A mountainous area low-altitude logistics information recommendation method, device and equipment

Abstract

This application provides a method, apparatus, and equipment for recommending low-altitude logistics information in mountainous areas, belonging to the field of data processing technology. The method includes: determining multiple candidate pilots based on logistics demand; generating pricing lists for each candidate pilot based on the multiple candidate pilots and the logistics demand; constructing a logistics pricing list based on the pricing lists of each candidate pilot; pushing the logistics pricing list to a user; and having the user select a target pilot based on the logistics pricing list. The method, apparatus, and equipment for recommending low-altitude logistics information in mountainous areas provided by this application are used to improve the efficiency of logistics transportation in mountainous areas and reduce labor costs.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus and equipment for recommending low-altitude logistics information in mountainous areas. Background Technology

[0002] As an emerging industry, the low-altitude economy has shown significant application value in the field of mountain logistics. Due to geographical and topographical limitations, traditional ground logistics in mountainous areas suffers from problems such as low transportation efficiency, high coverage costs, and difficulty in reaching the last mile.

[0003] Currently, some preliminary service models have emerged in the mountainous low-altitude logistics sector. These models primarily facilitate transportation services by connecting CAAC-licensed captains with logistics demanders on a piecemeal basis. Some regions are experimenting with establishing simple information matching platforms to provide basic order posting and acceptance functions. However, current technology relies heavily on manual qualification verification for captain management, logistics demand matching is mainly based on distance, and pricing methods often employ fixed unit prices or negotiated pricing. Some services include basic transportation insurance, but overall, the operation remains fragmented and non-standardized, lacking a systematic service architecture. This results in demanders struggling to accurately assess captains' professional capabilities, and captains unable to consistently secure orders matching their abilities, leading to inefficient supply-demand matching. Summary of the Invention

[0004] In view of this, this application provides a method, apparatus and equipment for recommending low-altitude logistics information in mountainous areas, in order to improve the efficiency of logistics transportation in mountainous areas and reduce labor costs.

[0005] Specifically, this application is implemented through the following technical solution:

[0006] The first aspect of this application provides a method for recommending low-altitude logistics information in mountainous areas, the method comprising:

[0007] Multiple candidate captains were determined based on logistics requirements;

[0008] A pricing list for each candidate captain is generated based on the multiple candidate captains and the logistics requirements.

[0009] A logistics pricing list is constructed based on the pricing lists of each candidate captain, and the logistics pricing list is pushed to the user, who then selects a target captain based on the logistics pricing list.

[0010] A second aspect of this application provides a low-altitude logistics information recommendation device for mountainous areas, the device comprising a determining module, a generating module, and a recommending module; wherein...

[0011] The determining module is used to determine multiple candidate aircraft captains based on logistics requirements;

[0012] The generation module is used to generate a pricing list for each candidate captain based on the plurality of candidate captains and the logistics requirements.

[0013] The recommendation module is used to construct a logistics pricing list based on the pricing lists of each candidate captain, push the logistics pricing list to the user, and the user selects a target captain based on the logistics pricing list.

[0014] A third aspect of this application provides a low-altitude logistics information recommendation device for mountainous areas, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of any of the methods provided in the first aspect of this application.

[0015] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods provided in the first aspect of this application.

[0016] The method, apparatus, and equipment for recommending information on low-altitude logistics in mountainous areas provided in this application optimize the supply and demand matching model for low-altitude logistics in mountainous areas, achieving the dual core objectives of improving logistics transportation efficiency and reducing labor costs. Simultaneously, it provides users with a transparent and selectable service experience, effectively addressing the pain points of fragmented supply and demand matching and redundant processes in traditional low-altitude logistics in mountainous areas. Specifically, it determines candidate captains based on logistics needs, replacing the traditional manual captain screening model, quickly locating suitable service resources and avoiding captain matching delays caused by information asymmetry; it also shortens the communication cycle between supply and demand parties, eliminating the need for users to repeatedly negotiate service details with captains, allowing them to directly select a target captain based on a pricing list, significantly reducing the overall time from order initiation to confirmation, especially suitable for efficiency needs in scenarios such as emergency material delivery and time-sensitive agricultural product transportation in mountainous areas; traditional low-altitude logistics in mountainous areas relies on manual processes for captain qualification verification, order matching, and pricing negotiation, which not only consumes a large amount of manpower but is also prone to errors due to human operation; this application automatically completes the determination of candidate captains through a standardized process. Price list generation and pricing list construction require no manual intervention throughout the entire process. This reduces the manpower required for manual review and communication, and avoids additional costs such as mismatches and negotiation disputes caused by manual operations, thereby lowering the labor and management costs of low-altitude logistics operations in mountainous areas. The logistics pricing list built based on the candidate captain pricing list provides users with transparent information including multiple captain options and corresponding pricing. Users can intuitively compare the service quotes of different candidate captains and independently choose the target captain that meets their budget and needs, avoiding the information opacity problems of traditional negotiation models. At the same time, the structured presentation of the pricing list also reduces the difficulty of user decision-making, improves the convenience of service selection, and further optimizes the user experience for those with logistics needs in mountainous areas. Attached Figure Description

[0017] Figure 1 A flowchart of an embodiment of the method for recommending low-altitude logistics information in mountainous areas provided in this application;

[0018] Figure 2 This is a hardware structure diagram of a low-altitude logistics information recommendation device for mountainous areas, where the low-altitude logistics information recommendation device of this application is located.

[0019] Figure 3 This is a schematic diagram of the structure of Embodiment 2 of the mountainous low-altitude logistics information recommendation device provided in this application. Detailed Implementation

[0020] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0021] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used herein are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0022] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0023] The following specific embodiments are given to illustrate the technical solution of this application in detail.

[0024] It should be noted that the method for recommending low-altitude logistics information in mountainous areas provided in this application is applied to mountainous regions. Mountainous transportation scenarios are characterized by complex terrain, such as numerous valleys, high altitudes, steep slopes, sparse ground transportation networks (narrow rural roads, and some areas without paved surfaces), limited transportation routes (susceptible to natural disasters such as flash floods and landslides), and significant challenges in achieving last-mile delivery. For the transportation needs of fresh agricultural products, emergency supplies, and agricultural production materials, traditional ground transportation suffers from time-consuming, costly, and high cargo loss rates. Low-altitude logistics, with its advantages of high flexibility, minimal terrain limitations, and rapid response, has become the preferred solution for meeting the transportation needs of mountainous areas. In mountainous transportation scenarios, logistics demanders need to quickly connect with professional pilots capable of flying in mountainous areas, and simultaneously clarify the pricing and service matching of transportation services. Therefore, a standardized process is required to achieve precise matching of logistics needs with pilot resources.

[0025] Figure 1 This is a flowchart of an embodiment of the method for recommending low-altitude logistics information in mountainous areas provided in this application. Please refer to... Figure 1 The method provided in this embodiment may include:

[0026] S101. Determine multiple candidate captains based on logistics needs.

[0027] Specifically, logistics demand refers to all the requests and key information put forward by users (such as farmers, cooperatives, township enterprises, etc.) to realize the transportation of goods. It is the core basis for matching candidate captains and generating pricing lists. Logistics demand includes at least cargo information, transportation route information, and timeliness requirements. Candidate captains refer to captains selected from the captain pool who meet the logistics demand. A captain is a professional operator with legal qualifications who is responsible for operating low-altitude aircraft (such as drones, light general aviation aircraft, etc.) to complete cargo transportation tasks.

[0028] Furthermore, the logistics demand information is analyzed to extract parameters such as cargo type, cargo value, transportation distance, urgency, and geographical features of origin and destination. The transportation distance also includes transportation altitude. A demand screening model is established based on the parameters, and a basic threshold for captain matching is set. Captains who meet the threshold conditions are screened from the captain database, and a second filtering is performed based on the actual reachability distance between the captain's current location and the origin and the current order load. The filtered captains are sorted according to their matching degree with logistics demand, and the top N are selected as candidate captains.

[0029] Furthermore, by analyzing logistics demand in a structured manner, the core requirements of the transportation scenario are clarified (such as the characteristics of the cargo determining the requirements for the captain's operational skills, and the urgency determining the requirements for the captain's response speed). Secondly, by setting threshold conditions (such as qualifications, equipment, and location), obviously unsuitable captains are excluded to reduce invalid matches. Finally, by ranking the matching degree, it is ensured that the recommended candidate captains can meet the requirements in terms of ability, distance, and load, laying the foundation for subsequent pricing and selection.

[0030] Furthermore, the matching degree calculation needs to cover two major dimensions: logistics demand adaptability and captain service capability. Logistics demand adaptability focuses on the adaptability of cargo type, transportation distance, and timeliness requirements. Cargo type adaptability is judged based on the frequency of the captain's recent transport of similar cargo; the higher the frequency, the better the adaptability. Transportation distance adaptability considers whether the captain's historical transport distance can cover the current demand distance; complete coverage is better than partial coverage, and partial coverage is better than no coverage. Timeliness requirement adaptability refers to the captain's recent on-time completion of orders of the same timeliness; the higher the completion rate, the better the timeliness requirement is met. Captain service capability includes professional qualification matching degree, historical service quality, and real-time adaptability status. Professional qualification matching degree is directly related to the captain's level; the higher the level, the better the qualifications. Historical service quality is reflected by the captain's recent user reviews; the higher the review rate, the more guaranteed the service quality. Real-time adaptability status combines the distance between the captain's current location and the origin of the demand, as well as the load of the captain's current uncompleted orders; the closer the distance and the less the load, the stronger the real-time adaptability.

[0031] Furthermore, the calculation process first collects logistics demand information, captain static data, and dynamic data. Weights are assigned to each dimension according to their importance, and each dimension is scored. The weight of demand suitability is higher than that of captain service capability, ensuring that core needs are prioritized. A weighted sum is then used to obtain a comprehensive matching score. If there are special requirements for logistics needs, the weights of the corresponding dimensions can be adjusted to further calibrate the matching score, making the results more closely reflect actual needs. This transforms fuzzy matching judgments into quantitative results, avoiding subjective errors and ensuring the timeliness and practicality of the matching through the inclusion of dynamic data. This helps the platform accurately select suitable candidate captains, improving the efficiency of supply and demand matching.

[0032] Furthermore, before determining multiple candidate captains based on logistical needs, the method provided in this embodiment includes:

[0033] (1) Obtain multi-dimensional information about the captain;

[0034] Specifically, the multi-dimensional information includes at least the following: weather response capability, CAAC license holding period, historical order completion rate, user evaluation score, equipment compliance, and safe flight time. Weather response capability reflects the captain's ability to adapt to complex weather conditions in mountainous areas; CAAC license holding period refers to the length of time the license has been held by the Civil Aviation Administration of China, which is the core basis for measuring the captain's professional experience and legal operating qualifications; historical order completion rate includes the proportion of orders delivered on time and the reasons for unfulfilled orders, which can directly reflect the captain's sense of responsibility and task execution ability; user evaluation score is based on the evaluation feedback given by the service recipients, focusing on dimensions such as cargo protection, communication and cooperation, and problem handling during transportation, to reflect the captain's service level; compliance test results of the flight equipment used, including whether the equipment model meets the standards for low-altitude logistics in mountainous areas, whether the periodic inspections are qualified, and whether the safety performance meets the standards, are the foundation for ensuring transportation safety; and the cumulative flight time without safety accidents further confirms the captain's practical proficiency and risk control capabilities. Multi-dimensional information can be collected through various channels such as platform registration and review, pilot's proactive reporting, extraction of historical order data, and third-party certification and verification, forming a complete pilot information file, providing a comprehensive, objective, and traceable basis for subsequent quantitative scoring and rating.

[0035] (2) The captain is quantitatively scored based on the multi-dimensional information, and the captain is classified into different levels according to the scoring results. Different levels of captains correspond to different pricing coefficients.

[0036] Specifically, clear and implementable scoring rules are set for each information dimension. Based on the impact of each dimension on the captain's service capabilities and transportation safety, corresponding weights are reasonably allocated. Among them, the dimensions that are directly related to transportation safety and core service quality have a higher weight, ensuring that the scoring results highlight the differences in key capabilities. According to the set rules and weights, each piece of information about the captain is quantitatively scored one by one. The captain's comprehensive score is calculated by weighted summation, realizing the transformation from scattered information to unified quantitative indicators.

[0037] Based on the comprehensive score range, captains are divided into multiple distinct levels, with higher scores corresponding to higher levels, clearly differentiating the service capability tiers of different captains. Simultaneously, a differentiated pricing coefficient is assigned to each level of captain, with higher-level captains having higher pricing coefficients, forming a positive incentive mechanism where stronger service capabilities, higher pricing coefficients, and greater revenue rewards. This model, linking level division with pricing coefficients, provides logistics demanders with a clear and intuitive basis for service selection, helping them quickly match suitable captains to their needs. It also incentivizes captains to improve their professional skills, optimize service quality, and accumulate compliant operational experience to raise their levels, thereby obtaining higher revenue and promoting a virtuous cycle and continuous upgrading of the entire mountainous low-altitude logistics service system.

[0038] Furthermore, after classifying captains according to the scoring results, the method provided in this embodiment also includes:

[0039] (1) Determine the multi-dimensional information of the captain within the assessment period, and score the captain based on the multi-dimensional information of the period;

[0040] Specifically, the dynamic adjustment of captain ranks is based on a fixed assessment cycle. The cycle specifies the multi-dimensional information to be collected within each assessment cycle. This multi-dimensional information focuses on the captain's actual service performance and compliance status within that cycle, including the validity of licenses issued by the civil aviation administration, order completion rate, new evaluation scores from service recipients, the quality of completion of transportation missions under special weather conditions in mountainous areas, cumulative safe flight hours, and compliance test results of flight equipment within the cycle. After collecting complete multi-dimensional information, the standardized scoring system used for captain rank classification is applied, maintaining consistency in the scoring rules and weighting of each information dimension to ensure the continuity and comparability of the scoring results. Each piece of information within the cycle is quantitatively scored according to established rules, and then a weighted sum is calculated to obtain the captain's comprehensive cycle score, comprehensively and objectively reflecting the captain's service capabilities and overall performance within that assessment cycle. It should be noted that the assessment cycle is set according to actual needs; in this embodiment, it is not limited. Multi-dimensional information refers to the multi-dimensional information of the captain within each assessment cycle.

[0041] (2) Adjust the captain's level based on the periodic scoring results.

[0042] Specifically, based on the scoring range corresponding to the captain's current level, and combined with the comprehensive scoring results of the period, clear level adjustment rules are formulated. If the period score is significantly improved compared to the previous period score and reaches the scoring threshold corresponding to the higher level, the captain's level will be promoted, and a higher level of pricing coefficient and service authority will be granted. If the period score is significantly lower than the previous period score and falls below the scoring threshold corresponding to the current level, the captain's level will be downgraded, the pricing coefficient will be reduced accordingly, and the captain's eligibility to accept some high-difficulty and high-time-sensitivity orders will be restricted. If the period score fluctuation is within a reasonable range and does not exceed the scoring range of the current level, the captain's current level will remain unchanged. If the captain experiences a flight safety accident, fails to pass the compliance test of flight equipment, or receives a certain number of valid user complaints during the assessment period, which seriously affects service quality and safety, the emergency level adjustment mechanism will be triggered, and the captain will be directly downgraded and will not be eligible for level promotion in the next assessment period. The rating adjustment results will be pushed to the captain's terminal in real time, and the corresponding rating information and pricing coefficient in the platform's captain database will be updated simultaneously to ensure that the latest rating data is used in time for subsequent order matching and pricing generation, so as to achieve dynamic adaptation between captain rating and service capabilities and continuously incentivize captains to improve their professional skills and service quality.

[0043] Furthermore, the specific steps for determining multiple candidate captains based on logistics needs include:

[0044] (1) Determine logistics information based on the logistics demand, wherein the logistics information includes at least the type of goods, transportation distance and urgency;

[0045] Specifically, the original requests submitted by logistics demanders are structured and analyzed to extract core logistics information, including cargo type, transportation distance, and urgency level. Cargo type must clearly distinguish the attributes and characteristics of the goods, such as whether they are fragile, perishable, ordinary agricultural products, industrial materials, or emergency supplies. Different types of goods have different requirements for protection measures and loading methods during transportation. Transportation distance requires accurate calculation of the actual mileage between the logistics origin and destination, taking into account the characteristics of mountainous terrain and referencing traversable flight paths for distance calibration to ensure accuracy. Urgency level needs to be defined based on the delivery time specified by the demander, clarifying whether expedited transportation is required; different urgency levels correspond to different transportation response priorities. This information collectively forms the core basis for subsequent rating and captain matching, ensuring comprehensive information extraction that aligns with the actual operational scenarios of low-altitude logistics in mountainous areas.

[0046] (2) Calculate the level score of the logistics demand based on the logistics information;

[0047] Specifically, corresponding scoring rules are set based on the attribute characteristics of each piece of logistics information. For cargo type, different scoring levels are divided according to factors such as transportation difficulty, preservation requirements, and value. The higher the transportation difficulty, the stricter the preservation requirements, or the higher the value of the cargo, the higher the corresponding score. For transportation distance, scoring gradients are divided according to mileage ranges. The longer the distance, the higher the requirements for the captain's equipment endurance and flight planning capabilities, and the higher the corresponding score. For urgency, scoring standards are set according to the urgency of delivery time. The shorter the delivery time, the higher the urgency, and the higher the score.

[0048] Furthermore, in conjunction with the operational priorities of low-altitude logistics in mountainous areas, reasonable weights are allocated to three dimensions: cargo type, transportation distance, and urgency. Among these, the dimensions that directly affect transportation safety and service quality have a higher weight. According to the established scoring rules and weight allocation, each piece of logistics information is quantitatively scored, and the level score of logistics demand is obtained by weighted summation. This transforms the scattered logistics information into a unified quantitative indicator, providing a clear basis for subsequent captain matching.

[0049] (3) Match multiple candidate captains from the captain pool based on the rating score.

[0050] Specifically, a mapping rule is established between logistics demand ratings and captain levels. This clarifies the captain level compatibility range for different rating levels of logistics demand. High-rated logistics demand corresponds to captains with higher levels of suitability, ensuring that the captain's professional skills and equipment level can meet the demands of high-difficulty, high-requirement transportation tasks. Medium- and low-rated logistics demand corresponds to captains of the corresponding level or higher, ensuring service quality while considering resource utilization efficiency. Based on the established mapping rule, captains meeting the level compatibility requirements are selected from the captain pool to form an initial candidate captain pool. A second screening is conducted on captains in the initial candidate pool, taking into account the characteristics of mountainous terrain and the actual needs of logistics transportation. This screening focuses on the accessibility of the captain's current location to the logistics origin and the current order load, eliminating captains whose locations are too far away, potentially causing response delays, or whose excessive load could affect transportation timeliness. Finally, the screened captains are ranked according to their match with the logistics demand, and the several captains with the best suitability are selected as final candidate captains, ensuring that the recommended captains can complete transportation tasks efficiently and safely.

[0051] By accurately extracting core logistics information and converting it into quantifiable rating scores, precise matching of logistics needs with pilot capabilities is achieved, significantly improving the efficiency and rationality of supply and demand matching in mountainous low-altitude logistics. This avoids transportation risks or resource waste caused by mismatches between pilot capabilities and demand requirements, and quickly identifies suitable pilots through a scientific rating mapping mechanism, reducing the time costs of ineffective matching. Simultaneously, it ensures that logistics needs of varying difficulty and timeliness can be matched with pilots possessing the corresponding service capabilities, optimizing logistics service quality and user experience, and promoting the standardization and efficiency of mountainous low-altitude logistics services.

[0052] Furthermore, the specific implementation steps for matching multiple candidate captains from the captain database based on the aforementioned rating score include:

[0053] 3.1 Establish mapping rules between rating scores and captain ranks;

[0054] Specifically, based on the range of logistics demand ratings, the matching standards for captain levels corresponding to different rating ranges are clearly defined. High-rated logistics demands correspond to high-level captains, ensuring that high-difficulty, high-time-efficiency, and high-value transportation tasks can be undertaken by captains with strong professional capabilities and excellent service quality. Medium- and low-rated logistics demands correspond to captains of the corresponding level or above, ensuring service compatibility while achieving efficient utilization of captain resources. The mapping rules must fully consider the core elements represented by the captain level, such as professional capabilities, equipment level, and safety record, to form a precise match with the transportation difficulty, time-efficiency requirements, and cargo protection requirements behind the logistics demand ratings, avoiding compatibility issues of overcapacity or undercapacity, and laying the foundation for efficient matching in the future.

[0055] 3.2 Match captains of the corresponding levels according to the mapping rules and the level scores.

[0056] Specifically, based on the established mapping rules, the calculated logistics demand level score serves as the core matching criterion, quickly locating captains in the captain database who meet the level matching requirements. Through the platform system's automated retrieval and filtering, captains whose levels do not meet the requirements are directly filtered out, eliminating the need for manual comparison and significantly improving matching efficiency. This ensures that every logistics demand is matched with a captain possessing the corresponding service capabilities. High-requirement logistics demands can be accurately matched with experienced and qualified high-level captains, guaranteeing transportation safety and timeliness; routine logistics demands can be matched with captains of the appropriate level, achieving rational resource allocation. Simultaneously, the standardized application of the mapping rules avoids subjective errors from human matching, making supply and demand matching more objective and scientific, further promoting the standardized operation of low-altitude logistics services in mountainous areas.

[0057] S102. Generate a pricing list for each candidate captain based on the multiple candidate captains and the logistics requirements.

[0058] Specifically, determine the tiered pricing coefficient for candidate captains; calculate the basic pricing factors for logistics needs: set the mileage unit price based on transportation distance, set the difficulty coefficient based on cargo type, and set the timeliness coefficient based on urgency; calculate the basic price for each candidate captain based on the product of the mileage unit price, tiered pricing coefficient, difficulty coefficient, and timeliness coefficient; add additional fees to generate a pricing list containing detailed pricing components.

[0059] Specifically, the pricing list is generated not only based on the objective characteristics of logistics needs, but also on the captain's service level (the higher the level, the higher the pricing coefficient), ensuring high quality at a fair price; at the same time, by displaying the pricing composition in detail, users can clearly understand the source of the cost, avoiding the lack of transparency issues of the traditional fixed-price model.

[0060] Current pricing for low-altitude logistics in mountainous areas often employs fixed unit prices or negotiated pricing models, leading to issues such as a disconnect between pricing and service quality, and unclear cost structures. By using multi-factor weighted calculations and detailed presentation, both fairness and scientific rigor in pricing are achieved, while also increasing user trust in pricing.

[0061] Furthermore, the specific implementation steps for generating pricing lists for each candidate captain based on the multiple candidate captains and the logistics requirements include:

[0062] (1) Determine the grade of each candidate captain among the plurality of candidate captains, and determine the pricing coefficient of each candidate captain based on the grade;

[0063] Specifically, the system retrieves the rating information for each candidate captain from the captain database. This rating information is based on a quantitative assessment of the captain's multi-dimensional capabilities, objectively reflecting the captain's professional qualifications, service quality, and practical skills. According to a pre-defined rule that corresponds to the rating and pricing coefficient, a unique pricing coefficient is matched for each candidate captain at different ratings. The higher the rating of the captain, the higher the corresponding pricing coefficient, thus reflecting the principle of "high quality, high price." This directly links the captain's service capabilities with the pricing, ensuring reasonable income for high-rated captains and providing a clear basis for price expectations for demanders.

[0064] (2) Determine the flight price for each candidate captain based on the pricing coefficient;

[0065] Specifically, based on the basic pricing standard for the mountainous low-altitude logistics industry, and combined with the exclusive pricing coefficient for candidate captains, the flight price for each candidate captain is determined by multiplying the basic price by the pricing coefficient. The basic pricing standard fully considers common factors such as mountainous terrain and flight costs. Then, by multiplying by the pricing coefficient corresponding to the captain's level, the flight price can not only cover the basic operating costs of the industry, but also accurately reflect the differences in service capabilities of different captains, avoiding the unreasonable situation caused by uniform pricing, and making the pricing more fair and scientific.

[0066] (3) Determine the logistics pricing based on the aforementioned logistics demand;

[0067] Specifically, based on the specific characteristics of logistics demand, key factors influencing additional costs are extracted to determine the components of logistics pricing. Logistics pricing primarily covers additional fees directly related to logistics needs, such as cargo insurance fees, special loading and unloading service fees, and cold chain preservation fees. These fees are calculated based on the actual needs of the demander. For example, insurance fees are charged proportionally when the value of the goods is high, and corresponding service fees are charged when special equipment is required for loading and unloading. The entire logistics pricing process is tailored to the personalized characteristics of logistics needs, ensuring that all additional fees are collected reasonably and transparently, with no hidden costs.

[0068] (4) Determine the pricing of each candidate captain based on the sum of the flight pricing and logistics pricing of each candidate captain, and generate a pricing list based on the pricing of each candidate captain.

[0069] Specifically, the flight price for each candidate captain is summed with the logistics price corresponding to the current logistics demand to arrive at the final price for that candidate captain's logistics service. Based on this final price, a structured pricing document is generated, detailing the specific components and calculation basis of the flight and logistics prices, including basic pricing standards, pricing coefficients, and the amounts of various additional fees. The entire pricing document generation process is automated and standardized, ensuring the accuracy of the pricing results and allowing the client to clearly understand the source of each fee, thus enhancing pricing transparency and credibility and providing comprehensive support for the client's selection decision.

[0070] S103. Construct a logistics pricing list based on the pricing lists of each candidate captain, push the logistics pricing list to the user, and the user selects a target captain based on the logistics pricing list.

[0071] Specifically, a structured template for the pricing list is designed, including fields such as candidate captain level, historical positive review rate, estimated delivery time, pricing amount, pricing details, and insurance plan. The pricing lists are sorted primarily by pricing amount (low to high) and secondarily by historical positive review rate (high to low) to generate an initial list. The real-time status of captains in the initial list is verified (e.g., whether they have accepted new orders, whether their location is outside the designated area), and invalid entries are removed to form the final logistics pricing list. The list is pushed to users via the client or SMS, with a set validity period (e.g., 15 minutes for urgent orders, 60 minutes for regular orders). Within the validity period, users can select a target captain, and the system simultaneously pushes an order acceptance notification to the corresponding captain.

[0072] It provides users with a transparent selection interface that allows for comparison and decision-making. Through structured templates, it integrates key information such as captain capabilities, pricing, and service quality, helping users quickly weigh the cost-effectiveness. The sorting mechanism prioritizes economical or high-quality service options, reducing the user's decision-making cost. Real-time verification and validity period settings ensure the accuracy and timeliness of the list information, preventing users from selecting invalid captains.

[0073] In the traditional model, users need to contact each captain individually to inquire about prices and verify information. The decision-making process is cumbersome and it is easy to miss high-quality resources. By integrating information, optimizing sorting, and clarifying timeliness, the scattered service options are transformed into an intuitive comparison list. Users can complete the selection in a short time, which not only improves decision-making efficiency but also ensures the rationality of the selection. Ultimately, it achieves a two-way optimization that saves users time and effort and ensures stable order acceptance for captains.

[0074] The method for recommending low-altitude logistics information in mountainous areas provided in this embodiment fundamentally solves the core pain points of traditional low-altitude logistics in mountainous areas, such as fragmented supply and demand matching, low efficiency, and high costs, achieving multi-dimensional optimization of transportation efficiency, operating costs, and service experience. Regarding improved transportation efficiency, by structurally analyzing logistics demands and converting them into quantitative rating scores, and combining this with multi-dimensional captain capability data to establish a precise matching mechanism, it replaces the traditional manual screening model, quickly locating suitable candidate captains and avoiding matching delays caused by information asymmetry. Simultaneously, it automatically generates pricing lists and structured pricing lists, compressing the communication cycle between supply and demand sides. Users can quickly select target captains without repeated price negotiations, significantly shortening the time from order initiation to confirmation, especially suitable for time-sensitive scenarios such as emergency material delivery in mountainous areas and fresh agricultural product transportation. Regarding operational cost control, the entire process requires no manual intervention. The system automatically completes captain qualification verification, order matching, and pricing calculation, greatly reducing manual input and avoiding additional costs such as mismatches and disputes caused by human operation. The dynamic adjustment mechanism for captain levels is linked to pricing coefficients, incentivizing captains to improve their skills and optimizing resource allocation. This avoids resource waste caused by high-level captains taking on low-difficulty orders, thus reducing overall operating costs. Regarding service experience optimization, the pricing breakdown details the various costs, integrating key information such as captain level, positive review rate, and estimated delivery time. This provides users with transparent and comparable selection criteria, avoiding the information opacity issues of traditional negotiation models. Simultaneously, the matching calculation incorporates dynamic data such as real-time captain location and order load, ensuring the suitability and timeliness of recommended captains, guaranteeing transportation safety and service quality, comprehensively improving the user experience for logistics demanders, and promoting the standardization, efficiency, and sustainability of low-altitude logistics in mountainous areas.

[0075] Corresponding to the aforementioned embodiment of a method for recommending low-altitude logistics information in mountainous areas, this application also provides an embodiment of a device for recommending low-altitude logistics information in mountainous areas.

[0076] An embodiment of the low-altitude logistics information recommendation device for mountainous areas disclosed in this application can be applied to low-altitude logistics information recommendation equipment for mountainous areas. The device embodiment can be implemented through software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of the low-altitude logistics information recommendation equipment in which it is located reading the corresponding computer program instructions from the non-volatile memory into memory and running them. From a hardware perspective, such as... Figure 2 The diagram shown is a hardware structure diagram of a low-altitude logistics information recommendation device for mountainous areas, as described in this application. (Except for...) Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the mountainous low-altitude logistics information recommendation device in the embodiment may also include other hardware depending on the actual function of the device, which will not be described in detail here.

[0077] Figure 3 This is a schematic diagram of the structure of Embodiment 2 of the mountainous low-altitude logistics information recommendation device provided in this application. Please refer to... Figure 3 The apparatus provided in this embodiment includes a determining module 310, a generating module 320, and a recommending module 330; wherein,

[0078] The determining module 310 is used to determine multiple candidate aircraft captains based on logistics requirements;

[0079] The generation module 320 is used to generate a pricing list for each candidate captain based on the plurality of candidate captains and the logistics requirements.

[0080] The recommendation module 330 is used to construct a logistics pricing list based on the pricing lists of each candidate captain, push the logistics pricing list to the user, and the user selects a target captain based on the logistics pricing list.

[0081] The apparatus of this embodiment can be used to perform... Figure 1 The steps of the method embodiment shown are similar in principle and process, and will not be repeated here.

[0082] Please continue to refer to Figure 2 This application also provides a low-altitude logistics information recommendation device for mountainous areas, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of any of the methods provided in the first aspect of this application.

[0083] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods provided in this application.

[0084] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0085] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0086] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for recommending low-altitude logistics information in mountainous areas, characterized in that, The method includes: Multiple candidate captains were determined based on logistics requirements; Generating pricing lists for each candidate captain based on the plurality of candidate captains and the logistics requirements; wherein, generating pricing lists for each candidate captain based on the plurality of candidate captains and the logistics requirements includes: Determine the rank of each candidate captain among the plurality of candidate captains, and determine the pricing coefficient for each candidate captain based on the rank; The flight price for each candidate captain is determined based on the aforementioned pricing coefficient; The logistics pricing is determined based on the aforementioned logistics requirements; The pricing for each candidate captain is determined based on the sum of their flight pricing and logistics pricing, and a pricing list is generated based on the pricing for each candidate captain. A logistics pricing list is constructed based on the pricing lists of each candidate captain, and the logistics pricing list is pushed to the user, who then selects a target captain based on the logistics pricing list.

2. The method according to claim 1, characterized in that, The process of determining multiple candidate captains based on logistics needs includes: Based on the logistics demand, logistics information is determined, which includes at least the type of goods, transportation distance, and urgency level. Calculate the level score of the logistics demand based on the logistics information; Multiple candidate captains are matched from the captain pool based on the rating score.

3. The method according to claim 1, characterized in that, Before identifying multiple candidate captains based on logistical needs; including: Obtain multi-dimensional information about the captain; Based on the aforementioned multi-dimensional information, the captains are quantitatively scored, and the captains are classified into different levels according to the scoring results. Different levels of captains correspond to different pricing coefficients.

4. The method according to claim 3, characterized in that, After classifying captains according to their ratings, the following levels are included: Determine the captain's periodic multi-dimensional information within the assessment period, and score the captain's period based on the periodic multi-dimensional information; The captain's rank is adjusted based on the periodic scoring results.

5. The method according to claim 2, characterized in that, The step of matching multiple candidate captains from the captain database based on the rating score includes: Establish a mapping rule between rating scores and captain ratings; The corresponding captain is matched based on the mapping rules and the rating.

6. A low-altitude logistics information recommendation device for mountainous areas, characterized in that, The device includes a determining module, a generating module, and a recommending module; wherein... The determining module is used to determine multiple candidate aircraft captains based on logistics requirements; The generation module is used to generate a pricing list for each candidate captain based on the plurality of candidate captains and the logistics requirements; wherein, generating a pricing list for each candidate captain based on the plurality of candidate captains and the logistics requirements includes: Determine the rank of each candidate captain among the plurality of candidate captains, and determine the pricing coefficient for each candidate captain based on the rank; The flight price for each candidate captain is determined based on the aforementioned pricing coefficient; The logistics pricing is determined based on the aforementioned logistics requirements; The pricing for each candidate captain is determined based on the sum of their flight pricing and logistics pricing, and a pricing list is generated based on the pricing for each candidate captain. The recommendation module is used to construct a logistics pricing list based on the pricing lists of each candidate captain, push the logistics pricing list to the user, and the user selects a target captain based on the logistics pricing list.

7. A low-altitude logistics information recommendation device for mountainous areas, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the steps of the method according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the steps of the method according to any one of claims 1-5.

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