Cold-chain logistics transportation monitoring system based on Internet of Things

Abstract

The invention belongs to the technical field of logistics monitoring, and particularly discloses a cold-chain logistics transportation monitoring system based on the Internet of Things, which comprises a vehicle-mounted transportation terminal (sensing node), a transportation information aggregation station (aggregation node), a wireless communication module and a server. The vehicle-mounted terminal integrates a temperature and humidity sensor and a GPS module and monitors the temperature, the humidity and the vehicle position in real time. The processing module uses a Grubbs criterion to eliminate abnormal data, and encapsulates effective information for transmission; the sink node receives the data packet from the vehicle-mounted terminal, analyzes the data packet and uploads the data packet to the server; the wireless communication module adopts a LoRa technology to ensure efficient data transmission between the sensing node and the sink node; and the server is responsible for receiving, storing and analyzing data and providing data visualization and abnormity alarm functions. According to the system, the monitoring precision and reliability are remarkably improved, the energy consumption and communication efficiency are optimized, the intelligent level of goods tracking and management is enhanced, and remarkable beneficial effects are brought to cold-chain logistics transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics monitoring, and in particular to a cold chain logistics transportation monitoring system based on the Internet of Things. Background Art

[0002] With the rapid development of the cold chain logistics industry, higher requirements are placed on environmental monitoring and data management during transportation. Cold chain logistics involves the transportation of sensitive commodities such as food and medicine. These commodities have strict requirements on temperature and humidity conditions. Any slight environmental change may affect the quality and safety of the commodities. Therefore, it is very important to achieve real-time monitoring and data traceability of the cold chain logistics transportation process.

[0003] However, most of the existing cold chain logistics monitoring systems have the following problems: First, data transmission is unstable and easily affected by environmental interference, resulting in data loss or anomalies; second, the data processing capacity is insufficient, and abnormal data cannot be effectively identified and eliminated, affecting the accuracy and reliability of the monitoring system; third, the energy consumption is high, especially in remote areas or during long-term transportation, equipment energy consumption becomes a key factor restricting the application of the system; fourth, the data integration is low, and the data between different modules cannot be effectively linked and integrated, making it difficult to form a complete cargo status report.

[0004] In order to solve the above problems, the present invention proposes a cold chain logistics transportation monitoring system based on the Internet of Things, which realizes comprehensive, accurate and reliable monitoring and management of the cold chain logistics transportation process by optimizing data transmission methods, improving data processing capabilities, reducing energy consumption and improving data integration. Summary of the invention

[0005] In view of the shortcomings of the prior art mentioned above, the purpose of the present invention is to provide a cold chain logistics transportation monitoring system based on the Internet of Things, which is used to solve the problems of unstable data transmission, insufficient data processing capability, high energy consumption and low data integration in the prior art.

[0006] To achieve the above-mentioned purpose and other related purposes, the present invention provides a cold chain logistics transportation monitoring system based on the Internet of Things, which is composed of a sink node and a sensing node, wherein each sink node receives data from a plurality of sensing nodes, and the monitoring system comprises: The vehicle-mounted transport terminal, as the sensing node, includes a temperature and humidity sensor module, a GPS module, and a processing module; wherein the temperature and humidity sensor module is used to monitor the environmental temperature and humidity data in the cold chain logistics transportation process in real time; the GPS module is used to collect the location information of the cold chain logistics transportation vehicle in real time; the processing module is used to process the data of the temperature and humidity sensor module and the GPS module using the Grubbs criterion to remove abnormal values, and encapsulate and package the processed valid data; The transport information aggregation station, as the aggregation node, is used to receive data packets from the vehicle transport terminal, parse them and upload them to the server; A wireless communication module, used to realize data transmission between the sensing node and the aggregation node using LoRa technology; The server is used to receive, store and analyze cold chain logistics data from all aggregation nodes, and has data visualization and abnormal alarm functions.

[0007] Optionally, the processing module processes the data of the temperature and humidity sensor module and the GPS module using the Grubbs criterion to remove abnormal values, specifically including: The data collected by the temperature and humidity sensor module or the GPS module are respectively ( , Represents the number of measurement data points, then the module measures the arithmetic mean and standard deviation of the data: in, represents the arithmetic mean of the measured data, represents the i-th measurement data point; represents the standard deviation of the measured data; calculate the Grubbs statistic: in, represents the Grubbs statistic, which is a statistic used to measure the degree to which the measured data points deviate from the mean; According to the sample size of the measurement data set Determining critical values ​​for the Grubbs statistic The critical value can be found in the Grubbs statistical table or calculated by the following formula: in, It indicates the significant level, which is 0.05; If a measurement data point meets the following conditions, it is considered an outlier and needs to be removed: .

[0008] Optionally, the wireless communication module adopts LoRa wireless communication technology, and its configuration is as follows: When the AUX pin detects a rising edge, a configuration initialization instruction is sent through the serial port to configure the registers of the wireless communication module, including module address, network address, serial port baud rate, air rate, transmission power, channel, and key parameters; If the serial port receives a configuration confirmation response, it indicates that the parameters of the wireless communication module are successfully configured, and the wireless communication module is set to transparent transmission mode; if no configuration confirmation response is received, the parameter configuration instruction is resent until the configuration is successful.

[0009] Optionally, the sensing node encapsulates the processed temperature, humidity and location data according to a custom data transmission protocol, and sends it to the wireless communication module through the serial port. After receiving the data, the wireless communication module sends it to the aggregation node via wireless communication to achieve real-time data transmission and monitoring.

[0010] Optionally, the customized data transmission protocol includes the format and rules of data transmission between the perception node and the aggregation node. The data between the perception node and the aggregation node is transmitted in frames, and each frame of data includes a frame header, a data field, a check code and a frame tail.

[0011] Optionally, the sensing node receives the time synchronization response from the aggregation node to calibrate its own clock after each communication. If the sensing node successfully receives the time synchronization response from the aggregation node and the current data transmission task has been completed, the wireless communication module is powered off.

[0012] Optionally, the vehicle-mounted transport terminal is also provided with an RFID reader / writer for reading the RFID tag information on the goods. The RFID reader / writer works in conjunction with the temperature and humidity sensor module and the GPS module. When the status or position of the goods changes, it automatically triggers the reading of the RFID tag information and uploads the associated data to the server.

[0013] Optionally, when the temperature and humidity data are abnormal or the vehicle position changes significantly, the processing module automatically triggers the RFID reader to read the cargo RFID tag information, and integrates the cargo information, temperature and humidity data and location information into a cargo status report, which is uploaded to the server through the wireless communication module.

[0014] As described above, the cold chain logistics transportation monitoring system based on the Internet of Things proposed by the present invention has the following beneficial effects: By adopting the temperature and humidity sensor module and the GPS module, the system can monitor the environmental temperature and humidity data and vehicle location information in the cold chain logistics transportation process in real time to ensure the accuracy and timeliness of the data; the processing module uses the Grubbs criterion to process the collected data, effectively removes abnormal values, and improves the reliability and accuracy of the data; the customized data transmission protocol ensures the integrity and validity of the data during the transmission process, and reduces the possibility of data loss or error. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Shown is a structural block diagram of a cold chain logistics transportation monitoring system based on the Internet of Things according to an embodiment of the present invention; Figure 2 Shown is a structural schematic diagram of a wireless communication module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0017] It should be noted that the diagram provided in the present embodiment only illustrates the basic concept of the present invention in a schematic manner, so the diagram only shows the components related to the present invention rather than drawing according to the number, shape and size of the components during actual implementation. The type, quantity and ratio of each component during actual implementation can be a random change, and the component layout type may also be more complicated. The structure, ratio, size, etc. illustrated in the drawings of the present specification are only used to match the content disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions that the present invention can implement, so they have no technical substantive significance. Any modification of the structure, change of the proportional relationship or adjustment of the size should still fall within the scope of the technical content disclosed by the present invention without affecting the effect that the present invention can produce and the purpose that can be achieved. At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" quoted in this specification are only for the convenience of narration, and are not used to limit the scope of the present invention. The change or adjustment of its relative relationship should also be regarded as the scope of the present invention without substantially changing the technical content.

[0018] like Figure 1 As shown, a cold chain logistics transportation monitoring system based on the Internet of Things is provided. The system is composed of a sink node and a sensing node, wherein each sink node receives data from multiple sensing nodes. The monitoring system includes: The vehicle-mounted transport terminal, as a sensing node, includes a temperature and humidity sensor module, a GPS module, and a processing module; wherein the temperature and humidity sensor module is used to monitor the environmental temperature and humidity data in the cold chain logistics transportation process in real time; the GPS module is used to collect the location information of the cold chain logistics transportation vehicle in real time; the processing module is used to process the data of the temperature and humidity sensor module and the GPS module using the Grubbs criterion to remove abnormal values, and encapsulate and package the processed valid data; The transport information aggregation station, as an aggregation node, is used to receive data packets from the vehicle transport terminal, parse them and upload them to the server; Wireless communication module, used to realize data transmission between sensing nodes and aggregation nodes using LoRa technology; The server is used to receive, store and analyze cold chain logistics data from all aggregation nodes, with data visualization and abnormal alarm functions; In summary, the present invention can monitor the environmental temperature and humidity and vehicle location information in the cold chain logistics transportation process in real time through the temperature and humidity sensor module and GPS module of the vehicle-mounted transportation terminal, ensuring the accuracy and timeliness of the data. Secondly, the processing module uses the Grubbs criterion to process the data, effectively removes abnormal values, and improves the reliability and stability of the data. In addition, the wireless communication module uses LoRa technology to achieve low-power, long-distance data transmission, reducing the energy consumption and cost of the system. Finally, the server can receive, store and analyze cold chain logistics data from all aggregation nodes, provide data visualization and abnormal alarm functions, so that managers can intuitively understand the cold chain logistics transportation situation, and promptly discover and deal with potential problems. In summary, this system has the advantages of real-time monitoring, reliable data, low-power transmission and intelligent management, and provides strong technical support for the monitoring and management of cold chain logistics transportation.

[0019] Preferably, the processing module uses the Grubbs criterion to process the data of the temperature and humidity sensor module and the GPS module to remove abnormal values, specifically including: The data collected by the temperature and humidity sensor module or the GPS module are ( , Represents the number of measurement data points, then the module measures the arithmetic mean and standard deviation of the data: in, represents the arithmetic mean of the measured data, represents the i-th measurement data point; represents the standard deviation of the measured data; calculate the Grubbs statistic: in, represents the Grubbs statistic, which is a statistic used to measure the degree to which the measured data points deviate from the mean; According to the sample size of the measurement data set Determining critical values ​​for the Grubbs statistic , the critical value can be found in the Grubbs statistical table. The Grubbs statistical table may not cover all possible combinations of sample size and confidence level. Especially when the sample size is large (such as n>30) or a specific confidence level is required, the corresponding critical value may not be found in the table. It can also be calculated by the following formula: in, It indicates the significant level, which is 0.05; If a measurement data point meets the following conditions, it is considered an outlier and needs to be removed: .

[0020] Preferably, if Figure 2 As shown, the wireless communication module adopts LoRa wireless communication technology, including: Configuration initialization unit, when the AUX pin detects a rising edge, that is, when the AUX pin detects a voltage change from low to high, a configuration initialization instruction is sent through the serial port (Serial Port) to configure the registers of the wireless communication module. The parameters of the configuration initialization instruction are used to configure the registers inside the wireless communication module. The registers are the components inside the wireless communication module for storing data and control information. By modifying the values ​​of these registers, the working state and behavior of the wireless communication module can be changed.

[0021] Parameter setting unit, including setting parameters such as module address, network address, serial port baud rate, air rate, transmission power, channel, key, etc. The status confirmation unit, if the serial port receives a configuration confirmation response, it indicates that the parameters of the wireless communication module are successfully configured, and the wireless communication module is set to transparent transmission mode; if no configuration confirmation response is received, the parameter configuration command is resent until the configuration is successful.

[0022] Preferably, the sensing node encapsulates the processed temperature, humidity and location data according to a custom data transmission protocol, and sends it to the wireless communication module through the serial port. After receiving the data, the wireless communication module sends it to the aggregation node via wireless communication to achieve real-time data transmission and monitoring.

[0023] Preferably, the customized data transmission protocol includes the format and rules of data transmission between the sensing node and the sink node. The data between the sensing node and the sink node is transmitted in frames, and each frame of data includes a frame header, a data field, a check code and a frame tail. The frame header is used to identify the beginning of a frame of data, and usually uses a fixed byte sequence; for example, two bytes of "0xAA 0xBB" can be used as the frame header. The data field contains the actual transmitted data, including temperature and humidity data, location information, etc. The specific format of the data field is defined according to actual needs. Temperature and humidity data are represented by floating point numbers, such as "temperature: 25.3°C, humidity: 60.5%RH"; in order to save transmission bandwidth, the floating point number can be converted to an integer, such as multiplying the temperature and humidity by 100 and rounding. The location information is represented by longitude and latitude, such as "longitude: 116.404°, latitude: 39.915°"; similarly, in order to save transmission bandwidth, the longitude and latitude values ​​can be converted to integers. The check code is used to verify the integrity of the data, using simple sum check, CRC check, etc. In this example, the CRC16 check code is used. The frame tail is used to identify the end of a frame of data, and uses a fixed byte sequence; for example, two bytes of "0xCC 0xDD" are used as the frame tail.

[0024] In the sensing node, the processing module is responsible for processing the data from the temperature and humidity sensor module and the GPS module, and encapsulating them according to the above custom protocol. Then, the encapsulated data is sent to the wireless communication module through the serial port. After receiving the data, the wireless communication module sends it to the aggregation node through the LoRa wireless communication technology.

[0025] The sink node receives the data frame from the sensing node, parses and verifies it. If the data frame is verified to be correct, the temperature, humidity and location information are extracted and sent to the server for processing and storage.

[0026] Through the above customized data transmission protocol, the reliability and effectiveness of the data in the cold chain logistics transportation monitoring system can be ensured, providing a strong guarantee for the normal operation of the system.

[0027] Preferably, the sensing node will receive the time response from the aggregation node after each communication to calibrate its own clock. If the sensing node successfully receives the time response from the aggregation node and the current data transmission task has been completed, the wireless communication module will be powered off to save energy. If the sensing node fails to successfully receive the time response, a reasonable retry interval is set, such as a few seconds or minutes, and then try to receive the time response again. After multiple unsuccessful retries, the retry interval can be gradually increased to reduce the occupation of system resources and avoid network congestion; the sensing node sets a timer to monitor the time of receiving the time response. If the timer times out and no response is received, it is judged as a fault, and an alarm message is sent to the aggregation node or the server through the wireless communication module to prompt the system administrator to check and repair it.

[0028] It should be noted that the internal clock of both the sink node and the sensing node is provided by a crystal oscillator. However, due to differences in process and environment, the crystal oscillator may have a certain error. Therefore, by regularly calibrating the clock, the accuracy and stability of the system can be ensured. At the same time, by powering off the wireless communication module to save energy, the overall efficiency and sustainability of the system can be improved.

[0029] Preferably, the vehicle-mounted transport terminal is also provided with an RFID reader / writer for reading the RFID tag information on the goods. The RFID reader / writer works in conjunction with the temperature and humidity sensor module and the GPS module. When the status or location of the goods changes, it automatically triggers the reading of the RFID tag information and uploads the associated data to the server.

[0030] More preferably, when the temperature and humidity sensor module detects that the ambient temperature and humidity data in the cold chain logistics compartment exceeds the preset safety range, for example, the temperature exceeds the set maximum or minimum threshold, the processing module will immediately recognize this abnormal state. At the same time, the GPS module continuously monitors and updates the vehicle's location information. Once the cargo state is abnormal or the vehicle's location changes significantly, such as entering a new geographical area or approaching the destination, the processing module will automatically trigger the RFID reader. After receiving the trigger signal, the RFID reader will start scanning the RFID tags of the cargo in the compartment. Each RFID tag contains a unique identifier and the cargo information associated with it, such as cargo type, batch number, production date, etc. The RFID reader can quickly read these tag information and match and verify it with the cargo data stored in the processing module. The processing module combines the read RFID tag information with the current temperature and humidity data and location information to form a complete cargo status report, which is encapsulated into a data packet through the wireless communication module and transmitted to the transportation information aggregation station. After the aggregation node receives and parses the data packet, it uploads it to the server for further analysis and processing.

[0031] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A cold chain logistics transportation monitoring system based on the Internet of Things, the system is composed of a sink node and a sensing node, wherein each sink node receives data from a plurality of sensing nodes, characterized in that: The monitoring system comprises: The vehicle-mounted transport terminal, as the sensing node, includes a temperature and humidity sensor module, a GPS module, and a processing module; wherein the temperature and humidity sensor module is used to monitor the environmental temperature and humidity data in the cold chain logistics transportation process in real time; the GPS module is used to collect the location information of the cold chain logistics transportation vehicle in real time; the processing module is used to process the data of the temperature and humidity sensor module and the GPS module using the Grubbs criterion to remove abnormal values, and encapsulate and package the processed valid data; The transport information aggregation station, as the aggregation node, is used to receive data packets from the vehicle transport terminal, parse them and upload them to the server; A wireless communication module, used to realize data transmission between the sensing node and the aggregation node using LoRa technology; The server is used to receive, store and analyze cold chain logistics data from all aggregation nodes, and has data visualization and abnormal alarm functions.

2. According to the cold chain logistics transportation monitoring system based on the Internet of Things according to claim 1, it is characterized in that: The processing module uses the Grubbs criterion to process the data of the temperature and humidity sensor module and the GPS module to remove abnormal values, specifically including: The data collected by the temperature and humidity sensor module or the GPS module are respectively ( , Represents the number of measurement data points, then the module measures the arithmetic mean and standard deviation of the data: in, represents the arithmetic mean of the measured data, represents the i-th measurement data point; represents the standard deviation of the measured data; calculate the Grubbs statistic: in, represents the Grubbs statistic, which is a statistic used to measure the degree to which the measured data points deviate from the mean; According to the sample size of the measurement data set Determining critical values ​​for the Grubbs statistic The critical value can be found in the Grubbs statistical table or calculated by the following formula: in, It indicates the significant level, which is 0.05; If a measurement data point meets the following conditions, it is considered an outlier and needs to be removed: 。 3. According to the cold chain logistics transportation monitoring system based on the Internet of Things in claim 1, it is characterized in that: The wireless communication module adopts LoRa wireless communication technology, and its configuration is as follows: When the AUX pin detects a rising edge, a configuration initialization instruction is sent through the serial port to configure the registers of the wireless communication module, including module address, network address, serial port baud rate, air rate, transmission power, channel, and key parameters; If the serial port receives a configuration confirmation response, it indicates that the parameters of the wireless communication module are successfully configured, and the wireless communication module is set to transparent transmission mode; if no configuration confirmation response is received, the parameter configuration instruction is resent until the configuration is successful.

4. According to the cold chain logistics transportation monitoring system based on the Internet of Things in claim 3, it is characterized in that: The sensing node encapsulates the processed temperature, humidity and location data according to a custom data transmission protocol, and sends it to the wireless communication module through the serial port. After receiving the data, the wireless communication module sends it to the aggregation node via wireless communication to achieve real-time data transmission and monitoring.

5. According to the cold chain logistics transportation monitoring system based on the Internet of Things according to claim 4, it is characterized in that: The customized data transmission protocol includes the format and rules of data transmission between the sensing node and the aggregation node. The data between the sensing node and the aggregation node is transmitted in frames, and each frame of data includes a frame header, a data field, a check code and a frame tail.

6. The cold chain logistics and transportation monitoring system based on the Internet of Things according to claim 5 is characterized in that: The sensing node receives the time synchronization response from the aggregation node to calibrate its own clock after each communication. If the sensing node successfully receives the time synchronization response from the aggregation node and the current data transmission task has been completed, the wireless communication module is powered off.

7. The cold chain logistics and transportation monitoring system based on the Internet of Things according to claim 1 is characterized in that: The vehicle-mounted transport terminal is also provided with an RFID reader / writer for reading the RFID tag information on the goods. The RFID reader / writer works in conjunction with the temperature and humidity sensor module and the GPS module. When the state or position of the goods changes, it automatically triggers the reading of the RFID tag information and uploads the associated data to the server.

8. The cold chain logistics and transportation monitoring system based on the Internet of Things according to claim 7 is characterized in that: When the temperature and humidity data are abnormal or the vehicle position changes significantly, the processing module automatically triggers the RFID reader to read the cargo RFID tag information, and integrates the cargo information, temperature and humidity data and location information into a cargo status report, which is uploaded to the server through the wireless communication module.

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