Logistics information management device and system based on internet of things

Abstract

The present application relates to the field of supply chain management, and discloses a logistics information management device and system based on the Internet of Things. The device comprises a support frame; a conveyor belt is fixedly connected to the upper surface of the support frame; a detection compartment is fixedly connected to the upper surface of the support frame; the conveyor belt is arranged inside the detection compartment; a scanner is fixedly connected to the lower surface of the detection compartment; the scanner is arranged above the conveyor belt; a console is fixedly connected to an outer wall of the detection compartment; and a data port is fixedly connected to the lower surface of the console. The system comprises an Internet interface module. Because the device can support multiple Internet of Things communication protocols, the device can integrate data from multiple sources; by receiving data from various sensors in real time, a data processing module can process the data in real time, thereby better planning and optimizing logistics paths and processes; and big data technology can be used for processing large amounts of data collected from sensors and devices.

Description

A logistics information management device and system based on the Internet of Things Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a logistics information management device and system based on the Internet of Things. Background Art

[0002] IoT-based logistics information management equipment and systems are solutions built using IoT technology, designed to improve the visibility, efficiency, and safety of logistics and transportation processes. This system combines key IoT components such as sensors, communication devices, and data processing and analysis platforms to monitor, control, and manage various elements of the logistics and transportation process, such as goods, vehicles, equipment, and information. Traditional IoT logistics information management equipment may utilize different hardware devices, sensors, communication technologies, and data formats across different logistics supply chain links. This leads to challenges in interoperability and data integration between devices. The lack of unified standards and specifications complicates seamless connectivity and data exchange between devices and systems.

[0003] Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a logistics information management device and system based on the Internet of Things, which solves the problem that the lack of unified standards and specifications makes seamless connection and data exchange between devices and systems more complicated.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a logistics information management device based on the Internet of Things, including a bracket, the upper surface of the bracket is fixedly connected to a conveyor belt, the upper surface of the bracket is fixedly connected to a detection bin, the conveyor belt is arranged inside the detection bin, the lower surface of the detection bin is fixedly connected to a scanner, the scanner is arranged above the conveyor belt, the outer wall of the detection bin is fixedly connected to a console, and the lower surface of the console is fixedly connected to a data port.

[0006] A logistics information management system based on the Internet of Things, comprising:

[0007] Internet interface module: The Internet interface module enables logistics equipment to connect with remote servers or cloud platforms, allowing remote monitoring and control;

[0008] Cargo Identification Module: Identify, track and manage different types of cargo;

[0009] Data processing module: Data collection, the data processing module will perform data cleaning operations to identify and correct errors, duplicates or incomplete information in the data;

[0010] Storage module: stores raw IoT data for subsequent query;

[0011] Multi-data storage module: Data from different sources are integrated into a unified storage module to achieve unified data management and analysis;

[0012] Logistics Optimization Module: Autonomous vehicles, robotics, and automated warehouse technologies can be used to accelerate logistics processes;

[0013] Security module: Implements tamper-proof audit logs to ensure data security and transparency:

[0014] Visualization module: Provides an interactive map so that logistics managers can track the location of multiple shipments in real time and plan the best routes.

[0015] Working Principle: The device is equipped with internal temperature sensors to monitor cargo temperature, which is crucial for cold chain logistics. They ensure that temperature-sensitive goods such as frozen foods, pharmaceuticals, and chemicals maintain the appropriate temperature throughout transportation. A humidity sensor monitors the humidity level of the cargo. This is crucial for logistics requiring a dry environment, such as the transportation of electronic devices, paper, and textiles. It also includes a GPS device for real-time tracking of cargo locations. This helps logistics managers understand the current location of cargo and its estimated arrival time, enabling better planning and coordination of logistics processes. RFID tags and readers: RFID technology allows logistics managers to track cargo and monitor its status. Each item can be attached with an RFID tag and then scanned with a reader to record its location and status. Accelerometers can detect vibration, tilt, and impact during transportation. This is crucial for protecting fragile goods and preventing damage. Logistics equipment is typically connected to a central system via wireless communication methods such as cellular networks, Wi-Fi, and LoRaWAN. This ensures that the equipment can transmit data in real time, regardless of the cargo's location. The data is typically uploaded to a cloud platform, making it accessible and shareable globally. Cloud platforms also provide data storage, analysis, and backup capabilities. Big data technologies are used to process the vast amounts of data collected from sensors and devices. This includes data cleansing, aggregation, and storage for subsequent analysis. Data mining techniques can be used to identify potential logistics issues and trends. Historical data can be analyzed to predict demand fluctuations for better inventory management. Machine learning and predictive analytics can be used to forecast cargo arrival times, traffic conditions, and other relevant factors. This facilitates better planning of logistics routes and delivery times. Logistics management systems provide visual dashboards and reports of real-time and historical data to help administrators monitor logistics processes. These dashboards can be customized to display key performance indicators. Alerts and notifications can be set to notify administrators of important changes or issues with cargo status. This facilitates timely action to prevent potential problems. The system can calculate optimal cargo transportation routes to reduce transportation time and costs. This typically takes into account factors such as traffic, road conditions, and cargo type to help manage inventory levels and avoid overstocking or understocking. The system can adjust inventory levels based on demand forecasts. Data should be encrypted during transmission to ensure confidentiality and integrity. Only authorized personnel can access the logistics management system to perform specific tasks. This helps ensure the security of data and operations, and the integrated application of this system helps improve logistics efficiency, reduce costs, mitigate risks, and provide greater visibility and control.

[0016] The present invention provides a logistics information management device and system based on the Internet of Things. It has the following beneficial effects:

[0017] 1. The present invention, by enabling the device to support multiple IoT communication protocols, can integrate data from a variety of sources, increasing the system's flexibility and applicability. By receiving data from various sensors in real time, the system can provide immediate cargo monitoring, enabling faster and more efficient decision-making. The data processing module can not only process data in real time but also predict the future status or location of cargo, which helps to better plan and optimize logistics routes and processes. Big data technology is used to process large amounts of data collected from sensors and devices. This includes data cleaning, aggregation, and storage for subsequent analysis. Data mining techniques can be used to identify potential logistics issues and trends. Predictive analysis can be used to predict cargo arrival times, traffic conditions, and other related factors, which helps to better plan logistics routes and delivery times. Through the coordination between the above modules, transparent real-time tracking of logistics can be achieved, as well as predictions about logistics. The overall increase in multiple data types makes the present invention flexible.

[0018] 2. The present invention can store large amounts of data through the storage module and supports multiple data storage formats, which enables data to be efficiently queried and analyzed according to different needs. The system can automatically generate alarms based on preset standards, thereby notifying users immediately when problems occur, which can help reduce losses and delays. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a main frame diagram of the present invention;

[0020] FIG2 is a flow chart of a cargo identification module according to the present invention;

[0021] FIG3 is a flow chart of a data processing module of the present invention;

[0022] FIG4 is a flow chart of a storage module according to the present invention;

[0023] FIG5 is a flow chart of a multi-data storage module according to the present invention;

[0024] FIG6 is a flow chart of a visualization module of the present invention;

[0025] FIG7 is a flow chart of the logistics optimization module of the present invention;

[0026] FIG8 is a flow chart of the security module of the present invention;

[0027] FIG9 is a perspective view of the present invention.

[0028] Among them, 1. Inspection chamber; 2. Control console; 3. Conveyor belt; 4. Scanner; 5. Data port. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] Example:

[0031] Please refer to Figures 1 to 9. An embodiment of the present invention provides a logistics information management device based on the Internet of Things, including a bracket, the upper surface of the bracket is fixedly connected to a conveyor belt 3, the upper surface of the bracket is fixedly connected to a detection chamber 1, the conveyor belt 3 is arranged inside the detection chamber 1, the lower surface of the detection chamber 1 is fixedly connected to a scanner 4, the scanner 4 is arranged above the conveyor belt 3, the outer wall of the detection chamber 1 is fixedly connected to a console 2, and the lower surface of the console 2 is fixedly connected to a data port 5.

[0032] A logistics information management system based on the Internet of Things, comprising:

[0033] Internet interface module: The Internet interface module enables logistics equipment to connect with remote servers or cloud platforms, allowing remote monitoring and control;

[0034] Cargo Identification Module: Identify, track and manage different types of cargo;

[0035] Data processing module: Data collection, the data processing module will perform data cleaning operations to identify and correct errors, duplicates or incomplete information in the data;

[0036] Storage module: stores raw IoT data for subsequent query;

[0037] Multi-data storage module: Data from different sources are integrated into a unified storage module to achieve unified data management and analysis;

[0038] Logistics Optimization Module: Autonomous vehicles, robotics, and automated warehouse technologies can be used to accelerate logistics processes;

[0039] Security module: Implements tamper-proof audit logs to ensure data security and transparency:

[0040] Visualization module: Provides an interactive map so that logistics managers can track the location of multiple shipments in real time and plan the best routes.

[0041] The cargo identification module includes an RFID tag unit, a QR code unit, and a card reader unit. The cargo identification module is connected to the RFID tag unit, the RFID tag unit is connected to the QR code unit, and the QR code unit is connected to the card reader unit:

[0042] The RFID tag unit is used to read the RFID tag attached to the goods to achieve wireless identification and tracking.

[0043] Data is cleaned, aggregated, and stored for subsequent analysis. Data mining techniques can be used to identify potential logistics problems and trends, and predictive analysis can be used to predict cargo arrival times, traffic conditions, and other relevant factors, which helps to better plan logistics routes and delivery times.

[0044] The data processing module includes a data real-time processing unit, a data analysis unit, a standard threshold setting unit and an early warning unit, the data processing module is connected to the data real-time processing unit, the real-time processing unit is connected to the data analysis unit, the real-time data analysis unit is connected to the standard threshold setting unit, and the standard threshold setting unit is connected to the early warning unit;

[0045] The early warning unit is used to automatically generate alarms and notifications so that relevant personnel can be notified immediately when problems or abnormal situations occur.

[0046] Identify logistics parameters that require monitoring and control, including cargo temperature, humidity, vibration, and location. These parameters can be selected based on logistics needs and cargo characteristics, with preset temperature ranges, humidity limits, vibration thresholds, and more. These rules can be based on industry standards, regulatory requirements, or user-defined, setting appropriate standard thresholds for the monitored parameters. These thresholds can be maximum / minimum values, average values, rates of change, or other indicators. Ensure that thresholds match business needs and cargo characteristics, and define actions and notification mechanisms that are triggered when monitored parameters exceed the set standard thresholds. These can include alarm notifications, warning lights, sound prompts, text message notifications, and more. Ensure that relevant personnel can take appropriate and timely measures to resolve issues or prevent further risks.

[0047] The storage module includes an original data unit, a history track unit and a state update unit, the storage module is connected to the original data unit, the original data unit is connected to the history track unit, and the history track unit is connected to the state change unit;

[0048] The history track unit is used to record and store the location and movement history data of objects, vehicles, equipment or individuals.

[0049] The multi-data storage module includes an SQL unit, a NoSQL unit, and a time series database unit. The multi-data storage unit is connected to the SQL unit, the SQL unit is connected to the SoSQL unit, and the NoSQL unit is connected to the time series database unit.

[0050] The SQL unit is used to store, retrieve, update, and manage data in the database.

[0051] The visualization module includes a cargo virtualization unit and an interactive map unit, the visualization module is connected to the cargo virtualization unit, and the cargo virtualization unit is connected to the interactive map unit;

[0052] The visualization module provides visual dashboards and reports to help administrators monitor logistics processes. These dashboards can be customized as needed to display key performance indicators.

[0053] Through a visual interface, the system presents logistics data to users in the form of charts, maps, and dashboards. This visualization allows users to more intuitively understand logistics operations, trends, and key indicators. The system also generates reports and analytical results to aid decision-making and optimization.

[0054] The logistics optimization module includes a smart contract unit, a logistics agreement unit, and an automated payment unit. The logistics optimization unit is connected to the smart contract unit, the smart contract unit is connected to the logistics agreement unit, and the logistics agreement unit is connected to the automated payment unit.

[0055] The logistics optimization module is used to calculate the best cargo transportation route to reduce transportation time and cost.

[0056] The security module includes a system identification unit;

[0057] The system identification unit is used to allow authorized personnel to access the logistics management system and perform specific tasks.

[0058] Security and privacy protection are crucial in IoT-based logistics information management devices and systems. Measures such as data encryption transmission, identity authentication, and access control are adopted to protect data security and ensure that only authorized personnel can access sensitive information.

[0059] The security module also includes a blockchain unit and an audit log unit, and the blockchain unit is connected to the audit log unit;

[0060] Blockchain units are used for completely transparent data records, and every participant can view and verify the data.

[0061] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A logistics information management device based on the Internet of Things, comprising a bracket, characterized in that: The upper surface of the bracket is fixedly connected to a conveyor belt (3), the upper surface of the bracket is fixedly connected to a detection chamber (1), the conveyor belt (3) is arranged inside the detection chamber (1), the lower surface of the detection chamber (1) is fixedly connected to a scanner (4), the scanner (4) is arranged above the conveyor belt (3), the outer wall of the detection chamber (1) is fixedly connected to a console (2), and the lower surface of the console (2) is fixedly connected to a data port (5).

2. A logistics information management system based on the Internet of Things, according to the logistics information management device based on the Internet of Things according to claim 1, characterized in that: include: Internet interface module: The Internet interface module enables logistics equipment to connect with remote servers or cloud platforms, allowing remote monitoring and control; Cargo Identification Module: Identify, track and manage different types of cargo; Data processing module: Data collection, the data processing module will perform data cleaning operations to identify and correct errors, duplicates or incomplete information in the data; Storage module: stores raw IoT data for subsequent query; Multi-data storage module: Data from different sources are integrated into a unified storage module to achieve unified data management and analysis; Logistics Optimization Module: Autonomous vehicles, robotics, and automated warehouse technologies can be used to accelerate logistics processes; Security module: Implements tamper-proof audit logs to ensure data security and transparency: Visualization module: Provides an interactive map so that logistics managers can track the location of multiple shipments in real time and plan the best routes.

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