Remote monitoring system based on cold chain transportation process data

Abstract

The application discloses a remote monitoring system based on cold chain transportation process data and relates to the technical field of cold chain logistics. The remote monitoring system comprises a monitoring center and further comprises: a sensing module, which is used for acquiring temperature data in a cold chain compartment at various positions and external environment data; a thermodynamic model construction module, which is used for constructing a compartment thermodynamic model according to the acquired temperature data in the compartment and the external environment data; a transportation efficiency analysis module, which is used for evaluating the cold storage adaptation degree in the compartment according to the constructed compartment thermodynamic model, vehicle state data and to-be-transported article information, and judging whether the cold storage adaptation degree in the compartment meets the cold chain transportation demand according to an evaluation result; and a remote control module, which is used for issuing a remote operation instruction to a cold chain transportation vehicle that does not meet the cold chain transportation demand. The application realizes the spatial reconstruction of the heat distribution state in the compartment, so that the temperature distribution characteristics, heat exchange states and local temperature change trends of various regions in the compartment can be more accurately reflected.

Description

Technical Field

[0001] This invention relates to the field of cold chain logistics technology, specifically a remote monitoring system based on cold chain transportation process data. Background Technology

[0002] Cold chain transportation of pharmaceuticals refers to a transportation method that uses transport equipment with refrigeration and insulation functions to continuously maintain pharmaceuticals within a specified temperature range during transportation to ensure their quality, safety, and efficacy. For vaccines, biological agents, blood products, cell products, and some chemical drugs that require low-temperature storage, the transport environment temperature directly affects the drug's activity and stability. If the temperature exceeds the limit during transportation, it may lead to drug inactivation or even safety risks. Therefore, cold chain transportation of pharmaceuticals has high requirements for temperature control during the transportation process. Due to the combined effects of various factors such as air vents, cargo stacking, insulation structure, and changes in external ambient temperature, localized high-temperature zones, localized low-temperature zones, and temperature stratification can easily form inside refrigerated truck compartments. Relying solely on data from a limited number of temperature measurement points is insufficient to accurately reflect the overall thermal distribution within the compartment, which can easily lead to situations where the temperature at a monitoring point is normal while localized areas have experienced temperature anomalies. Therefore, a remote monitoring system based on cold chain transportation process data is now provided. Summary of the Invention

[0003] The purpose of this invention is to provide a remote monitoring system based on cold chain transportation process data.

[0004] The objective of this invention can be achieved through the following technical solution: a remote monitoring system based on cold chain transportation process data, including a monitoring center, wherein cold chain transportation vehicles upload vehicle status data and information on goods to be transported to the monitoring center, and further comprising: The sensing module is used to acquire temperature data inside the refrigerated truck compartment and external environmental data at various locations inside the compartment. The thermodynamic model building module is used to build a thermal model of the carriage based on the obtained temperature data inside the carriage and external environmental data; The transportation efficiency analysis module is used to evaluate the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported, and to determine whether the refrigeration suitability of the compartment meets the requirements of cold chain transportation based on the evaluation results. The remote control module is used to issue remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation.

[0005] Furthermore, the vehicle status data includes cargo compartment specification data, vehicle electrical energy data, and driving data. The cargo compartment specification data includes the interior dimensions of the cargo compartment, the material of the cargo compartment, the thickness and material of the vehicle insulation layer, and the location of the air vents inside the cargo compartment. The vehicle electrical energy data includes the power supply voltage and power of the refrigeration system. The driving data includes driving speed, vibration frequency, vibration amplitude, steering speed, and steering angle.

[0006] Furthermore, the sensing module consists of several temperature sensing terminals. The temperature values ​​of various locations inside the carriage are obtained in real time through the temperature sensing terminals deployed at various locations. After time synchronization of each temperature sensing terminal, the temperature time series data corresponding to each temperature sensing terminal is obtained. The temperature time series data obtained by all temperature sensing terminals are summarized as the temperature data inside the carriage. It also includes temperature sensing terminals deployed at various locations on the outer surface of the carriage to acquire the external ambient temperature at various locations on the carriage surface, and after time synchronization, summarize it as external environment data.

[0007] Furthermore, the process of constructing a thermal model of the carriage based on the obtained interior temperature data and external environmental data includes: A three-dimensional physical model of the carriage is established based on the carriage specification data. According to the deployment location of each temperature sensing terminal, a corresponding sensing data source is generated at the corresponding location in the three-dimensional physical model of the carriage, and the data obtained by each temperature sensing terminal is associated with the corresponding sensing data source. The corresponding thermal distribution field inside the carriage is constructed by using the data obtained from the sensor data source associated with each temperature sensor terminal inside the carriage, and the thermal distribution field on the carriage surface is constructed by using the data from the sensor data source associated with each temperature sensor terminal at various locations on the outer surface of the carriage. The obtained thermal distribution fields inside and on the surface of the compartment are mapped to the corresponding positions in the three-dimensional physical model of the compartment, thereby obtaining the thermal model of the compartment.

[0008] Furthermore, the process of constructing the thermal distribution field on the surface of the compartment is as follows: Based on the unit space inside the carriage near the inner surface of the carriage, the outer surface of the carriage is divided into several corresponding unit areas, and each vertex of the unit area has a corresponding temperature sensing terminal. The average temperature value of the outer surface obtained from the sensor data source of each vertex of each unit area is used as the temperature filling interpolation of the center of the unit area, thereby completing the construction of the thermal distribution field of the box surface.

[0009] Furthermore, the process of constructing the thermal distribution field inside the compartment includes: Based on the carriage specifications, a corresponding spatial coordinate system is established within the three-dimensional carriage physical model. Based on the actual installation position of each temperature sensing terminal in the carriage, the sensing data source corresponding to each temperature sensing terminal is mapped to the spatial coordinate system. Based on each sensor data source, the three-dimensional carriage physical model is spatially discretized to obtain several adjacent intra-carriage unit spaces. Each intra-carriage unit space consists of several vertices, boundary surfaces, and center points. Vertices and centers are defined as spatial nodes. Based on the sensor data sources contained in each compartment unit space, the corresponding measured temperature value is obtained, and the space node with the measured temperature value is defined as the known temperature node, and the remaining space nodes without temperature sensor terminals are defined as the temperature nodes to be filled. If the temperature node to be filled belongs to a certain compartment unit space, then the known temperature nodes contained in that compartment unit space are associated with the temperature node to be filled. For any temperature node to be filled, determine the associated known temperature nodes to obtain the distance influence coefficient between the temperature node to be filled and each known temperature node. Determine the unit area of ​​the nearest outer surface of the carriage corresponding to the temperature node to be filled, and obtain the outer surface temperature value corresponding to the unit area. Obtain the corresponding boundary heat exchange influence coefficient based on the distance from the temperature node to be filled to the carriage wall. The vehicle operation disturbance correction coefficient is obtained based on the vehicle status data, including driving speed, vibration frequency, and vibration amplitude. For each temperature node to be filled, the combined distance influence coefficient, boundary heat exchange influence coefficient, and vehicle operation disturbance correction coefficient are used to obtain the combined thermal influence weight of each associated known temperature node on the temperature node to be filled, and then the temperature filling interpolation of the temperature node to be filled is obtained. After completing the temperature filling of the current temperature node to be filled, update the temperature node to be filled to a known temperature node, and continue to perform the above process on the remaining temperature nodes to be filled until all vertices and center points corresponding to the unit space in the compartment have obtained the corresponding temperature filling interpolation.

[0010] Furthermore, the transportation efficiency analysis module evaluates the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported. The process of determining whether the refrigeration suitability meets the requirements of cold chain transportation based on the evaluation results includes: Obtain information about the items to be transported, including the type of goods, target transport temperature range, allowable temperature fluctuation range, allowable duration of overheating, loading location, and stacking method. Based on the loading location of the goods to be transported, the goods to be transported are mapped to the corresponding spatial area in the thermal model of the carriage to obtain the target temperature area corresponding to each goods to be transported. Based on the temperature values ​​of each spatial node contained in the target temperature region in the thermal model of the carriage, the average temperature, the highest temperature, the lowest temperature, and the temperature uniformity of the target temperature region are obtained. By further combining the power supply, voltage supply, vehicle speed, vibration frequency and vibration amplitude in the vehicle status data, the regional temperature change trend is corrected to obtain the predicted temperature change curve of the corresponding target temperature region, and a corresponding preset analysis time window is generated in the predicted temperature change curve. By generating the predicted temperature change curves and the target transportation temperature, allowable temperature fluctuation range, and allowable continuous over-temperature time corresponding to the items to be transported, the refrigeration adaptability corresponding to each target temperature zone is obtained. Based on the items to be transported within the target temperature zone, a corresponding suitability evaluation threshold is set. The obtained refrigeration suitability is compared with the suitability evaluation threshold of the items to be transported. If the refrigeration suitability is not lower than the suitability evaluation threshold, it means that the refrigeration suitability of the compartment within the target temperature zone meets the cold chain transportation requirements of the items to be transported. Otherwise, it means that the cold chain transportation requirements are not met, and the corresponding target temperature zone is marked as an abnormal zone.

[0011] Furthermore, the process by which the remote control module issues remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation includes: Based on the temperature difference between the average temperature of the abnormal area and the target transportation temperature range of the corresponding goods to be transported, this temperature difference is used as the temperature compensation range. Based on the temperature compensation range of the abnormal area, the required cooling compensation range for the air outlet is obtained. The cooling compensation range of all abnormal areas is summarized and analyzed to see if there is any intersection. If there is no intersection, the abnormal area with the largest cooling compensation range is removed and the analysis is repeated. This process is repeated until the analysis of all abnormal areas is completed. The intersection containing the most abnormal areas is selected, and a remote operation command is generated based on the cooling compensation range corresponding to the intersection. At the same time, a warning message is generated for the remaining abnormal areas. If there is an intersection, a remote operation command is generated based on the cooling compensation range corresponding to the intersection.

[0012] Compared with the prior art, the beneficial effects of the present invention are: 1. By collecting temperature data from multiple locations inside and outside the carriage and combining it with the carriage specification data to construct a three-dimensional physical model of the carriage, a thermal model of the carriage is further generated, realizing the spatial reconstruction of the heat distribution state inside the carriage. This enables a more accurate reflection of the temperature distribution characteristics, heat exchange state, and local temperature change trends of various areas inside the carriage, effectively improving the identification accuracy of local temperature anomaly areas. This provides a more comprehensive and reliable data foundation for real-time monitoring, anomaly analysis, and subsequent control of temperature status during the cold chain transportation of pharmaceuticals. 2. By comprehensively assessing the refrigeration suitability of the compartment based on the heat distribution status of the compartment, vehicle status data, and information on the medicines to be transported, and by executing corresponding remote control based on the assessment results, it is possible to analyze the causes of temperature anomalies by combining the heat exchange characteristics of the compartment and the transportation conditions, and to formulate targeted control strategies. This improves the level of intelligent management in the cold chain transportation process, helps to ensure that medicines are always in a suitable refrigerated environment, reduces refrigeration energy consumption, and improves transportation reliability and efficiency. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0014] Figure 1 This is a schematic diagram of the present invention; Figure 2 This is a schematic diagram showing the spatial node relationships within a portion of the compartment. Detailed Implementation

[0015] like Figure 1 As shown, the remote monitoring system based on cold chain transportation process data includes a monitoring center, where cold chain transport vehicles upload vehicle status data and information on goods to be transported to the monitoring center, and also includes: The sensing module is used to acquire temperature data inside the refrigerated truck compartment and external environmental data at various locations inside the compartment. The thermodynamic model building module is used to build a thermal model of the carriage based on the obtained temperature data inside the carriage and external environmental data; The transportation efficiency analysis module is used to evaluate the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported, and to determine whether the refrigeration suitability of the compartment meets the requirements of cold chain transportation based on the evaluation results. The remote control module is used to issue remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation.

[0016] It should be further explained that the vehicle status data includes cargo box specifications, vehicle electrical energy data, and driving data. The cargo box specifications include the interior dimensions of the cargo box, the material of the cargo box, the thickness and material of the vehicle insulation layer, and the location of the air vents inside the cargo box. The vehicle electrical energy data includes the power supply voltage and power of the refrigeration system. The driving data includes driving speed, vibration frequency, vibration amplitude, steering speed, and steering angle.

[0017] It should be further explained that, in the specific implementation process, the sensing module consists of several temperature sensing terminals, which are distributed in various locations inside the vehicle. It should be noted that corresponding temperature sensing terminals are installed at the air vents inside the vehicle, and corresponding temperature sensing terminals are also installed in other locations inside the vehicle. The installation is carried out by technicians according to actual needs, and the temperature sensing terminals inside the vehicle are installed in a corresponding manner, such as up and down, on both sides, and front and back. Temperature values ​​at various locations within the carriage are acquired in real time by temperature sensing terminals deployed at various locations. After time synchronization of each temperature sensing terminal, the temperature time series data corresponding to each temperature sensing terminal is obtained. The temperature time series data obtained by all temperature sensing terminals are summarized as the temperature data inside the carriage.

[0018] It also includes temperature sensing terminals deployed at various locations on the outer surface of the carriage to acquire the external ambient temperature at various locations on the carriage surface, and after time synchronization, summarize it as external environment data.

[0019] It should be further explained that, in the specific implementation process, the thermodynamic model construction module constructs the thermal model of the carriage based on the obtained interior temperature data and external environmental data, including the following steps: A three-dimensional physical model of the carriage is established based on the carriage specification data. According to the deployment location of each temperature sensing terminal, a corresponding sensing data source is generated at the corresponding location in the three-dimensional physical model of the carriage, and the data obtained by each temperature sensing terminal is associated with the corresponding sensing data source. The corresponding thermal distribution field inside the carriage is constructed by using the data obtained from the sensor data source associated with each temperature sensor terminal inside the carriage, and the thermal distribution field on the carriage surface is constructed by using the data from the sensor data source associated with each temperature sensor terminal at various locations on the outer surface of the carriage. The obtained thermal distribution fields inside and on the surface of the compartment are mapped to the corresponding positions in the three-dimensional physical model of the compartment, thereby obtaining the thermal model of the compartment.

[0020] It should be further explained that, in the specific implementation process, the construction process of the thermal distribution field on the surface of the compartment is as follows: Based on the unit space inside the carriage near the inner surface of the carriage, the outer surface of the carriage is divided into several corresponding unit areas, and each vertex of the unit area has a corresponding temperature sensing terminal. The average temperature value of the outer surface obtained from the sensor data source of each vertex of each unit area is used as the temperature filling interpolation of the center of the unit area, thereby completing the construction of the thermal distribution field of the box surface.

[0021] It should be further explained that, in the specific implementation process, the construction process of the thermal distribution field inside the compartment includes: Based on the carriage specifications, a corresponding spatial coordinate system is established within the three-dimensional carriage physical model. Based on the actual installation position of each temperature sensing terminal in the carriage, the sensing data source corresponding to each temperature sensing terminal is mapped to the spatial coordinate system. Based on each sensor data source, the three-dimensional carriage physical model is spatially discretized to obtain several adjacent intra-carriage unit spaces. It should be noted that each intra-carriage unit space consists of several vertices, boundary surfaces, and a center point, and adjacent intra-carriage unit spaces share common vertices and common boundary surfaces. Vertices and centers are defined as spatial nodes. Based on the sensor data sources contained in each compartment unit space, the corresponding measured temperature value is obtained, and the space node with the measured temperature value is defined as the known temperature node. Then, the remaining space nodes without temperature sensor terminals are defined as temperature nodes to be filled. If the temperature node to be filled belongs to a certain compartment unit space, then the known temperature nodes contained in that compartment unit space are associated with the temperature node to be filled. For any temperature node to be filled, determine the associated known temperature nodes to obtain the distance influence coefficient between the temperature node to be filled and each known temperature node. Specifically, the known temperature nodes are labeled as i, and the distance influence coefficient between the temperature node to be filled and the known temperature node labeled i is... Represented as: in: Let be the spatial distance between the temperature node to be filled and the i-th known temperature node. The length of the heat propagation path corresponding to the air supply direction along the carriage. This is the path correction factor. The effective heat propagation length is determined based on the dimensions of the carriage, the air supply capacity of the vents, and the vehicle's operating status. Further, determine the unit area of ​​the nearest outer surface of the carriage corresponding to the temperature node to be filled, and obtain the outer surface temperature value corresponding to the unit area. Obtain the corresponding boundary heat exchange influence coefficient Kb based on the distance from the temperature node to be filled to the carriage wall. Specifically: ; in: The obtained external surface temperature value, For preset reference temperature difference, The boundary heat effect length depends on the insulation capacity, the external heat load, and the air supply intensity of the air outlet. The boundary heat exchange intensity coefficient depends on the thickness of the insulation layer per unit area and the thermal conductivity of the insulation material. Furthermore, based on the vehicle status data, including driving speed, vibration frequency, and vibration amplitude, a vehicle operation disturbance correction coefficient is obtained. ; Specifically: ; Where: v is the vehicle speed, f is the vehicle vibration frequency, and A is the vehicle vibration amplitude. For correction factor, These are the preset reference speed, preset reference vibration frequency, and preset reference vibration amplitude, respectively. For each temperature node to be filled, the combined thermal influence weight of each associated known temperature node on the temperature node to be filled is obtained by integrating the distance influence coefficient, the boundary heat exchange influence coefficient, and the vehicle operation disturbance correction coefficient. ; Specifically: ; The corresponding temperature fill interpolation value is then obtained as Tp, where: ; in The measured temperature value corresponding to the known temperature node labeled i.

[0022] After completing the temperature filling of the current temperature node to be filled, update the temperature node to be filled to a known temperature node, and continue to perform the above calculation process on the remaining temperature nodes to be filled until all vertices and center points corresponding to the unit space in the compartment have obtained the corresponding temperature filling interpolation. like Figure 2 As shown, for example: The selected vertices of the unit space inside the compartment are A1, A2, A3, A4, A5, A6, A7, and A8. The sensor data sources are deployed at A1, A2, A3, A4, A5, A6, and A8, respectively. The known temperature nodes are A1, A2, A3, A4, A5, A6, and A8. It can be seen that A7 is a vertex inside the compartment and no temperature sensor terminal is deployed there. Therefore, the temperature nodes to be filled in the unit space inside the compartment are A1 and A7. The center point of the unit space in the compartment is denoted as a1. The measured temperature values ​​obtained from each sensor data source A1, A2, A3, A4, A5, A6, and A8 are obtained. Thus, the temperature filling interpolation of the temperature nodes a1 and A7 to be filled is obtained, and the temperature nodes a1 and A7 to be filled are updated to known temperature nodes. The vertices of the adjacent unit spaces within the compartment are B1, B2, B3, B4, B5, B6, B7, and B8. The sensor data sources are located at B1, B2, B3, B4, B5, and B6, which are known temperature nodes. The common vertices of the adjacent unit spaces within the compartment are B1 and A2, B4 and A3, B5 and A6, and B8 and A7. Therefore, B8 (A7) has been updated to a known temperature node. The center point of the unit space in the adjacent compartment is denoted as b1. Therefore, the temperature nodes to be filled in the unit space in the compartment are b1 and B7. The temperature filling interpolation of b1 and B7 is obtained based on the measured temperature values ​​of B1, B2, B3, B4, B5, and B6, as well as the temperature value of the known temperature node corresponding to B8 (i.e. A7). By analogy, the temperature filling interpolation values ​​of the center points c1 and d1 of the adjacent unit spaces in the compartment are obtained until the temperature filling interpolation values ​​of all temperature nodes to be filled are obtained.

[0023] It should be further explained that, in the specific implementation process, the transportation efficiency analysis module evaluates the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported. The process of determining whether the refrigeration suitability meets the requirements of cold chain transportation based on the evaluation results includes: Obtain information about the items to be transported, including the type of goods, target transport temperature range, allowable temperature fluctuation range, allowable duration of overheating, loading location, and stacking method. Based on the loading location of the goods to be transported, the goods to be transported are mapped to the corresponding spatial area in the thermal model of the carriage to obtain the target temperature area corresponding to each goods to be transported. Based on the temperature values ​​of each spatial node contained in the target temperature region in the thermal model of the carriage, the average temperature, the highest temperature, the lowest temperature, and the temperature uniformity of the target temperature region are obtained. Further combining vehicle status data such as power supply, voltage, speed, vibration frequency, and amplitude, the regional temperature change trend is corrected to obtain a predicted temperature change curve for the target temperature region. A corresponding preset analysis time window is then generated within the predicted temperature change curve. Specifically: The current temperature values ​​of each spatial node are obtained based on the current thermal model of the carriage; Obtain vehicle speed, power supply, power supply voltage, and external ambient temperature from the current vehicle status data; Based on a preset time interval Δt, a heat transfer update is performed on each spatial node, that is, the temperature value of all spatial nodes is updated every Δt. Repeatedly perform multiple time step updates to obtain the temperature values ​​corresponding to multiple moments for each spatial node; Arrange the temperatures corresponding to each moment of the same spatial node in chronological order to form a temperature change curve, and generate a predicted temperature change curve based on the trend of the temperature change curve. By generating the predicted temperature change curves and the target transportation temperature range, allowable temperature fluctuation range, and allowable continuous over-temperature time corresponding to the items to be transported, the refrigeration adaptability S corresponding to each target temperature zone is obtained. in: ; in, The average temperature of all spatial nodes within the target temperature region. The target transport temperature range for the goods to be transported within the target area, and meeting the following requirements. ,but ,but The actual value; This is the maximum permissible temperature deviation value. The standard deviation of temperature for all spatial nodes in the target temperature region. To preset the reference temperature standard deviation, To predict the maximum temperature fluctuation value of the temperature change curve within a preset analysis time window, To allow for temperature fluctuation range, Pr is the power supply capacity, U is the power supply voltage, and Ur is the rated voltage. These are the weighting coefficients; Based on the items to be transported within the target temperature zone, a corresponding suitability evaluation threshold is set. The obtained refrigeration suitability is compared with the suitability evaluation threshold of the items to be transported. If the refrigeration suitability is not lower than the suitability evaluation threshold, it means that the refrigeration suitability of the compartment within the target temperature zone meets the cold chain transportation requirements of the items to be transported. Otherwise, it means that the cold chain transportation requirements are not met, and the corresponding target temperature zone is marked as an abnormal zone.

[0024] It should be further explained that the process by which the remote control module issues remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation includes: The temperature difference between the average temperature of the abnormal area and the target transport temperature range of the corresponding goods to be transported is used as the temperature compensation range. It should be noted that the temperature difference is taken as the boundary of the target transport temperature range that is closest to the average temperature. For example, if the average temperature is lower than the lower limit of the target transport temperature range, the temperature compensation range is the difference between the average temperature and the lower limit to the difference between the average temperature and the upper limit. Conversely, if the average temperature is higher than the upper limit of the target transport temperature range, the compensation is the difference between the average temperature and the upper limit to the difference between the average temperature and the lower limit. If the average temperature is within the target transport temperature range, the temperature compensation is 0. If the temperature compensation for the abnormal area is 0, an early warning message is generated directly. Based on the temperature compensation range of the abnormal area, the required cooling compensation range for the air outlet is obtained. Summarize the cooling compensation range of all abnormal areas and analyze whether there is an intersection. If there is no intersection, it means that it is impossible to eliminate all abnormal areas by adjusting the air outlet temperature. Then, remove the abnormal area with the largest cooling compensation range and re-analyze. Repeat this process until the analysis of all abnormal areas is completed. Select the intersection containing the most abnormal areas and generate a remote operation command based on the cooling compensation range corresponding to the intersection. At the same time, generate early warning information for the remaining abnormal areas. If there is an intersection, it means that all abnormal areas can be eliminated by adjusting the air outlet temperature. Then, a remote operation command is generated based on the cooling compensation range corresponding to the intersection.

[0025] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications or equivalent substitutions made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A remote monitoring system based on cold chain transportation process data, comprising a monitoring center, wherein cold chain transport vehicles upload vehicle status data and information on goods to be transported to the monitoring center, characterized in that, Also includes: The sensing module is used to acquire temperature data inside the refrigerated truck compartment and external environmental data at various locations inside the compartment. The thermodynamic model building module is used to build a thermal model of the carriage based on the obtained temperature data inside the carriage and external environmental data; The transportation efficiency analysis module is used to evaluate the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported, and to determine whether the refrigeration suitability of the compartment meets the requirements of cold chain transportation based on the evaluation results. The remote control module is used to issue remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation.

2. The remote monitoring system based on cold chain transportation process data according to claim 1, characterized in that, Vehicle status data includes cargo box specifications, vehicle electrical energy data, and driving data. Cargo box specifications include the interior dimensions of the cargo box, cargo box material, thickness and material of the vehicle insulation layer, and the location of the interior air vents. Vehicle electrical energy data includes the power supply voltage and power of the refrigeration system. Driving data includes driving speed, vibration frequency, vibration amplitude, steering speed, and steering angle.

3. The remote monitoring system based on cold chain transportation process data according to claim 2, characterized in that, The sensing module consists of several temperature sensing terminals. The temperature values ​​of various locations inside the carriage are obtained in real time by the temperature sensing terminals deployed at various locations. After time synchronization of each temperature sensing terminal, the temperature time series data corresponding to each temperature sensing terminal is obtained. The temperature time series data obtained by all temperature sensing terminals are summarized as the temperature data inside the carriage. It also includes temperature sensing terminals deployed at various locations on the outer surface of the carriage to acquire the external ambient temperature at various locations on the carriage surface, and after time synchronization, summarize it as external environment data.

4. The remote monitoring system based on cold chain transportation process data according to claim 3, characterized in that, The process of constructing a thermal model of the train compartment based on the obtained interior temperature data and external environmental data includes: A three-dimensional physical model of the carriage is established based on the carriage specification data. According to the deployment location of each temperature sensing terminal, a corresponding sensing data source is generated at the corresponding location in the three-dimensional physical model of the carriage, and the data obtained by each temperature sensing terminal is associated with the corresponding sensing data source. The corresponding thermal distribution field inside the carriage is constructed by using the data obtained from the sensor data source associated with each temperature sensor terminal inside the carriage, and the thermal distribution field on the carriage surface is constructed by using the data from the sensor data source associated with each temperature sensor terminal at various locations on the outer surface of the carriage. The obtained thermal distribution fields inside and on the surface of the compartment are mapped to the corresponding positions in the three-dimensional physical model of the compartment, thereby obtaining the thermal model of the compartment.

5. The remote monitoring system based on cold chain transportation process data according to claim 4, characterized in that, The process of constructing the thermal distribution field on the surface of the compartment is as follows: Based on the unit space inside the carriage near the inner surface of the carriage, the outer surface of the carriage is divided into several corresponding unit areas, and each vertex of the unit area has a corresponding temperature sensing terminal. The average temperature value of the outer surface obtained from the sensor data source of each vertex of each unit area is used as the temperature filling interpolation of the center of the unit area, thereby completing the construction of the thermal distribution field of the box surface.

6. The remote monitoring system based on cold chain transportation process data according to claim 4, characterized in that, The process of constructing the thermal distribution field inside the compartment includes: Based on the carriage specifications, a corresponding spatial coordinate system is established within the three-dimensional carriage physical model. Based on the actual installation position of each temperature sensing terminal in the carriage, the sensing data source corresponding to each temperature sensing terminal is mapped to the spatial coordinate system. Based on each sensor data source, the three-dimensional carriage physical model is spatially discretized to obtain several adjacent intra-carriage unit spaces. Each intra-carriage unit space consists of several vertices, boundary surfaces, and center points. Vertices and centers are defined as spatial nodes. Based on the sensor data sources contained in each compartment unit space, the corresponding measured temperature value is obtained, and the space node with the measured temperature value is defined as the known temperature node, and the remaining space nodes without temperature sensor terminals are defined as the temperature nodes to be filled. If the temperature node to be filled belongs to a certain compartment unit space, then the known temperature nodes contained in that compartment unit space are associated with the temperature node to be filled. For any temperature node to be filled, determine the associated known temperature nodes to obtain the distance influence coefficient between the temperature node to be filled and each known temperature node. Determine the unit area of ​​the nearest outer surface of the carriage corresponding to the temperature node to be filled, and obtain the outer surface temperature value corresponding to the unit area. Obtain the corresponding boundary heat exchange influence coefficient based on the distance from the temperature node to be filled to the carriage wall. The vehicle operation disturbance correction coefficient is obtained based on the vehicle status data, including driving speed, vibration frequency, and vibration amplitude. For each temperature node to be filled, the combined distance influence coefficient, boundary heat exchange influence coefficient, and vehicle operation disturbance correction coefficient are used to obtain the combined thermal influence weight of each associated known temperature node on the temperature node to be filled, and then the temperature filling interpolation of the temperature node to be filled is obtained. After completing the temperature filling of the current temperature node to be filled, update the temperature node to be filled to a known temperature node, and continue to perform the above process on the remaining temperature nodes to be filled until all vertices and center points corresponding to the unit space in the compartment have obtained the corresponding temperature filling interpolation.

7. The remote monitoring system based on cold chain transportation process data according to claim 6, characterized in that, The transportation efficiency analysis module evaluates the refrigeration suitability of the compartment based on the constructed compartment thermal model, vehicle status data, and information on the goods to be transported. The process of determining whether the refrigeration suitability meets the requirements of cold chain transportation based on the evaluation results includes: Obtain information about the items to be transported, including the type of goods, target transport temperature range, allowable temperature fluctuation range, allowable duration of overheating, loading location, and stacking method. Based on the loading location of the goods to be transported, the goods to be transported are mapped to the corresponding spatial area in the thermal model of the carriage to obtain the target temperature area corresponding to each goods to be transported. Based on the temperature values ​​of each spatial node contained in the target temperature region in the thermal model of the carriage, the average temperature, the highest temperature, the lowest temperature, and the temperature uniformity of the target temperature region are obtained. By further combining the power supply, voltage supply, vehicle speed, vibration frequency and vibration amplitude in the vehicle status data, the regional temperature change trend is corrected to obtain the predicted temperature change curve of the corresponding target temperature region, and a corresponding preset analysis time window is generated in the predicted temperature change curve. By generating the predicted temperature change curves and the target transportation temperature, allowable temperature fluctuation range, and allowable continuous over-temperature time corresponding to the items to be transported, the refrigeration adaptability corresponding to each target temperature zone is obtained. Based on the items to be transported within the target temperature zone, a corresponding suitability evaluation threshold is set. The obtained refrigeration suitability is compared with the suitability evaluation threshold of the items to be transported. If the refrigeration suitability is not lower than the suitability evaluation threshold, it means that the refrigeration suitability of the compartment within the target temperature zone meets the cold chain transportation requirements of the items to be transported. Otherwise, it means that the cold chain transportation requirements are not met, and the corresponding target temperature zone is marked as an abnormal zone.

8. The remote monitoring system based on cold chain transportation process data according to claim 7, characterized in that, The process by which the remote control module issues remote operation commands to cold chain transport vehicles that do not meet the requirements of cold chain transportation includes: Based on the temperature difference between the average temperature of the abnormal area and the target transportation temperature range of the corresponding goods to be transported, this temperature difference is used as the temperature compensation range. Based on the temperature compensation range of the abnormal area, the required cooling compensation range for the air outlet is obtained. The cooling compensation range of all abnormal areas is summarized and analyzed to see if there is any intersection. If there is no intersection, the abnormal area with the largest cooling compensation range is removed and the analysis is repeated. This process is repeated until the analysis of all abnormal areas is completed. The intersection containing the most abnormal areas is selected, and a remote operation command is generated based on the cooling compensation range corresponding to the intersection. At the same time, a warning message is generated for the remaining abnormal areas. If there is an intersection, a remote operation command is generated based on the cooling compensation range corresponding to the intersection.

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