Intelligent logistics sharing coordination information platform

Abstract

The invention belongs to the technical field of engineering construction logistics management, and particularly relates to an intelligent logistics sharing coordination information platform, which comprises a data layer used for getting through a multi-subject heterogeneous data barrier through a standardized interface, an Internet of Things terminal and an ETL tool, and forming a standardized data resource pool through data cleaning, format unification and field mapping; meanwhile, based on a distributed storage and block chain technology, data security storage, on-demand authorization sharing and full operation tracing are realized; and the coordination layer is used for realizing transparent and low-cost matching of conventional logistics demands through sealed bidding, multi-round optimization and credit scoring. According to the method, the multi-subject heterogeneous data and the block chain technology are integrated through the standardized API interface and the ETL tool to construct the secure shared account book, logistics data island breaking in the engineering construction field is realized, and each participant can controllably share data according to needs.

Description

Technical Field

[0001] This invention relates to the field of engineering construction logistics management technology, specifically to a smart logistics sharing and coordination information platform. Background Technology

[0002] Logistics in the engineering construction sector is characterized by a wide variety of materials (such as steel, cement, and sand), large transportation volumes, a broad range of stakeholders (construction companies, logistics providers, material suppliers, and regulatory authorities), and complex transportation routes. Its efficiency directly impacts the progress and cost of engineering construction. With the development of digital technology, engineering logistics is gradually transforming towards intelligentization, but the following key issues still exist:

[0003] 1. Severe Data Silo Problems: Logistics data from various stakeholders in engineering construction are scattered and stored in independent systems, lacking a unified sharing mechanism. For example, the construction company's material requirements data is stored in the Enterprise Resource Planning (ERP) system, the logistics provider's vehicle scheduling and transportation trajectory data is stored in the Transportation Management System (TMS), and the material supplier's inventory data is stored in the Supply Chain Management (SCM) system. The data formats of these systems are inconsistent, and their interfaces are not interoperable. In a highway construction project, the construction company's inability to obtain real-time vehicle location data from the logistics provider resulted in three batches of steel being delayed at the highway entrance, failing to reach the construction site on time, delaying the bridge pouring process, and causing direct economic losses exceeding 500,000 yuan.

[0004] 2. Lack of transparency and efficiency in logistics bidding mechanisms: Currently, the connection between engineering logistics needs is mostly based on offline negotiations or single bidding methods. This leads to problems such as an opaque bidding process and information asymmetry, making it prone to malicious price gouging or bribery. For example, when bidding for concrete transportation services for a subway construction project, three logistics companies colluded to agree on the lowest bid, resulting in a final winning bid price 22% higher than the reasonable market price, adding approximately 3 million yuan in additional logistics costs for the construction company. Furthermore, the offline bidding process requires manual processing of needs, screening of logistics companies, and price negotiations, with the entire process taking an average of 15 days, which cannot meet the urgent material transportation needs of engineering construction.

[0005] 3. Low efficiency and large errors in verifying the authenticity of waybills: In engineering logistics and transportation, paper weighbridge slips are the core documents for material weight calculation and cost settlement, currently relying mainly on manual entry and verification. On the one hand, manual entry is slow. In one building materials transportation project, the logistics company needed to submit more than 200 paper weighbridge slips per day, requiring 3 staff members to complete the manual entry in 8 hours. On the other hand, manual verification is easily affected by factors such as blurred weighbridge slips (e.g., soaked by rain, illegible handwriting) and human tampering, leading to data errors. In a hydropower station construction project, the weight on the paper weighbridge slips was altered by the logistics company (changing the actual transported 18 tons of sand and gravel to 20 tons). The anomaly was not detected during manual verification, resulting in the construction company overpaying freight charges by 12,000 yuan. The problem was only discovered during subsequent reconciliation, and re-verifying all weighbridge slips took 5 days, affecting the project settlement schedule.

[0006] 4. Poor visibility throughout the logistics process: Construction companies and regulatory authorities cannot track the transportation status of materials in real time, and can only obtain information through verbal feedback from logistics providers. When abnormal situations such as vehicle breakdowns or road congestion occur, it is impossible to adjust the scheduling plan in a timely manner. For example, in a bridge construction project, a batch of key steel components was delayed during transportation due to a tire blowout. The logistics provider did not inform the construction company in a timely manner, and the construction company failed to prepare spare components in advance, resulting in a two-day suspension of the steel structure installation process.

[0007] In summary, the existing engineering construction logistics management model can no longer meet the needs of efficient, transparent, and low-cost intelligent management. Therefore, an intelligent logistics sharing and coordination information platform is invented. Summary of the Invention

[0008] This invention provides the following technical solution:

[0009] A smart logistics sharing and coordination information platform, comprising:

[0010] The data layer is used to break down heterogeneous data barriers between multiple entities through standardized interfaces, IoT terminals, and ETL tools. After data cleaning, format unification, and field mapping, a standardized data resource pool is formed. At the same time, relying on distributed storage and blockchain technology, it realizes secure data storage, on-demand authorized sharing, and full traceability of operations.

[0011] The coordination layer is used to first achieve transparent and low-cost matching of routine logistics needs through sealed bidding, multiple rounds of optimization, and credit scoring; then, for sudden engineering needs, it relies on real-time capacity pools and AI scheduling algorithms to achieve hourly emergency capacity matching and cross-regional coordination.

[0012] The application layer is used to first automate the verification of weighbridge slips through OCR and large model technology, then to achieve real-time monitoring of vehicle trajectories through GIS and GPS, and finally to ensure the safety of materials in transit by relying on IoT sensing and AI analysis.

[0013] As a preferred embodiment of the intelligent logistics sharing and coordination information platform described in this invention, the data layer includes:

[0014] The data access module is used to connect with multiple entities to collect data by using standardized API interfaces, ETL tools and IoT data acquisition terminals;

[0015] The data standardization module is used to establish a standard library of engineering logistics data, and to perform format conversion, field mapping, and data cleaning on the collected heterogeneous data to form a standardized data resource pool.

[0016] The data storage and sharing module uses a distributed database to store standardized data and builds a data sharing ledger based on blockchain technology to record the data upload, query, and usage records of each entity, ensuring that the data is tamper-proof. At the same time, it sets data access permissions, allowing construction companies to view logistics companies' transportation data, logistics companies to view construction companies' material demand data, and regulatory authorities to view data throughout the entire process, achieving on-demand sharing and secure control.

[0017] As a preferred embodiment of the intelligent logistics sharing and coordination information platform described in this invention, the coordination layer includes:

[0018] The demand posting and review module allows construction companies to fill out logistics demand forms and upload relevant qualification documents through the platform. Based on the company's credit rating and historical cooperation records, the platform reviews the authenticity of the demand and publishes it to the bidding area after the review is approved.

[0019] The logistics provider access and bidding module allows logistics providers to submit their company qualifications, transportation capacity certificates, and historical service ratings. After approval, logistics providers can participate in bidding. The bidding adopts a sealed bidding and multi-round optimization mode. In the first round of bidding, logistics providers submit sealed bids. The platform calculates a comprehensive score based on the bid, service rating, and transportation capacity matching degree, and selects the top 5 to enter the second round of bidding. In the second round, logistics providers are allowed to adjust their bids based on the scores in the first round. Finally, the logistics provider with the highest comprehensive score is selected as the winning bidder.

[0020] The emergency dispatch optimization module allows construction companies to mark emergency demand levels and simplify the reporting process. It dynamically retrieves idle vehicles and standby capacity based on the real-time transportation capacity pool, and achieves the optimal dispatch scheme in terms of cost, timeliness, and matching degree through an improved genetic algorithm. It also supports cross-regional coordination and material substitution recommendations.

[0021] The bidding supervision and violation handling module is used to first identify collusive bidding behavior through big data analysis. Once a violation is discovered, the logistics provider's bidding qualification will be suspended immediately, and the violation record will be added to the company's credit file. At the same time, the entire bidding process data is stored on the blockchain in real time to ensure traceability.

[0022] As a preferred embodiment of the intelligent logistics shared coordination information platform described in this invention, the emergency dispatch optimization module includes:

[0023] The emergency demand rapid triggering and classification module is used to first enable construction companies to mark the urgency level when submitting emergency demands on the platform and simplify the demand filling; then the platform automatically verifies the rationality of the emergency demand and triggers the emergency dispatch process after the verification is passed.

[0024] The real-time capacity pool dynamic update module is used to first automatically search for idle capacity within the platform; then display key information of idle vehicles and sort them from closest to furthest from the loading point.

[0025] The AI-powered intelligent scheduling and matching module uses an improved genetic algorithm to calculate matching priorities based on the objectives of lowest transportation cost, shortest delivery time, and highest capacity matching. It then automatically generates a scheduling plan and pushes it to 3-5 qualified logistics providers. These providers must confirm acceptance within 30 minutes; failure to do so will automatically push the plan to the next provider. If idle capacity is insufficient, it automatically triggers cross-regional capacity coordination, connecting with logistics providers in surrounding cities or recommending material substitution solutions to construction companies.

[0026] As a preferred embodiment of the intelligent logistics sharing and coordination information platform described in this invention, the application layer includes:

[0027] The waybill authenticity verification module is used to collect standardized weighbridge images through the platform APP, and to automatically extract key information by relying on deep learning OCR technology. Then, combined with a large-scale model for engineering logistics, it conducts authenticity verification from three dimensions: semantic consistency, data rationality, and feature matching.

[0028] The logistics process visualization module is used to build a multi-dimensional real-time monitoring system based on vehicle GPS and GIS map technology. It supports the dynamic display of single / multi-vehicle transportation trajectory, driving speed, and remaining mileage, and can trigger intelligent early warnings through preset rules, push notifications simultaneously and provide solutions. At the same time, it integrates data statistical analysis functions, automatically generates management reports, and supports access from multiple terminals such as PC, APP, and mini-program, meeting the management and control needs of construction companies, logistics providers, and regulatory departments in different scenarios.

[0029] The material safety monitoring module is used to collect material environment data and loading images through vehicle-mounted IoT terminals and cameras. Relying on a material safety threshold library and a lightweight AI model, it identifies risks in real time, triggers multi-terminal warnings simultaneously, records the handling process, and finally generates a safety report associated with the electronic waybill.

[0030] As a preferred embodiment of the intelligent logistics shared coordination information platform described in this invention, the waybill authenticity verification module includes:

[0031] The image acquisition module enables logistics providers to take photos of paper weighbridge slips through the platform's app and upload them to the platform. The platform then automatically detects the image clarity and prompts the user to retake the photo if the clarity is insufficient.

[0032] The OCR recognition module is used to identify key information on the weight slip using a deep learning OCR model.

[0033] The large model verification module is used to introduce a large model specifically for engineering logistics and verify its authenticity from three dimensions: semantic consistency verification, data rationality verification, and feature matching verification.

[0034] The result feedback module is used to automatically enter the weighbridge data into the system and generate an electronic waybill when the verification passes; if the verification fails, an alert is issued and suspicious items are marked, requiring manual review, and the review results are included in the logistics provider's credit score.

[0035] As a preferred embodiment of the intelligent logistics shared coordination information platform described in this invention, the semantic consistency verification is to compare whether the material name identified by OCR is consistent with the material type in the winning bid waybill.

[0036] The data rationality verification is based on historical data to determine whether the weight is within a reasonable range;

[0037] The feature matching verification compares whether the signature and stamp area of ​​the weighbridge slip is consistent with the signature and stamp template reserved by the logistics provider to identify traces of tampering.

[0038] As a preferred embodiment of the intelligent logistics shared coordination information platform described in this invention, the logistics full-process visualization module includes:

[0039] The real-time trajectory monitoring module is used to display the location, speed and remaining mileage of the transport vehicle in real time on the platform interface based on the vehicle's GPS and GIS map. It supports viewing the trajectory of a single vehicle and monitoring multiple vehicles in batches.

[0040] The anomaly warning module is used to set warning rules. Once a rule is triggered, it automatically sends SMS / APP notifications to construction companies and logistics providers, and recommends solutions.

[0041] The data statistics and analysis module is used to automatically generate logistics management reports, and supports filtering and querying by project, time period, and material type, providing data support for construction companies to control costs and logistics providers to optimize services.

[0042] The multi-terminal access module supports access from PC, mobile APP, and WeChat mini-program, meeting the usage needs of construction company managers, logistics drivers, and supervisors in different scenarios.

[0043] As a preferred embodiment of the intelligent logistics shared coordination information platform described in this invention, the material safety monitoring module includes:

[0044] The multi-dimensional perception data acquisition module is used to first connect to the vehicle-mounted IoT terminal to collect material transportation environment data in real time; then, it uses the vehicle camera to collect loading status images, automatically capturing one image every 30 minutes, or triggering a capture when the vibration exceeds the threshold, to identify whether there is a problem with the material.

[0045] The intelligent safety risk assessment module is used to first establish a material safety threshold library; then, a lightweight AI model is used to analyze sensor data and images in real time.

[0046] The risk response and traceability module is used to first push notifications to the logistics company's driver and the construction company's material manager when a risk warning is triggered, along with the risk location and real-time data screenshots; then it automatically records the time, location, and handling process of the risk, generates a material safety monitoring report, and links it to the electronic waybill as the basis for determining liability for cargo damage.

[0047] Compared with existing technologies:

[0048] 1. By integrating heterogeneous data from multiple entities through standardized API interfaces and ETL tools, and constructing a secure shared ledger using blockchain technology, it can break down data silos in the engineering construction field and enable all participating entities to share data on demand and in a controllable manner.

[0049] 2. Through sealed bidding, multiple rounds of optimization and credit scoring, the entire process of logistics provider credit access review and bidding is monitored and stored on the blockchain, which can realize the openness and transparency of the engineering logistics bidding process, avoid malicious price increases and transfer of benefits, and improve the efficiency of demand matching.

[0050] 3. By using deep learning OCR technology, key information on paper weighbridge slips can be automatically identified. The large-scale model for engineering logistics verifies the authenticity of waybills from multiple dimensions, including semantics, data rationality, and feature matching. This enables the automation of waybill authenticity verification and reduces the intensity of manual data entry and verification errors.

[0051] 4. By collecting transportation trajectories in real time through vehicle-mounted GPS, displaying vehicle dynamics on GIS maps, and triggering abnormal warnings according to preset rules, it has the advantages of enabling real-time tracking of the entire process of engineering logistics transportation and timely detection and response to transportation abnormalities. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the overall framework of the present invention;

[0053] Figure 2 This is a schematic diagram of the data layer framework of the present invention;

[0054] Figure 3 This is a schematic diagram of the coordination layer framework of the present invention;

[0055] Figure 4 This is a schematic diagram of the application layer framework of the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0057] This invention provides a smart logistics sharing and coordination information platform. Please refer to [link / reference]. Figures 1-4 ,include:

[0058] The data layer is used to break down heterogeneous data barriers between multiple entities through standardized interfaces, IoT terminals, and ETL tools. After data cleaning, format unification, and field mapping, a standardized data resource pool is formed. At the same time, relying on distributed storage and blockchain technology, it realizes secure data storage, on-demand authorized sharing, and full traceability of operations.

[0059] The coordination layer is used to first achieve transparent and low-cost matching of routine logistics needs through sealed bidding, multiple rounds of optimization, and credit scoring; then, for sudden engineering needs, it relies on real-time capacity pools and AI scheduling algorithms to achieve hourly emergency capacity matching and cross-regional coordination.

[0060] The application layer is used to first automate the verification of weighbridge slips through OCR and large model technology, then to achieve real-time monitoring of vehicle trajectories through GIS and GPS, and finally to ensure the safety of materials in transit by relying on IoT sensing and AI analysis.

[0061] The data layer includes:

[0062] The data access module is used to connect with multiple entities, such as construction company ERP systems, logistics provider TMS systems, material supplier SCM systems, highway ETC systems, and vehicle GPS terminals, using standardized API interfaces, ETL tools (Extract-Transform-Load), and IoT data acquisition terminals, to collect data such as material requirements (type, quantity, time, location), vehicle information (license plate number, load, vehicle condition), transportation trajectory (real-time location, driving speed), inventory data (material inventory, outbound time), and weighbridge images.

[0063] The data standardization module is used to establish a standard library of engineering logistics data. It performs format conversion (such as unifying transportation trajectory data from different TMS systems into JSON format), field mapping (such as unifying "material code" and "material number" into "unique material identifier"), and data cleaning (removing duplicate data and correcting abnormal data, such as abnormal trajectory data where the vehicle speed exceeds 120km / h) on the collected heterogeneous data to form a standardized data resource pool.

[0064] The data storage and sharing module is used to store standardized data using a distributed database (such as HBase) and to build a data sharing ledger based on blockchain technology to record the data upload, query, and usage records of each entity, ensuring that the data is tamper-proof. At the same time, data access permissions are set, allowing construction companies to view logistics companies' transportation data, logistics companies to view construction companies' material demand data, and regulatory authorities to view data throughout the entire process, achieving on-demand sharing and secure control.

[0065] The coordination layer includes:

[0066] The demand posting and review module allows construction companies to fill out logistics demand forms (including material type, transportation volume, origin and destination, time requirements, and quality requirements) through the platform, upload relevant qualification documents (such as construction permits), and verify the authenticity of the demand based on the company's credit rating (connected to the National Enterprise Credit Information Publicity System) and historical cooperation records. Once approved, the demand is posted to the bidding area.

[0067] The logistics provider access and bidding module allows logistics providers to submit their business qualifications (such as road transport operation license), capacity proof (number of vehicles, load capacity), and historical service ratings (based on past on-time delivery rate, cargo damage rate, and customer reviews). After approval, logistics providers can participate in bidding. The bidding adopts a sealed bidding and multi-round optimization mode. In the first round of bidding, logistics providers submit sealed bids (without hidden bid information). The platform calculates a comprehensive score based on the bid, service rating, and capacity matching degree (such as the matching degree between vehicle load capacity and transport volume, and the distance between vehicle location and loading point). The top 5 are selected to enter the second round of bidding. In the second round, logistics providers are allowed to adjust their bids based on the scores from the first round. Finally, the logistics provider with the highest comprehensive score is selected as the winning bidder.

[0068] The emergency dispatch optimization module allows construction companies to mark emergency demand levels and simplify the reporting process. It dynamically retrieves idle vehicles and standby capacity based on the real-time transportation capacity pool, and achieves the optimal dispatch scheme in terms of cost, timeliness, and matching degree through an improved genetic algorithm. It also supports cross-regional coordination and material substitution recommendations.

[0069] The bidding supervision and violation handling module is used to first identify collusive bidding behavior through big data analysis (such as multiple accounts with the same IP address or a bid difference rate of less than 5%). Once a violation is found, the logistics provider's bidding qualification will be suspended immediately, and the violation record will be added to the company's credit file. At the same time, all data of the bidding process (demand, bid, score, and result) will be stored on the blockchain in real time to ensure traceability.

[0070] The emergency dispatch optimization module includes:

[0071] The emergency demand rapid triggering and classification module enables construction companies to mark the urgency level when submitting emergency demands on the platform (Level 1: delivery within 24 hours, such as sand and gravel for disaster relief; Level 2: delivery within 48 hours, such as temporarily supplemented steel), and simplifies the demand entry (automatically links to historical project material information, eliminating the need for repetitive entry); then the platform automatically verifies the rationality of the emergency demand (e.g., combining with the construction schedule to determine whether it is a genuine emergency demand, avoiding malicious occupation of emergency transportation capacity), and triggers the emergency dispatch process after the verification is passed;

[0072] The real-time capacity pool dynamic update module is used to automatically search for idle capacity within the platform, including vehicles that have completed transportation tasks, vehicles waiting for orders (based on GPS positioning to determine if the vehicle is idle), and "emergency backup capacity" signed with the platform (such as 3 fixed logistics providers in the region, promising to respond within 1 hour); then it displays key information of idle vehicles (current location, load, types of materials that can be transported, driver contact information, historical emergency service rating), and sorts them from closest to furthest from the loading point;

[0073] The AI-powered intelligent scheduling and matching module employs an improved genetic algorithm to calculate matching priorities based on the objectives of lowest transportation cost, shortest delivery time, and highest capacity matching. For example, first-level emergency needs prioritize matching with idle vehicles within a 30-kilometer radius, while second-level needs can be extended to 50 kilometers. The module then automatically generates a scheduling plan (including loading time, optimal route, and estimated delivery time) and pushes it to 3-5 qualified logistics providers. These providers must confirm acceptance within 30 minutes; failure to do so will automatically push the order to the next provider. If idle capacity is insufficient, the module automatically triggers cross-regional capacity coordination, connecting with logistics providers in surrounding cities or recommending material alternatives to construction companies (e.g., prioritizing nearby suppliers with similar materials).

[0074] In particular, after an emergency dispatch is completed, the service record will be automatically included in the logistics provider's credit score, affecting its ranking in subsequent regular bidding.

[0075] The application layer includes:

[0076] The waybill authenticity verification module is used to collect standardized weighbridge images through the platform APP, and to automatically extract key information by relying on deep learning OCR technology. Then, combined with a large-scale model for engineering logistics, it conducts authenticity verification from three dimensions: semantic consistency, data rationality, and feature matching.

[0077] The logistics process visualization module is used to build a multi-dimensional real-time monitoring system based on vehicle GPS and GIS map technology. It supports the dynamic display of single / multi-vehicle transportation trajectory, driving speed, and remaining mileage, and can trigger intelligent early warnings through preset rules, push notifications simultaneously and provide solutions. At the same time, it integrates data statistical analysis functions, automatically generates management reports, and supports access from multiple terminals such as PC, APP, and mini-program, meeting the management and control needs of construction companies, logistics providers, and regulatory departments in different scenarios.

[0078] The material safety monitoring module is used to collect material environment data and loading images through vehicle-mounted IoT terminals and cameras. Relying on a material safety threshold library and a lightweight AI model, it identifies risks in real time, triggers multi-terminal warnings simultaneously, records the handling process, and finally generates a safety report associated with the electronic waybill.

[0079] The waybill authenticity verification module includes:

[0080] The image acquisition module enables logistics providers to take photos of paper weighbridge slips through the platform's app and upload them to the platform. The platform then automatically detects the image clarity (such as resolution and brightness), and prompts the user to retake the photo if the clarity is insufficient.

[0081] The OCR recognition module is used to identify key information on the weighbridge slip using a deep learning OCR model (such as ResNet-based text detection + CRNN-based text recognition), including material name, weight, transportation time, license plate number, weighbridge slip number, signature and stamp information.

[0082] The large model verification module is used to introduce a large model specifically for engineering logistics (based on the Transformer architecture, with training data including 100,000+ images of engineering logistics weighbridge slips and 500,000+ historical waybill data), and verify its authenticity from three dimensions: semantic consistency verification, data rationality verification, and feature matching verification.

[0083] The semantic consistency check compares whether the material name identified by OCR is consistent with the material type in the winning bid waybill (e.g., if the waybill requires the transport of "rebar", but the identification result is "round steel", an alert will be issued).

[0084] The data rationality verification is based on historical data to determine whether the weight is within a reasonable range (e.g., the historical weight range of a certain type of truck transporting sand and gravel is 15-20 tons, and if the identification result is 25 tons, an alert will be issued).

[0085] The feature matching verification compares whether the signature and stamp area of ​​the weighbridge is consistent with the signature and stamp template reserved by the logistics provider, and identifies traces of tampering (such as PS modification of weight figures).

[0086] The results feedback module is used to automatically enter the weighbridge data into the system and generate an electronic waybill when the verification passes; if the verification fails, an alert is issued and suspicious items are marked (such as "weight exceeds reasonable range" or "signature does not match"), and manual review is required. The review results are included in the logistics provider's credit score.

[0087] The logistics process visualization module includes:

[0088] The real-time trajectory monitoring module is used to display the location, speed and remaining mileage of the transport vehicle in real time on the platform interface based on the vehicle's GPS and GIS map. It supports viewing the trajectory of a single vehicle and monitoring multiple vehicles in batches.

[0089] The anomaly warning module is used to set warning rules (such as vehicle deviating from the planned route, abnormal driving speed, failure to arrive on time). Once a rule is triggered, it automatically sends SMS / APP notifications to construction companies and logistics providers, and recommends solutions (such as recommending the optimal return route when deviating from the route).

[0090] The data statistics and analysis module is used to automatically generate logistics management reports, including transportation efficiency (on-time rate, average transportation time), cost statistics (freight cost per ton, total freight cost), cargo damage rate, etc. It supports filtering and querying by project, time period, and material type, providing data support for construction companies to control costs and logistics providers to optimize services.

[0091] The multi-terminal access module supports access from PC, mobile APP, and WeChat mini-program, meeting the usage needs of construction company managers, logistics drivers, and supervisors in different scenarios.

[0092] The material safety monitoring module includes:

[0093] The multi-dimensional sensing data acquisition module is used to first connect to the vehicle-mounted IoT terminal (such as temperature and humidity sensors, three-axis vibration sensors, and infrared ranging sensors) to collect real-time material transportation environment data (cement transportation requires monitoring humidity ≤60% and temperature 5-30℃; steel transportation requires monitoring vibration acceleration ≤0.5g to avoid collision deformation); then, it collects loading status images through vehicle cameras (front-facing + side-loading of cargo box), automatically taking a picture once every 30 minutes, or triggering a picture when the vibration exceeds the threshold, to identify whether there are problems such as material spillage, displacement, or damage to the covering.

[0094] The intelligent safety risk assessment module first establishes a material safety threshold database (based on industry standards and historical cargo damage cases, such as judging a risk if the spillage area of ​​sand and gravel transportation is ≥0.5㎡, and judging a high risk if the vibration of precast components lasts for more than 10 minutes); then, it uses a lightweight AI model (such as an image recognition model based on MobileNet) to analyze sensor data and images in real time; if the humidity exceeds the standard, it automatically judges "cement moisture risk"; if the image recognition shows that the cargo box cover cloth is damaged and sand and gravel are spilled, it automatically judges "material loss risk";

[0095] The risk response and traceability module is used to first push notifications to the logistics company's driver (APP pop-up + voice reminder, such as "Humidity exceeds the standard, please check the sealing of the rainproof cloth") and the construction company's material manager (SMS + platform message) when a risk warning is triggered, along with the risk location and real-time data screenshots; then it automatically records the time, location, and handling process of the risk (such as the driver uploading images after rectification), generates a material safety monitoring report, and links it to the electronic waybill as the basis for determining liability for cargo damage (e.g., if the cement gets damp due to the driver's failure to rectify in time, the logistics company's credit score will be automatically deducted).

[0096] In practical use, the specific steps are as follows:

[0097] S1: By using standardized interfaces, IoT terminals, and ETL tools, the heterogeneous data barriers between multiple entities are broken down, and a standardized data resource pool is formed through data cleaning, format unification, and field mapping; at the same time, relying on distributed storage and blockchain technology, secure data storage, on-demand authorized sharing, and full traceability of operations are achieved.

[0098] S2: First, through sealed bidding, multiple rounds of optimization, and credit scoring, transparent and low-cost matching of routine logistics needs is achieved; then, for sudden engineering needs, relying on real-time capacity pools and AI scheduling algorithms, hourly emergency capacity matching and cross-regional coordination are achieved.

[0099] S3: First, automated verification of weighbridge slips is achieved through OCR + large model technology. Then, real-time monitoring of vehicle trajectories is achieved through GIS + GPS. Finally, the safety of materials in transit is ensured by relying on IoT sensing and AI analysis.

[0100] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A smart logistics sharing and coordination information platform, characterized in that, include: The data layer is used to break down heterogeneous data barriers between multiple entities through standardized interfaces, IoT terminals, and ETL tools. After data cleaning, format unification, and field mapping, a standardized data resource pool is formed. At the same time, relying on distributed storage and blockchain technology, it realizes secure data storage, on-demand authorized sharing, and full traceability of operations. The coordination layer is used to first achieve transparent and low-cost matching of routine logistics needs through sealed bidding, multiple rounds of optimization, and credit scoring; then, for sudden engineering needs, it relies on real-time capacity pools and AI scheduling algorithms to achieve hourly emergency capacity matching and cross-regional coordination. The application layer is used to first automate the verification of weighbridge slips through OCR and large model technology, then to achieve real-time monitoring of vehicle trajectories through GIS and GPS, and finally to ensure the safety of materials in transit by relying on IoT sensing and AI analysis.

2. The intelligent logistics sharing and coordination information platform according to claim 1, characterized in that, The data layer includes: The data access module is used to connect with multiple entities to collect data by using standardized API interfaces, ETL tools and IoT data acquisition terminals; The data standardization module is used to establish a standard library of engineering logistics data, and to perform format conversion, field mapping, and data cleaning on the collected heterogeneous data to form a standardized data resource pool. The data storage and sharing module uses a distributed database to store standardized data and builds a data sharing ledger based on blockchain technology to record the data upload, query, and usage records of each entity, ensuring that the data is tamper-proof. At the same time, it sets data access permissions, allowing construction companies to view logistics companies' transportation data, logistics companies to view construction companies' material demand data, and regulatory authorities to view data throughout the entire process, achieving on-demand sharing and secure control.

3. The intelligent logistics sharing and coordination information platform according to claim 1, characterized in that, The coordination layer includes: The demand posting and review module allows construction companies to fill out logistics demand forms and upload relevant qualification documents through the platform. Based on the company's credit rating and historical cooperation records, the platform reviews the authenticity of the demand and publishes it to the bidding area after the review is approved. The logistics provider access and bidding module allows logistics providers to submit their company qualifications, transportation capacity certificates, and historical service ratings. After approval, logistics providers can participate in bidding. The bidding adopts a sealed bidding and multi-round optimization mode. In the first round of bidding, logistics providers submit sealed bids. The platform calculates a comprehensive score based on the bid, service rating, and transportation capacity matching degree, and selects the top 5 to enter the second round of bidding. In the second round, logistics providers are allowed to adjust their bids based on the scores in the first round. Finally, the logistics provider with the highest comprehensive score is selected as the winning bidder. The emergency dispatch optimization module allows construction companies to mark emergency demand levels and simplify the reporting process. It dynamically retrieves idle vehicles and standby capacity based on the real-time transportation capacity pool, and achieves the optimal dispatch scheme in terms of cost, timeliness, and matching degree through an improved genetic algorithm. It also supports cross-regional coordination and material substitution recommendations. The bidding supervision and violation handling module is used to first identify collusive bidding behavior through big data analysis. Once a violation is discovered, the logistics provider's bidding qualification will be suspended immediately, and the violation record will be added to the company's credit file. At the same time, the entire bidding process data is stored on the blockchain in real time to ensure traceability.

4. The intelligent logistics sharing and coordination information platform according to claim 3, characterized in that, The emergency dispatch optimization module includes: The emergency demand rapid triggering and classification module is used to first enable construction companies to mark the urgency level when submitting emergency demands on the platform and simplify the demand filling; then the platform automatically verifies the rationality of the emergency demand and triggers the emergency dispatch process after the verification is passed. The real-time capacity pool dynamic update module is used to first automatically search for idle capacity within the platform; then display key information of idle vehicles and sort them from closest to furthest from the loading point. The AI-powered intelligent scheduling and matching module uses an improved genetic algorithm to calculate matching priorities based on the objectives of lowest transportation cost, shortest delivery time, and highest capacity matching. It then automatically generates a scheduling plan and pushes it to 3-5 qualified logistics providers. These providers must confirm acceptance within 30 minutes; failure to do so will automatically push the plan to the next provider. If idle capacity is insufficient, it automatically triggers cross-regional capacity coordination, connecting with logistics providers in surrounding cities or recommending material substitution solutions to construction companies.

5. The intelligent logistics sharing and coordination information platform according to claim 1, characterized in that, The application layer includes: The waybill authenticity verification module is used to collect standardized weighbridge images through the platform APP, and to automatically extract key information by relying on deep learning OCR technology. Then, combined with a large-scale model for engineering logistics, it conducts authenticity verification from three dimensions: semantic consistency, data rationality, and feature matching. The logistics process visualization module is used to build a multi-dimensional real-time monitoring system based on vehicle GPS and GIS map technology. It supports the dynamic display of single / multi-vehicle transportation trajectory, driving speed, and remaining mileage, and can trigger intelligent early warnings through preset rules, push notifications simultaneously and provide solutions. At the same time, it integrates data statistical analysis functions, automatically generates management reports, and supports access from multiple terminals such as PC, APP, and mini-program, meeting the management and control needs of construction companies, logistics providers, and regulatory departments in different scenarios. The material safety monitoring module is used to collect material environment data and loading images through vehicle-mounted IoT terminals and cameras. Relying on a material safety threshold library and a lightweight AI model, it identifies risks in real time, triggers multi-terminal warnings simultaneously, records the handling process, and finally generates a safety report associated with the electronic waybill.

6. The intelligent logistics sharing and coordination information platform according to claim 5, characterized in that, The waybill authenticity verification module includes: The image acquisition module enables logistics providers to take photos of paper weighbridge slips through the platform's app and upload them to the platform. The platform then automatically detects the image clarity and prompts the user to retake the photo if the clarity is insufficient. The OCR recognition module is used to identify key information on the weight slip using a deep learning OCR model. The large model verification module is used to introduce a large model specifically for engineering logistics and verify its authenticity from three dimensions: semantic consistency verification, data rationality verification, and feature matching verification. The result feedback module is used to automatically enter the weighbridge data into the system and generate an electronic waybill when the verification passes; if the verification fails, an alert is issued and suspicious items are marked, requiring manual review, and the review results are included in the logistics provider's credit score.

7. A smart logistics sharing and coordination information platform according to claim 6, characterized in that, The semantic consistency verification is to compare whether the material name recognized by OCR is consistent with the material type in the winning bid waybill; The data rationality verification is based on historical data to determine whether the weight is within a reasonable range; The feature matching verification compares whether the signature and stamp area of ​​the weighbridge slip is consistent with the signature and stamp template reserved by the logistics provider to identify traces of tampering.

8. The intelligent logistics sharing and coordination information platform according to claim 5, characterized in that, The logistics process visualization module includes: The real-time trajectory monitoring module is used to display the location, speed and remaining mileage of the transport vehicle in real time on the platform interface based on the vehicle's GPS and GIS map. It supports viewing the trajectory of a single vehicle and monitoring multiple vehicles in batches. The anomaly warning module is used to set warning rules. Once a rule is triggered, it automatically sends SMS / APP notifications to construction companies and logistics providers, and recommends solutions. The data statistics and analysis module is used to automatically generate logistics management reports, and supports filtering and querying by project, time period, and material type, providing data support for construction companies to control costs and logistics providers to optimize services. The multi-terminal access module supports access from PC, mobile APP, and WeChat mini-program, meeting the usage needs of construction company managers, logistics drivers, and supervisors in different scenarios.

9. A smart logistics sharing and coordination information platform according to claim 5, characterized in that, The material safety monitoring module includes: The multi-dimensional perception data acquisition module is used to first connect to the vehicle-mounted IoT terminal to collect material transportation environment data in real time; then, it uses the vehicle camera to collect loading status images, automatically capturing one image every 30 minutes, or triggering a capture when the vibration exceeds the threshold, to identify whether there is a problem with the material. The intelligent safety risk assessment module is used to first establish a material safety threshold library; then, a lightweight AI model is used to analyze sensor data and images in real time. The risk response and traceability module is used to first push notifications to the logistics company's driver and the construction company's material manager when a risk warning is triggered, along with the risk location and real-time data screenshots; then it automatically records the time, location, and handling process of the risk, generates a material safety monitoring report, and links it to the electronic waybill as the basis for determining liability for cargo damage.

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