An intelligent temperature control system for cold chain cargo transportation based on Internet of Things

Abstract

The present application relates to the technical field of cold chain transportation, and specifically discloses an intelligent temperature control system for cold chain cargo transportation based on the Internet of Things. The present application uses the smaller of the volume collected by the temperature sensor and the volume controlled by the temperature control element as the unit volume, ensures that the temperature control range of the temperature control element is completely covered by the sensor monitoring, avoids temperature control lag or blind spots caused by insufficient monitoring range, better meets the requirements of cold chain cargo for specific temperature environment, and helps to prolong the preservation period of the cargo. The effective transportation temperature is analyzed according to the transportation environment evaluation index and the cargo state coefficient, and the efficient transportation temperature corresponding to the transportation cold chain cargo characteristic vector is considered, the effective transportation temperature and the efficient transportation temperature are compared, the suitable transportation temperature is determined, the suitable transportation temperature corresponding to each transportation period can be accurately analyzed according to the actual transportation situation and the cargo characteristics, and the temperature control is more scientific and reasonable.

Description

Technical Field

[0001] This invention relates to the field of cold chain transportation technology, specifically to an intelligent temperature control system for cold chain cargo transportation based on the Internet of Things. Background Technology

[0002] With the continuous improvement of people's living standards, the market demand for cold chain goods such as fresh food continues to rise, and the cold chain logistics industry is ushering in a period of rapid development. Cold chain goods have extremely strict requirements for the temperature environment during transportation. Even slight temperature fluctuations or unsuitable temperature and humidity conditions can accelerate the deterioration of goods, shorten the shelf life, or even cause the goods to lose their usability, resulting in huge economic losses. Therefore, an efficient and precise temperature control system has become the key to ensuring the quality of cold chain goods transportation.

[0003] Traditional cold chain cargo transportation temperature control systems mostly adopt a crude, uniform temperature control model, treating the entire transport compartment as a single temperature-controlled space. This approach cannot address the uneven temperature distribution within the compartment caused by factors such as cargo distribution and the location of refrigeration equipment. For example, in actual transportation, the temperature near the air vents of the refrigeration equipment may be lower, while corners further away from the vents may experience higher temperatures. This results in cold chain goods within the same compartment facing different temperature environments, causing some goods to spoil prematurely due to unsuitable temperatures.

[0004] Meanwhile, existing temperature control technologies have limited capabilities in responding to dynamic changes in the transportation environment. During cold chain transportation, environmental factors such as ambient temperature, humidity, sunlight intensity, and vehicle vibration are constantly changing, and traditional systems struggle to dynamically adjust their temperature control strategies based on these real-time changes. For example, in hot weather, a large amount of heat from the outside environment enters the vehicle compartment; if cooling is not strengthened in time, the temperature inside the compartment will rise rapidly. When the vehicle vibrates or bumps, the operation of the refrigeration equipment may be affected, leading to unstable cooling effects, but traditional systems cannot respond effectively to these issues.

[0005] Furthermore, existing cold chain transportation temperature control systems rely on relatively simple methods for monitoring cargo status, primarily focusing on temperature measurement. They lack comprehensive monitoring of key indicators such as changes in cargo weight and fluctuations in gas concentrations (e.g., oxygen, carbon dioxide, ethylene). Changes in these indicators directly reflect the freshness and spoilage risk of goods; the lack of comprehensive monitoring makes it impossible to accurately assess cargo status and implement timely, targeted temperature control measures. For example, fresh fruits and vegetables release ethylene gas during transportation, accelerating the ripening and spoilage of themselves and surrounding goods. If ethylene concentration cannot be monitored in real time and temperature control strategies adjusted accordingly, the quality of the goods will be severely affected.

[0006] To address the aforementioned shortcomings, a technical solution is provided. Summary of the Invention

[0007] The purpose of this invention is to provide an intelligent temperature control system for cold chain cargo transportation based on the Internet of Things, so as to solve the above-mentioned technical problems existing in the prior art.

[0008] The objective of this invention is achieved through the following technical solution:

[0009] An IoT-based intelligent temperature control system for cold chain cargo transportation includes:

[0010] The cargo area division module is used to divide the cargo space of the cold chain cargo transport vehicle into sub-space areas, and to install temperature sensors and temperature control elements in the corresponding compartments of each sub-space area. The temperature control elements installed in each sub-space area are controlled by the main control terminal.

[0011] The transportation environment monitoring module is used to monitor and analyze the transportation environment at preset time intervals when the transport vehicle starts transportation, and obtain the transportation environment assessment indicators corresponding to each transportation period.

[0012] The cargo status monitoring module is used to monitor the cargo status during each transportation period and obtain the cargo status coefficient corresponding to each transportation period.

[0013] The suitable transportation temperature analysis module is used to analyze the suitable transportation temperature for each transportation period based on the transportation stage corresponding to each transportation period.

[0014] The transportation temperature acquisition module is used to acquire the transportation temperature of each sub-space area during each transportation period through temperature sensors;

[0015] The abnormal subspace region discrimination module is used to compare the transportation temperature of each subspace region during each transportation period with the appropriate transportation temperature for each transportation period, and thereby discern abnormal transportation periods and abnormal subspace regions.

[0016] The transportation temperature control module is used to regulate the transportation temperature of the temperature control elements in the abnormal sub-regions during abnormal transportation periods through the main control terminal, so that the temperature meets the appropriate transportation temperature.

[0017] The transportation temperature early warning terminal is used to compare the transportation temperature of each sub-area during each transportation period with the set early warning transportation temperature. If the transportation temperature of a certain sub-area during a certain monitoring period is greater than the early warning transportation temperature, an abnormal transportation temperature early warning will be issued.

[0018] The server is used to store the volume of the acquisition coverage area corresponding to each temperature sensor specification and model, the volume of the control coverage area corresponding to each temperature control element specification and model, the temperature corresponding to each colorimetric value, and the thermal conductivity of each packaging material.

[0019] The beneficial effects of this invention are:

[0020] This invention compares the coverage volume collected by the temperature sensor with the coverage volume controlled by the temperature control element, using the smaller value as the unit coverage volume. This ensures that the temperature control range of the temperature control element is completely covered by the sensor, avoiding temperature control lag or blind spots caused by insufficient monitoring range. For cold chain goods such as fresh food, this invention can better meet their requirements for specific temperature environments, helping to extend the shelf life of goods and ensure their quality.

[0021] This invention monitors and analyzes the transportation environment and cargo status of cold chain goods during various monitoring periods, and obtains real-time assessment results of transportation environment indicators and cold chain goods spoilage risk indicators. This provides a foundation for the subsequent analysis of the temperature control demand index for cold chain goods transportation, helps to detect abnormalities in the transportation process in advance, ensures that cold chain goods are transported in a suitable transportation temperature environment, and reduces cargo losses.

[0022] This invention analyzes suitable transportation temperatures based on transportation environment assessment indicators and cargo state coefficients. It also considers the efficient transportation temperature corresponding to the characteristic vector of cold chain cargo. By comparing the effective transportation temperature and the efficient transportation temperature, the suitable transportation temperature is determined. Based on actual transportation conditions and cargo characteristics, it can accurately analyze the suitable transportation temperature for each transportation period, making temperature control more scientific and reasonable, better meeting the temperature requirements of cold chain cargo, and ensuring the quality and safety of the cargo. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the connections between the modules of the present invention. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0025] like Figure 1 As shown, this invention is an intelligent temperature control system for cold chain cargo transportation based on the Internet of Things (IoT), comprising: a cargo area division module, a transportation environment monitoring module, a cargo status monitoring module, a suitable transportation temperature analysis module, a transportation temperature acquisition module, an abnormal subspace region discrimination module, a transportation temperature control module, a transportation temperature early warning terminal, and a server. The cargo area division module and the transportation temperature acquisition module are connected; the transportation environment monitoring module, the cargo status monitoring module, and the suitable transportation temperature analysis module are connected; the transportation temperature acquisition module is connected to the transportation temperature early warning terminal; the suitable transportation temperature analysis module, the transportation temperature acquisition module, and the abnormal subspace region discrimination module are connected; the abnormal subspace region discrimination module is connected to the transportation temperature control module; and the server is connected to the cargo area division module, the cargo status monitoring module, and the suitable transportation temperature analysis module.

[0026] The cargo area division module is used to divide the cargo space of the cold chain cargo transport vehicle into sub-space areas, and to install temperature sensors and temperature control elements in the corresponding compartments of each sub-space area. The temperature control elements installed in each sub-space area are controlled by the main control terminal.

[0027] For example, the temperature control element is a small refrigeration unit that integrates components such as a compressor, condenser, and evaporator.

[0028] For example, cold chain goods are fresh food products.

[0029] It should be noted that since the cargo space of a transport vehicle is usually quite regular, often rectangular or near-rectangular in shape, the sub-space areas are also mostly rectangular or similar in shape. When selecting temperature sensors and temperature control elements, in order to cover the sub-space areas as completely as possible, temperature sensors and temperature control elements that match the shape of the covered space areas should be selected as much as possible. This can improve the temperature control effect of the sub-space areas to a certain extent from the perspective of temperature control hardware.

[0030] Specifically, the process of dividing the cargo space area of ​​the cold chain cargo transport vehicle into sub-space areas is as follows:

[0031] The specifications and models of temperature sensors and temperature control elements are obtained and matched with the acquisition coverage space volume corresponding to each temperature sensor specification and model and the control coverage space volume corresponding to each temperature control element specification and model stored in the server, so as to obtain the acquisition coverage space volume corresponding to a single temperature sensor and the control coverage space volume corresponding to a single temperature control element.

[0032] The volume of the acquisition coverage area corresponding to a single temperature sensor and the volume of the control coverage area corresponding to a single temperature control element are compared and analyzed. If the volume of the acquisition coverage area is greater than or equal to the volume of the control coverage area, the volume of the control coverage area is taken as the unit coverage volume. If the volume of the acquisition coverage area is less than the volume of the control coverage area, the volume of the acquisition coverage area is taken as the unit coverage volume. The unit coverage volume is thus calculated and denoted as V. unit ;

[0033] The volume of the cargo space of a cold chain transport vehicle is obtained and denoted as V. total According to the formula The number of subspace regions n is calculated. zone In the formula Indicates the round-up operation symbol;

[0034] The cargo space of the cold chain transport vehicle is evenly divided according to the number of sub-space regions, thus obtaining the corresponding sub-space regions of the cold chain transport vehicle.

[0035] In one specific embodiment, the present invention compares the coverage volume collected by the temperature sensor with the coverage volume controlled by the temperature control element, using the smaller value as the unit coverage volume. This ensures that the temperature control range of the temperature control element is completely covered by the sensor, avoiding temperature control lag or blind spots caused by insufficient monitoring range. For cold chain goods such as fresh food, this invention can better meet their requirements for specific temperature environments, helping to extend the shelf life of goods and ensure their quality.

[0036] The transportation environment monitoring module is used to monitor the transportation environment at preset time intervals when the transport vehicle starts transportation, obtain transportation environment data corresponding to each transportation period, and analyze the transportation environment evaluation indicators corresponding to each transportation period.

[0037] It should be noted that the transportation environment data includes: ambient air temperature, atmospheric humidity, solar radiation intensity, wind force, transportation vehicle speed, and vibration amplitude of the transportation vehicle.

[0038] It should be further explained that the reason for using ambient air temperature, humidity, solar radiation intensity, wind force, transport vehicle speed, and transport vehicle vibration amplitude as the corresponding transport environment data for each transport period is as follows:

[0039] (1) Atmospheric temperature directly affects the external heat exchange of refrigerated truck compartments. If the outside temperature is too high, it will increase the heat load of the compartment's insulation layer, causing the refrigeration system inside the compartment to consume more energy to maintain the low temperature; if the outside temperature is too low, it may affect the normal operation of the refrigeration equipment and may also expose the goods to the risk of freezing damage.

[0040] (2) In a high humidity environment, water vapor is easy to condense inside and outside the carriage, which can cause the goods to get damp and the packaging to be damaged, which is not conducive to the preservation of the goods.

[0041] (3) The radiant heat generated by sunlight will increase the temperature of the carriage. Strong sunlight will cause the surface temperature of the carriage to rise rapidly, and the heat will be transferred into the carriage, interfering with the stability of the internal temperature. This may accelerate the spoilage process, especially for some temperature-sensitive fresh foods.

[0042] (4) Wind will affect the heat exchange rate. Strong winds will accelerate the air flow on the surface of the carriage, enhance convective heat transfer, and the enhanced convective heat transfer will affect the temperature stability inside the carriage.

[0043] (5) Changes in transport speed (rapid acceleration or deceleration) will cause the goods in the carriage to shake, affecting air circulation and thus affecting temperature uniformity.

[0044] (6) Vibration during the operation of the transport vehicle will affect the condition of the goods and the refrigeration equipment. Excessive vibration may cause the goods to collide and squeeze each other, resulting in damage; it may also cause the connection of the refrigeration equipment components to become loose, reducing the reliability and refrigeration effect of the refrigeration equipment, which is not conducive to the stable transportation of goods.

[0045] Specifically, the process of monitoring and analyzing the transportation environment is as follows:

[0046] The system acquires the ambient air temperature, humidity, solar radiation intensity, and wind speed for each transportation period and corresponding time point. It then calculates the absolute values ​​of these differences with preset reference air temperature, humidity, solar radiation intensity, and wind speed to obtain the ambient air temperature difference, humidity difference, solar radiation intensity difference, and wind speed difference for each transportation period and corresponding time point. These differences are then compared with preset allowable ambient air temperature difference, allowable humidity difference, allowable solar radiation intensity difference, and allowable wind speed difference to obtain the ratios of these differences for each transportation period and corresponding time point. Finally, these ratios are converted to long-distance ranges according to preset proportions. Ellipses are constructed with the lengths of the ratios of atmospheric temperature difference and atmospheric humidity difference as their major and minor axes, respectively. The center of the ellipse is selected, and an elliptical cylinder is constructed with the length of the ratio of solar intensity difference as its base and the height of the ellipse as its height. The center of the upper surface of the elliptical cylinder is selected, and a height corresponding to the length of the ratio of wind force difference is drawn at the center. An elliptical cone is constructed with the upper surface of the cylinder. The elliptical cylinder and the elliptical cone are marked as an elliptical cube combination. The volume value of the elliptical cube combination is extracted and marked as a type of transportation environment assessment index corresponding to each transportation time point in each transportation period. The types of transportation environment assessment indexes corresponding to each transportation period are obtained by accumulating them.

[0047] Obtain the transport vehicle speed at each transport time point corresponding to each transport period, filter out the maximum transport speed, and calculate the difference between it and the preset reference transport speed to obtain the transport speed deviation corresponding to each transport period.

[0048] At the same time, the transportation speed at each transportation time point is compared with the preset reference transportation speed. If the transportation speed at a certain transportation time point is greater than the preset reference transportation speed, then the transportation time point is recorded as a transportation speed influence point. The number of transportation speed influence points is counted, and the ratio of the number of transportation time points to the total number of transportation time points is calculated to obtain the transportation speed influence ratio.

[0049] The vibration amplitude of the transport vehicle at each transport time point is obtained for each transport period. A vibration amplitude curve is constructed with each transport time point as the abscissa and the vibration amplitude of the transport vehicle as the ordinate. The positions of each peak point and each valley point are identified from the curve. The vibration amplitude difference between each peak point and its adjacent valley point is extracted and the average vibration amplitude difference is calculated.

[0050] The vibration amplitude difference between each peak point and its adjacent valley point is compared with the preset reference vibration amplitude difference. If the vibration amplitude difference is greater than or equal to the preset reference vibration amplitude difference, the peak point is marked as a marked peak point. The number of marked peak points is obtained by counting the number of marked peak points. The frequency of vibration amplitude difference change corresponding to each transportation period is calculated by the ratio of the number of marked peak points to the number of all peak points.

[0051] The transport speed deviation, transport speed influence ratio, average vibration amplitude difference, and vibration amplitude difference change frequency corresponding to each transport period are converted into lengths according to a preset ratio. A sector region one is constructed with the length of the transport speed deviation as the radius and the length of the transport speed influence ratio as the arc length. A sector region two is constructed with the length of the average vibration amplitude difference as the radius and the length of the vibration amplitude difference change frequency as the arc length. The areas of sector region one and sector region two are extracted and summed to obtain the total area value as the second-class transport environment assessment index for each transport period.

[0052] The transportation environment assessment indicators for each transportation period are multiplied by the pre-set weighting factors and then summed to obtain the transportation environment assessment indicators for each transportation period.

[0053] It should be further explained that the preset weighting factors for the Class I and Class II transportation environment assessment indicators are 0.5 and 0.5, respectively.

[0054] The first category of transportation environment assessment indicators integrates natural environmental factors such as ambient temperature, humidity, solar radiation intensity, and wind force. These factors directly affect heat and humidity exchange between the refrigerated truck compartment and the outside environment, playing a crucial role in the stability of temperature and humidity within the compartment. The second category of transportation environment assessment indicators covers factors related to the transportation process, such as vehicle speed and vibration amplitude. Transportation speed affects the transit time of goods and airflow within the compartment, while vibration amplitude affects the condition of the goods and the operation of refrigeration equipment; both are also vital to the transportation environment. From the perspective of the overall transportation environment, the factors involved in these two categories have a comparable impact on the cold chain cargo transportation environment, therefore, they are assigned equal weight.

[0055] The cargo status monitoring module is used to monitor the cargo status during each transportation period and obtain the cargo status coefficient corresponding to each transportation period.

[0056] Specifically, the process of monitoring the status of goods during each transportation period is as follows:

[0057] Thermal images of the cold chain cargo storage area were comprehensively collected using an infrared thermal imager during each transportation period, resulting in thermal images of the cold chain cargo storage area for each transportation period. From each thermal image of each transportation period, the number of temperature distribution areas and the corresponding area and chromaticity value of each temperature distribution area were extracted. The chromaticity values ​​were then matched with the temperatures corresponding to the chromaticity values ​​stored in the server to obtain the temperatures corresponding to each temperature distribution area. The temperature distribution areas corresponding to the highest and lowest temperatures were then selected and designated as high-temperature and low-temperature distribution areas, respectively. The area and temperature of the high-temperature distribution area and the area and temperature of the low-temperature distribution area in each thermal image were extracted and denoted as follows: i represents the number of each monitoring period, i = 1, 2, ..., m; f represents the number of each thermal image, f = 1, 2, ..., g. Normalization is performed and the values ​​are taken according to the formula. The temperature uniformity index corresponding to each transportation period was calculated. In the formula This represents the total area of ​​the temperature distribution region in the f-th thermal image during the i-th transportation period;

[0058] Humidity was measured at various monitoring points in the cold chain goods storage area using humidity sensors. The humidity at each monitoring point was then recorded, and the maximum, minimum, and average humidity values ​​were selected and denoted as HU. max HU min HU avg Through the preset uniformity algorithm The humidity uniformity index HU for each transportation period was calculated. uniformity ;

[0059] The initial transport weight and initial concentrations of various gas components of the cold chain goods from the transport vehicle are extracted from the server. The transport weight and concentrations of various gas components for each transport period are then collected using weighing sensors and gas sensors at the last transport monitoring point. The difference in transport weight and concentration of various gas components for each transport period is calculated and denoted as ΔG. i ,

[0060] It should be noted that the concentrations of various gas components include oxygen concentration, carbon dioxide concentration, and ethylene concentration.

[0061] Extract the cold chain cargo transportation route, and at the same time extract the transportation time corresponding to each cold chain cargo transportation route from the transportation history stored in the server, and calculate the average of the historical transportation time corresponding to the cold chain cargo transportation route to obtain the average transportation time of the cold chain cargo transportation route, which is used as the reference transportation time of the cold chain cargo transportation route.

[0062] Extract the cumulative transportation time corresponding to each transportation period and calculate its ratio with the reference transportation time to obtain the transportation progress corresponding to each transportation period. Match the transportation progress corresponding to each transportation period with the preset permissible weight difference for cold chain cargo transportation and the permissible concentration difference for various gas components corresponding to each transportation progress to obtain the permissible weight difference for cold chain cargo transportation and the permissible concentration difference for various gas components corresponding to each transportation period, denoted as ΔG. i '、 j represents the number of each type of gas, j = 1, 2, 3;

[0063] Substitute into the preset Softplus function model Obtain the weight deviation coefficient corresponding to each transportation period. and gas concentration deviation coefficient

[0064] The weight deviation coefficient and gas concentration deviation coefficient are input into the processor. The graphics processor converts them into numerical values ​​according to a certain ratio and inputs them into the line graph to obtain two corresponding points. The two points are connected sequentially by line segments to obtain a line. The two endpoints of the line are drawn perpendicular to the X-axis so that the line and the two perpendicular lines form a closed figure with the X-axis. The area of ​​the closed figure is identified and the value of its area is used as the cold chain cargo spoilage risk index. Thus, the cold chain cargo spoilage risk index corresponding to each transportation period is statistically obtained.

[0065] The temperature uniformity index, humidity uniformity index, and cold chain cargo deterioration risk index corresponding to each transportation period are multiplied by preset weighting factors and then summed to obtain the cargo status coefficient corresponding to each transportation period.

[0066] It should be further explained that the preset weighting factors for the temperature uniformity index, humidity uniformity index, and cold chain cargo spoilage risk index are 0.3, 0.3, and 0.4, respectively.

[0067] The core objective of cold chain cargo transportation is to prevent spoilage. The cold chain cargo spoilage risk index comprehensively considers factors such as changes in cargo weight and gas concentration, directly reflecting the likelihood of spoilage. It holds a central position in assessing cargo condition and is therefore assigned a relatively high weight of 0.4. Temperature uniformity and humidity uniformity indices are also crucial for cargo preservation. Uneven temperature can lead to localized overheating or undercooling, accelerating spoilage; uneven humidity can cause partial dampness or dehydration. However, their individual impact on spoilage is slightly weaker than the spoilage risk index, and both play similar, interconnected, and complementary roles in affecting cargo preservation. Therefore, they are assigned the same, but relatively low, weight of 0.3.

[0068] In one specific embodiment, the present invention monitors and analyzes the transportation environment and cargo status of cold chain goods during each monitoring period, and obtains real-time judgment on transportation environment assessment indicators, cold chain goods deterioration risk indicators, etc., which provides a basis for subsequent analysis of the cold chain goods transportation temperature control demand index, helps to detect abnormal situations in the transportation process in advance, ensures that cold chain goods are transported in a suitable transportation temperature environment, and reduces cargo loss.

[0069] The suitable transportation temperature analysis module is used to analyze the suitable transportation temperature for each transportation period based on the transportation stage corresponding to each transportation period.

[0070] Specifically, the analysis process for the suitable transportation temperature corresponding to each transportation period is as follows:

[0071] The transportation environment assessment indicators and cargo status coefficients corresponding to each transportation period are extracted, and then multiplied by preset control demand influencing factors and summed to obtain the transportation temperature control demand index corresponding to each transportation period. This index is then matched with the preset effective transportation temperature corresponding to each transportation temperature control demand index to obtain the effective transportation temperature corresponding to each transportation period, denoted as .

[0072] Obtain the packaging material corresponding to the cold chain goods currently being transported, and match it with the thermal conductivity of the packaging materials stored in the server to obtain the thermal conductivity of the packaging material corresponding to the cold chain goods currently being transported.

[0073] The system obtains the type of cold chain goods currently being transported, the thermal conductivity of the packaging materials, the stacking density of the goods, and the average remaining shelf life. This information forms a feature vector for the current cold chain goods. This feature vector is then matched with the efficient transport temperatures corresponding to the feature vectors of each cold chain goods stored on the server to obtain the efficient transport temperature for each transport time period, denoted as .

[0074] Substitute the preset sigmoid function model The deviation of the transport temperature between the effective transport temperature and the high-efficiency transport temperature for each transport period is obtained. In the formula, e represents the natural constant;

[0075] The deviation of the effective transport temperature and the high-efficiency transport temperature corresponding to each transport period is compared and analyzed with the preset permissible transport temperature deviation. If the deviation of the effective transport temperature and the high-efficiency transport temperature corresponding to a certain transport period is greater than the preset permissible transport temperature deviation, then the effective transport temperature corresponding to that transport period is taken as the suitable transport temperature for that transport period; otherwise, the high-efficiency transport temperature corresponding to that transport period is taken as the suitable transport temperature for that transport period.

[0076] The appropriate transport temperature for each transport period can be obtained from the statistics.

[0077] In one specific embodiment, the present invention analyzes the suitable transportation temperature based on transportation environment assessment indicators and cargo state coefficients. It also considers the efficient transportation temperature corresponding to the characteristic vector of cold chain cargo, compares the effective transportation temperature and the efficient transportation temperature, and thus determines the suitable transportation temperature. Based on the actual transportation conditions and cargo characteristics, it can accurately analyze the suitable transportation temperature for each transportation period, making temperature control more scientific and reasonable, better meeting the temperature requirements of cold chain cargo, and ensuring the quality and safety of the cargo.

[0078] The transport temperature acquisition module is used to acquire the transport temperature of each subspace area during each transport period through temperature sensors.

[0079] The abnormal subspace region discrimination module is used to compare the transportation temperature of each subspace region during each transportation period with the suitable transportation temperature corresponding to each transportation period, and thereby determine the abnormal transportation period and abnormal subspace region.

[0080] Specifically, the process of identifying abnormal transportation periods and abnormal subspace regions is as follows:

[0081] The transport temperature of each sub-space region during each transport period is compared with the corresponding suitable transport temperature for each transport period. The suitability of transportation temperature for each subspace region during each transportation period is obtained;

[0082] The temperature suitability of each subspace region during each transportation period is compared with the preset temperature suitability threshold. If the temperature suitability of a certain subspace region during a certain transportation period is greater than or equal to the preset temperature suitability threshold, then the transportation period is determined to be an abnormal transportation period and the subspace region is an abnormal subspace region.

[0083] The transport temperature control module is used to regulate the transport temperature of the temperature control elements in the abnormal sub-regions during abnormal transport periods through the main control terminal, so that the temperature meets the appropriate transport temperature.

[0084] It should be noted that the temperature control element is used to regulate the transport temperature, including but not limited to regulating the refrigerant flow rate, compressor operating frequency and power, and evaporator fan speed.

[0085] The transport temperature early warning terminal is used to compare the transport temperature of each sub-area during each transport period with the set early warning transport temperature. If the transport temperature of a certain sub-area during a certain monitoring period is greater than the early warning transport temperature, an abnormal transport temperature warning will be issued to facilitate timely handling by cold chain cargo transport personnel and avoid serious deterioration and damage to cold chain cargo caused by abnormal transport temperature.

[0086] The server is used to store the volume of the acquisition coverage area corresponding to each temperature sensor specification and model, the volume of the control coverage area corresponding to each temperature control element specification and model, the temperature corresponding to each color value, and the thermal conductivity of each packaging material.

[0087] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

Claims

1. An intelligent temperature control system for cold chain cargo transportation based on the Internet of Things, characterized in that, include: The cargo area division module is used to divide the cargo space of the cold chain cargo transport vehicle into sub-space areas, and to install temperature sensors and temperature control elements in the corresponding compartments of each sub-space area. The temperature control elements installed in each sub-space area are controlled by the main control terminal. The transportation environment monitoring module is used to monitor and analyze the transportation environment at preset time intervals when the transport vehicle starts transportation, and obtain the transportation environment assessment indicators corresponding to each transportation period. The cargo status monitoring module is used to monitor the cargo status during each transportation period and obtain the cargo status coefficient corresponding to each transportation period. The suitable transportation temperature analysis module is used to analyze the suitable transportation temperature for each transportation period based on the transportation stage corresponding to each transportation period. The transportation temperature acquisition module is used to acquire the transportation temperature of each sub-space area during each transportation period through temperature sensors; The abnormal subspace region discrimination module is used to compare the transportation temperature of each subspace region during each transportation period with the appropriate transportation temperature for each transportation period, and thereby discern abnormal transportation periods and abnormal subspace regions. The process of monitoring and analyzing the transportation environment includes: The system acquires the ambient air temperature, humidity, solar radiation intensity, and wind speed for each transportation period and corresponding time point. It then calculates the absolute values ​​of these differences with preset reference air temperature, humidity, solar radiation intensity, and wind speed to obtain the ambient air temperature difference, humidity difference, solar radiation intensity difference, and wind speed difference for each transportation period and corresponding time point. These differences are then compared with preset allowable ambient air temperature difference, allowable humidity difference, allowable solar radiation intensity difference, and allowable wind speed difference to obtain the ratios of these differences for each transportation period and corresponding time point. Finally, these ratios are converted to long-distance ranges according to preset proportions. Ellipses are constructed with the lengths of the ratios of atmospheric temperature difference and atmospheric humidity difference as their major and minor axes, respectively. The center of the ellipse is selected, and an elliptical cylinder is constructed with the length of the ratio of solar intensity difference as its base and the height of the ellipse as its height. The center of the upper surface of the elliptical cylinder is selected, and a height corresponding to the length of the ratio of wind force difference is drawn at the center. An elliptical cone is constructed with the upper surface of the cylinder. The elliptical cylinder and the elliptical cone are marked as an elliptical cube combination. The volume value of the elliptical cube combination is extracted and marked as a type of transportation environment assessment index corresponding to each transportation time point in each transportation period. The types of transportation environment assessment indexes corresponding to each transportation period are obtained by accumulating them. Obtain the transport vehicle speed at each transport time point corresponding to each transport period, filter out the maximum transport speed, and calculate the difference between it and the preset reference transport speed to obtain the transport speed deviation corresponding to each transport period. At the same time, the transportation speed at each transportation time point is compared with the preset reference transportation speed. If the transportation speed at a certain transportation time point is greater than the preset reference transportation speed, then the transportation time point is recorded as a transportation speed influence point. The number of transportation speed influence points is counted, and the ratio of the number of transportation time points to the total number of transportation time points is calculated to obtain the transportation speed influence ratio. The vibration amplitude of the transport vehicle at each transport time point is obtained for each transport period. A vibration amplitude curve is constructed with each transport time point as the abscissa and the vibration amplitude of the transport vehicle as the ordinate. The positions of each peak point and each valley point are identified from the curve. The vibration amplitude difference between each peak point and its adjacent valley point is extracted and the average vibration amplitude difference is calculated. The vibration amplitude difference between each peak point and its adjacent valley point is compared with the preset reference vibration amplitude difference. If the vibration amplitude difference is greater than or equal to the preset reference vibration amplitude difference, the peak point is marked as a marked peak point. The number of marked peak points is obtained by counting the number of marked peak points. The frequency of vibration amplitude difference change corresponding to each transportation period is calculated by the ratio of the number of marked peak points to the number of all peak points. The transport speed deviation, transport speed influence ratio, average vibration amplitude difference, and vibration amplitude difference change frequency corresponding to each transport period are converted into lengths according to a preset ratio. A sector region one is constructed with the length of the transport speed deviation as the radius and the length of the transport speed influence ratio as the arc length. A sector region two is constructed with the length of the average vibration amplitude difference as the radius and the length of the vibration amplitude difference change frequency as the arc length. The areas of sector region one and sector region two are extracted and summed to obtain the total area value as the second-class transport environment assessment index for each transport period. The transportation environment assessment indicators for each transportation period are multiplied by the pre-set weighting factors and then summed to obtain the transportation environment assessment indicators for each transportation period.

2. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, Also includes: The transportation temperature control module is used to regulate the transportation temperature of the temperature control elements in the abnormal sub-regions during abnormal transportation periods through the main control terminal, so that the temperature meets the appropriate transportation temperature. The transportation temperature early warning terminal is used to compare the transportation temperature of each sub-area during each transportation period with the set early warning transportation temperature. If the transportation temperature of a certain sub-area during a certain monitoring period is greater than the early warning transportation temperature, an abnormal transportation temperature early warning will be issued. The server is used to store the volume of the acquisition coverage area corresponding to each temperature sensor specification and model, the volume of the control coverage area corresponding to each temperature control element specification and model, the temperature corresponding to each colorimetric value, and the thermal conductivity of each packaging material.

3. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, The specific process for dividing the cargo space area of ​​the cold chain cargo transport vehicle into sub-space areas is as follows: The specifications and models of temperature sensors and temperature control elements are obtained and matched with the acquisition coverage space volume corresponding to each temperature sensor specification and model and the control coverage space volume corresponding to each temperature control element specification and model stored in the server, so as to obtain the acquisition coverage space volume corresponding to a single temperature sensor and the control coverage space volume corresponding to a single temperature control element. The volume of the acquisition coverage area corresponding to a single temperature sensor and the volume of the control coverage area corresponding to a single temperature control element are compared and analyzed. If the volume of the acquisition coverage area is greater than or equal to the volume of the control coverage area, the volume of the control coverage area is taken as the unit coverage volume. If the volume of the acquisition coverage area is less than the volume of the control coverage area, the volume of the acquisition coverage area is taken as the unit coverage volume. The unit coverage volume is thus calculated and denoted as . ; Obtain the volume of the cargo space area of ​​the refrigerated cargo transport vehicle, denoted as . According to the formula The number of subspace regions was calculated. In the formula Indicates the round-up operation symbol; The cargo space of the cold chain transport vehicle is evenly divided according to the number of sub-space regions, thus obtaining the corresponding sub-space regions of the cold chain transport vehicle.

4. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, The process of monitoring the status of goods during each transportation period includes: The thermal images of the cold chain cargo storage area during each transportation period are collected from all directions using an infrared thermal imager. The thermal images of the cold chain cargo storage area during each transportation period are obtained. The number of temperature distribution areas and the corresponding area and chromaticity value of each temperature distribution area are extracted from the thermal images of each transportation period. The chromaticity value is matched with the temperature corresponding to each chromaticity value stored in the server to obtain the temperature corresponding to each temperature distribution area. The temperature distribution areas corresponding to the highest temperature and the lowest temperature are selected and designated as high temperature distribution areas and low temperature distribution areas, respectively. The area and temperature of the high temperature distribution area and the area and temperature of the low temperature distribution area in each thermal image are extracted, and the temperature uniformity index corresponding to each transportation period is calculated. The humidity of each monitoring point in the cold chain goods storage area is detected by a humidity sensor. The humidity of each monitoring point in the cold chain goods storage area is obtained, and the maximum humidity, minimum humidity and average humidity are selected. The humidity uniformity index corresponding to each transportation period is calculated by a preset uniformity algorithm.

5. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, The process of monitoring the status of goods during each transportation period also includes: The initial transport weight and initial concentration of various gas components of the cold chain goods in the transport vehicle are extracted from the server. The transport weight and concentration of various gas components of the cold chain goods at the last transport monitoring time point of each transport period are collected by weighing sensors and gas sensors respectively. The difference is calculated to obtain the difference in transport weight and concentration of various gas components of the cold chain goods in each transport period. Extract the cold chain cargo transportation route, and at the same time extract the transportation time corresponding to each cold chain cargo transportation route from the transportation history stored in the server, and calculate the average of the historical transportation time corresponding to the cold chain cargo transportation route to obtain the average transportation time of the cold chain cargo transportation route, which is used as the reference transportation time of the cold chain cargo transportation route. Extract the cumulative transportation time corresponding to each transportation period, and calculate the ratio with the reference transportation time to obtain the transportation progress corresponding to each transportation period. Match the transportation progress corresponding to each transportation period with the preset permissible weight difference of cold chain cargo transportation weight and permissible concentration difference of various gas components corresponding to each transportation progress to obtain the permissible weight difference of cold chain cargo transportation weight and permissible concentration difference of various gas components corresponding to each transportation period. Substituting the values ​​into the preset Softplus function model, we obtain the weight deviation coefficient and gas concentration deviation coefficient corresponding to each transportation period; The weight deviation coefficient and gas concentration deviation coefficient are input into the processor. The graphics processor converts them into numerical values ​​according to a certain ratio and inputs them into the line graph to obtain two corresponding points. The two points are connected sequentially by line segments to obtain a line. The two endpoints of the line are drawn perpendicular to the X-axis so that the line and the two perpendicular lines form a closed figure with the X-axis. The area of ​​the closed figure is identified and the value of its area is used as the cold chain cargo spoilage risk index. Thus, the cold chain cargo spoilage risk index corresponding to each transportation period is statistically obtained. The temperature uniformity index, humidity uniformity index, and cold chain cargo deterioration risk index corresponding to each transportation period are multiplied by preset weighting factors and then summed to obtain the cargo status coefficient corresponding to each transportation period.

6. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, The analysis process for the suitable transportation temperature corresponding to each transportation period is as follows: The transportation environment assessment indicators and cargo status coefficients corresponding to each transportation period are extracted, and then multiplied by preset control demand influencing factors and summed to obtain the transportation temperature control demand index corresponding to each transportation period. This index is then matched with the preset effective transportation temperature corresponding to each transportation temperature control demand index to obtain the effective transportation temperature corresponding to each transportation period, denoted as . , i represents the number of each monitoring period, i=1,2,...,m; Obtain the packaging material corresponding to the cold chain goods currently being transported, and match it with the thermal conductivity of the packaging materials stored in the server to obtain the thermal conductivity of the packaging material corresponding to the cold chain goods currently being transported. The system obtains the type of cold chain goods currently being transported, the thermal conductivity of the packaging materials, the stacking density of the goods, and the average remaining shelf life. This information forms a feature vector for the current cold chain goods. This feature vector is then matched with the efficient transport temperatures corresponding to the feature vectors of each cold chain goods stored on the server to obtain the efficient transport temperature for each transport time period, denoted as . ; Substitute the preset sigmoid function model The deviation of the transport temperature between the effective transport temperature and the high-efficiency transport temperature for each transport period is obtained. In the formula, e represents the natural constant; The deviation of the effective transport temperature and the high-efficiency transport temperature corresponding to each transport period is compared and analyzed with the preset permissible transport temperature deviation. If the deviation of the effective transport temperature and the high-efficiency transport temperature corresponding to a certain transport period is greater than the preset permissible transport temperature deviation, then the effective transport temperature corresponding to that transport period is taken as the suitable transport temperature for that transport period; otherwise, the high-efficiency transport temperature corresponding to that transport period is taken as the suitable transport temperature for that transport period. The appropriate transport temperature for each transport period can be obtained from the statistics.

7. The intelligent temperature control system for cold chain cargo transportation according to claim 1, characterized in that, The process for identifying abnormal transportation periods and abnormal sub-space regions is as follows: The transport temperature of each subspace region during each transport period is compared with the suitable transport temperature for each transport period. The results are then substituted into a preset logarithmic function model to obtain the suitability of the transport temperature for each subspace region during each transport period. The temperature suitability of each subspace region during each transportation period is compared with the preset temperature suitability threshold. If the temperature suitability of a certain subspace region during a certain transportation period is greater than or equal to the preset temperature suitability threshold, then the transportation period is determined to be an abnormal transportation period and the subspace region is an abnormal subspace region.

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