivery tasks, and regional environmental data through IoT terminals; extracting delivery scenario feature factors through edge computing preprocessing; and associating these factors to form a single set of delivery data. Cross-device interaction is achieved using an IoT gateway. Multiple sets of data are classified using a K-means clustering algorithm and combined with historical best solutions to generate a first collaborative delivery strategy. During delivery, dynamic interference factors are monitored through an IoT sensing network. After anomaly index evaluation, the strategy is corrected using a Kalman filter algorithm to obtain a second collaborative delivery strategy. This strategy is then distributed to the execution terminal based on a distributed decision-making algorithm on an IoT cloud platform, realizing multi-shopping cart route planning, task allocation, and capacity coordination. This effectively solves the problems of poor adaptability, low intelligence, and low delivery efficiency in existing technologies.

This application provides a cargo transportation method, system, and equipment. The method belongs to the field of logistics technology. The method includes: acquiring first real-time information of a drone and second real-time information of an automated unloading rack; sending a takeoff command to the drone and a waiting command to the automated unloading rack based on the first and second real-time information; after receiving landing information from the drone, sending a dropping command to the drone to release cargo; after receiving takeoff status information from the drone, sending a horizontal pusher movement command to the automated unloading rack to allow cargo to enter the warehouse under the pushing force of the horizontal pusher; and after receiving cargo entry information from the automated unloading rack, dispatching an unmanned vehicle to the automated unloading rack to receive the cargo according to the user's delivery time, and delivering the cargo to the user's delivery address at the delivery time. According to this application, labor costs are reduced, and delivery efficiency and user experience are improved.

The application discloses a WMS-based intelligent management interconnection system and relates to the technical field of warehouse logistics management. The application is applied to a cargo storage warehouse and comprises a first line conveying mechanism sequentially passing through a plurality of storage areas, a first track conveying mechanism parallel to the first line conveying mechanism and a carrying mechanism arranged on the first track conveying mechanism. The carrying mechanism can move back and forth among the plurality of storage areas through cooperation of the first conveying mechanism, and when there is cargo in the corresponding storage area, the carrying mechanism can complete cargo taking, and the first line conveying mechanism can convey the cargo out of the warehouse. In the whole process, under the information scheduling of the WMS system, the carrying mechanism selectively grasps the cargo without ordering the time of the cargo, so compared with the process of taking the cargo by relying on manual work in the prior art, a large amount of time is saved, and the overall delivery efficiency is greatly improved.

The present application relates to the technical field of information processing, and particularly relates to a smart map grouping and aggregation method and device, equipment and a storage medium, wherein package data collected after a deliveryman scans a package barcode is acquired, the address of the receiving address in the package data is analyzed, the target AOI to which the current package belongs is determined according to the analysis result, the target AOI and the corresponding package data are projected to a map, and the package aggregation quantity in the target AOI is marked on the map, the division of the interest area can be dynamically optimized, and the package data can be visually aggregated and displayed, the optimal delivery route is generated according to all the AOIs with the package aggregation data in the map, when the current package is signed, the current package is removed from the package aggregation data of the target AOI, the optimal delivery route and the package aggregation quantity on the map are synchronously updated, the updated optimal delivery route is sent to the mobile terminal of the deliveryman, the optimal delivery route is dynamically updated, and the package delivery efficiency is improved.

This application pertains to the field of logistics and distribution, specifically an intelligent logistics and distribution dispatch system. The system includes a terminal server comprising an order receiving module, a data analysis module, an intelligent dispatch module, a vehicle monitoring module, a route planning module, a communication module, and a user exchange module. The order receiving module receives logistics and distribution order information from e-commerce platforms, customer terminals, and other channels, including order number, shipping address, delivery address, cargo weight, volume, and delivery time requirements. After formatting the order information, it transmits it to the data analysis module, which analyzes and processes the received order information. This application features a reasonable design, achieving intelligent order processing and efficient vehicle dispatch through multi-module collaboration. Combined with an optimized design incorporating GPS positioning devices, it improves delivery efficiency, reduces costs, ensures stable equipment operation, and enhances customer and logistics management satisfaction.

This invention discloses a scheduling method, apparatus, and storage medium for auxiliary agent delivery. The method includes: acquiring the call time and delivery time of the auxiliary agents required by the dyeing machines in each workshop; determining several scheduling schemes according to the delivery order of all the auxiliary agents; calculating the overall waiting time of each scheduling scheme based on the several scheduling schemes and the call time and delivery time of the auxiliary agents; acquiring the scheduling scheme with the minimum overall waiting time as the optimal scheduling scheme; and delivering the auxiliary agents according to the delivery order of the optimal scheduling scheme, thereby reducing the overall waiting time of the dyeing machines and improving the delivery efficiency of the auxiliary agents.

The application discloses a kind of intelligent summary and linkage export system and method based on GitLab, the system is configured through common base, for storing GitLab core configuration, the association of solution and the branch of multiple applications, provide unified resource range benchmark for double independent function link;Double independent function link includes project information integration link and multi-scene output link, project information integration link obtains GitLab configuration and commit information from GitLab platform, in turn complete data processing, achievement transformation, report generation and linkage push of instant office software;Multi-scene output link only obtains GitLab configuration from GitLab platform, in turn complete source code association configuration, source code acquisition, submodule integration and packing delivery.The application can realize the technical effects of improving the adaptability of system to fixed opening delivery scene, overall delivery efficiency and stability, while reducing delivery risk and artificial intervention cost.

This invention relates to the field of oil depot management technology, specifically disclosing a smart oil depot's full lifecycle data management system and method. The system constructs a data lineage graph G using a globally unique object code (UOID) as the primary key, achieving unified identification and continuous association of multi-source heterogeneous data during the construction and operation phases. Upon receiving a change event queue Q, it triggers a domain-limited traversal to obtain the set of affected objects U. aff And generate a minimum set of changed objects U min Only for U min Perform cross-modal alignment verification and rule base consistency verification to generate a structured record of discrepancies; based on this, generate a differential delivery package, calculate the consistency score S, and compare it with the acceptance threshold T. acc The comparison enables automatic determination and review of delivery nodes; at the same time, the acceptance results and lineage snapshots are solidified into a version backtracking chain, supporting traceability, auditing and rollback, improving data consistency and delivery efficiency.