Intelligent container and control system

Abstract

The embodiment of the present specification provides a kind of intelligent container and control system, including box, refrigeration device, thermal imaging device, air quality detection device, air conditioning compartment and processor;Box at least includes floor and air outlet passage, floor is T-shaped board, air outlet passage is equipped with one-way pressure valve and first electric control valve;Refrigeration device at least includes air inlet passage, air outlet passage and freezer unit;Air conditioning compartment at least includes air conditioning device, air inlet passage, air inlet fan and conveying passage;Air inlet passage is provided with second electric control valve;Conveying passage is connected with the air inlet passage of refrigeration device, and conveying passage is provided with third electric control valve;Processor is configured to: based on thermal imaging device, air quality detection device obtains the monitoring data of intelligent container;Based on monitoring data, the internal environment of intelligent container is adjusted, and internal environment includes temperature and / or air quality.

Description

Technical Field

[0001] This manual relates to the field of logistics equipment, and in particular to an intelligent container and its control system. Background Technology

[0002] In logistics transportation, when transporting goods requiring refrigeration, such as frozen foods, refrigerated containers are often used to maintain a low temperature inside the container. However, due to different stacking methods, the airflow for refrigeration can be obstructed, potentially leading to uneven temperature distribution within the container during prolonged transport, thus affecting refrigeration efficiency. Furthermore, refrigerated goods, such as plants, may undergo metabolism. During transport, the metabolism of these goods can cause changes in the gas composition inside the container, which may not only adversely affect the goods but also impact refrigeration effectiveness.

[0003] Regarding the issue of regulating the temperature inside a container, CN109625655B proposes a container device capable of regulating the internal environment. This device accelerates air circulation inside the refrigerated container by installing a powerful exhaust fan in front of the heat-absorbing evaporator, thereby speeding up the reduction of the refrigerated temperature. However, this application still does not address issues such as how to maintain a uniform temperature distribution inside the container during transportation and avoid the influence of gases generated by the biological processes of the cargo itself.

[0004] Therefore, we hope to propose an intelligent container and control system that can intelligently adjust the temperature inside the container during transportation to ensure that the temperature distribution inside the container is always uniform and does not affect the quality of the goods. Summary of the Invention

[0005] This specification provides one or more embodiments of a smart container. It is characterized by comprising a container body, a refrigeration unit, a thermal imaging unit, an air quality detection unit, an air conditioning compartment, and a processor; the container body includes at least a floor and an air outlet channel, the floor being a T-shaped panel; the air outlet channel is equipped with a one-way pressure valve and a first electrically controlled valve, the opening and closing of the first electrically controlled valve controlling whether air is discharged from the container body; the refrigeration unit includes at least an air inlet channel, an air outlet channel, and a refrigeration unit; the air conditioning compartment includes at least an air conditioning unit, an air inlet channel, an air intake fan, and a conveying channel; the air inlet channel is equipped with a second electrically controlled valve, the opening and closing of the second electrically controlled valve controlling whether air is supplied to the container body; the conveying channel is connected to the air inlet channel of the refrigeration unit, and the conveying channel is equipped with a third electrically controlled valve; the processor is configured to: acquire monitoring data of the smart container based on the thermal imaging unit and the air quality detection unit; and adjust the internal environment of the smart container based on the monitoring data, the internal environment including temperature and / or air quality.

[0006] One embodiment of this specification provides an intelligent container control system, characterized in that it includes an acquisition module and a control module; the acquisition module acquires monitoring data of the intelligent container based on a thermal imaging device and an air quality detection device in the intelligent container; and adjusts the internal environment of the intelligent container based on the monitoring data, wherein the internal environment includes at least temperature and / or air quality. Attached Figure Description

[0007] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0008] Figure 1 These are schematic diagrams of the structure of a smart container according to some embodiments of this specification;

[0009] Figure 2 This is a schematic diagram illustrating temperature adjustment according to some embodiments of this specification;

[0010] Figure 3 This is a schematic diagram illustrating the determination of a temperature adjustment scheme according to some embodiments of this specification;

[0011] Figure 4 This is a schematic diagram illustrating the performance of a ventilation operation according to some embodiments of this specification;

[0012] Figure 5 This is an exemplary block diagram of an intelligent container control system according to some embodiments of this specification. Detailed Implementation

[0013] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this specification. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0014] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0015] As indicated in this specification and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of expressly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0016] Flowcharts are used in this specification to illustrate the operations performed by the system according to embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0017] During long-distance transportation, the temperature inside a container can be affected by various factors. CN109625655B only maintains a low temperature inside the container through heat-absorbing evaporators on mechanical baffles and powerful exhaust fans, but it cannot maintain a uniform temperature distribution throughout the container; secondly, its device cannot handle the effects of gas and temperature changes generated by the cargo's own metabolic activities.

[0018] Therefore, some embodiments of this specification, by collecting temperature distribution data inside the container, predicting future temperature distribution, specifying appropriate temperature adjustment schemes, and instructing devices to make adjustments, can not only maintain uniform temperature distribution by relying on the flexibly sliding air inlet, but also monitor the temperature and gas environment inside the container and make self-adjustments based on data analysis, thereby improving the reliability of container transportation.

[0019] Figure 1 This is a structural schematic diagram of a smart container according to some embodiments of this specification.

[0020] like Figure 1 As shown, in some embodiments, the smart container includes a container body 110, a refrigeration unit 130, a thermal imaging unit 160, an air quality detection unit 170, an air-conditioned compartment 140, and a processor 150.

[0021] The container 110 refers to the container body. In some embodiments, the container body includes at least a floor 111 and an air vent 120.

[0022] Floor 111 refers to a structure installed inside the container near the bottom plate. In some embodiments, the floor may be a T-shaped panel with exhaust vents for continuously supplying cool air to the area around the goods.

[0023] In some embodiments, there is a duct storage layer between the floor and the bottom plate of the enclosure, which can be used to store a second exhaust duct.

[0024] The vent passage 120 is the channel through which the container discharges gas. The vent passage includes a one-way pressure valve 121 and a first electrically controlled valve 123. The one-way pressure valve controls the pressure inside and outside the container to prevent reverse gas flow. The opening and closing of the first electrically controlled valve controls whether air is discharged from the container.

[0025] In some embodiments, the vent passage may further include a pressure detection device 122. The pressure detection device may be disposed between the one-way pressure valve and the first electrically controlled valve. The pressure detection device may be used to detect the pressure inside the container. When the pressure data obtained by the pressure detection device is greater than the pressure threshold, the first electrically controlled valve opens, and the gas inside the container can be discharged to the outside of the container through the vent passage.

[0026] The refrigeration unit 130 is used to regulate the temperature inside the container. In some embodiments, the refrigeration unit may include an air inlet duct 131, an air outlet duct 132, and a refrigeration unit 133.

[0027] When the refrigeration unit 130 is in operation, air enters the refrigeration unit through the air inlet channel 131, is processed by the refrigeration unit 133 to obtain refrigerated air, and then enters the cabinet 110 through the exhaust channel 132, thereby completing the temperature regulation of the cabinet.

[0028] Air inlet channel 131 is a channel for supplying air to the refrigeration unit.

[0029] Refrigeration unit 133 is a device used to provide a low-temperature environment inside a container. Refrigeration unit 133 achieves refrigeration of the container through a refrigeration cycle system.

[0030] The refrigeration cycle system includes at least a compressor, a condenser, an expansion valve, and an evaporator. Through the operation of this system, the refrigeration unit absorbs heat from inside the container and exhausts it to the external environment, thereby reducing the internal temperature of the container and achieving a refrigeration effect.

[0031] Exhaust duct 132 is a channel used to transfer refrigerated air to the container.

[0032] In some embodiments, the exhaust duct includes a first exhaust duct and a second exhaust duct. The first exhaust duct and the second exhaust duct may be arranged in parallel.

[0033] The first exhaust duct can be evenly installed near the floor of the container to uniformly deliver cold air from the bottom to the top of the container.

[0034] The second exhaust duct can deliver cool air through multiple movable exhaust vents, and the movement of the exhaust vents can be used to target specific areas of the container with air.

[0035] In some embodiments, the second exhaust duct is a distributed exhaust channel, including a main duct and sub-ducts. The main duct is equipped with a primary electrically controlled valve, the opening and closing of which controls whether airflow is allowed through the main duct. The main duct is connected to at least one sub-exhaust duct, and the sub-duct is equipped with a secondary electrically controlled valve, the opening and closing of which controls whether airflow is allowed through the sub-duct.

[0036] The main and sub-pipes are located in the pipe housing layer, which is situated below the T-shaped plate. The T-shaped plate has adjustable exhaust vents, and the pipe housing layer and the T-shaped plate are connected via these vents. The exhaust vents can respond to processor commands and slide along a sliding track via a moving device. This sliding track can be an S-shaped track, mounted on the T-shaped plate.

[0037] In some embodiments, the cooling device can execute a temperature adjustment scheme in response to temperature adjustment cooling from the processor.

[0038] The air-conditioning compartment 140 is a structure in the intelligent container used to regulate the air inside the container, and can be installed on the left or right sides of the container. The air-conditioning compartment may include at least an air conditioning unit 141, an air intake duct 142, an air intake fan 143, and a conveying duct 145.

[0039] Air conditioning unit 141 is a device for regulating the composition of air inside a container. The air conditioning unit includes at least one membrane separator. In some embodiments, the air conditioning unit can treat the air inside the container using the membrane separator to generate nitrogen-rich air with a higher nitrogen concentration, and then deliver the nitrogen-rich air into the container.

[0040] The air intake passage 142 is a passage for blowing in gas. The air intake passage may include a second electrically controlled valve 144. The opening and closing of the second electrically controlled valve is used to control whether air is supplied to the container body through the air intake passage 142.

[0041] The air intake fan 143 is a mechanical device used for exhausting gas.

[0042] The conveying channel 145 is a channel for conveying gas and is equipped with a third electrically controlled valve 146. The third electrically controlled valve is used to control the opening and closing of the conveying channel 145.

[0043] In some embodiments, the conveying channel can be connected to the air inlet channel of the refrigeration unit. Outside air, driven by the intake fan, enters the air conditioning compartment through the intake channel, is processed by the air conditioning unit to obtain nitrogen-enriched air, and then enters the refrigeration unit through the conveying channel. The refrigeration unit's exhaust channel then delivers the cooled, nitrogen-enriched air into the container body.

[0044] Once the smart container is in operation, air from outside the container enters the air conditioning chamber through the air intake channel under the action of the air intake fan. The air is then processed by the membrane separator in the air conditioning chamber to form nitrogen-rich air. The nitrogen-rich air then enters the air intake channel of the refrigeration unit through the conveying channel. After being cooled by the refrigeration unit, the air enters the container through the exhaust channel, thus achieving the cooling of the inside of the smart container.

[0045] As air is continuously introduced, the pressure inside the smart container gradually increases. Therefore, to ensure safety, some air needs to be discharged through the venting channel. The venting channel is equipped with a one-way pressure valve and a first electrically controlled valve. When the pressure inside the container exceeds the pressure threshold of the one-way pressure valve, gas passes through the one-way pressure valve and enters the transition space between the one-way pressure valve and the first electrically controlled valve. When the pressure sensor reading in the transition space exceeds the pressure threshold, the first electrically controlled valve automatically opens, achieving ventilation and preventing backflow of gas.

[0046] The above process requires control by processor 150.

[0047] The processor 150 can be configured to acquire monitoring data of the smart container based on the thermal imaging device 160 and the air quality detection device 170; and to adjust the internal environment of the smart container based on the monitoring data, including temperature and / or air quality.

[0048] Thermal imaging device 160 refers to a device used to acquire temperature distribution data.

[0049] Air quality detection device 170 is used to detect air composition and concentration. The air quality detection device can include various sensors, such as carbon dioxide sensors and oxygen sensors, which can be configured according to actual monitoring needs.

[0050] In some embodiments, the processor 150 can also be used to determine a target future time in response to the future temperature distribution characteristics not meeting the preset temperature conditions; determine the temperature adjustment area at the target future time based on the temperature distribution characteristics at the target future time; and determine a temperature adjustment scheme based on the temperature adjustment area, wherein the temperature adjustment scheme includes at least one of execution time, number of exhaust vents, exhaust vent location, and opening degree of electrically controlled valve.

[0051] In some embodiments, the processor 150 can also be configured to: generate an initial ventilation command in response to the state of the smart container meeting a first preset condition; control the air conditioning unit to perform an initial ventilation operation based on the initial ventilation command; acquire air quality data through an air quality monitoring device in response to the state of the smart container meeting a second preset condition; generate a ventilation command in response to the air quality data meeting the first air quality condition; control the air conditioning unit to perform a ventilation operation based on the ventilation command, the ventilation operation including at least opening a second electrically controlled valve and a third electrically controlled valve, and starting an intake fan; and generate a ventilation stop command in response to the air quality data meeting the second air quality condition, and control the air conditioning unit to stop the ventilation operation based on the ventilation stop command.

[0052] For details regarding the processor's functionality, please refer to [link / reference]. Figures 2-5 And related explanations.

[0053] Figure 2 This is a schematic diagram illustrating the temperature adjustment process according to some embodiments of this specification. For example... Figure 2 As shown, the temperature adjustment process 200 may include the following.

[0054] In some embodiments, the processor can extract the temperature distribution characteristics at the current moment based on the temperature distribution data of the smart container; predict the future temperature distribution characteristics based on the temperature distribution characteristics; determine a temperature adjustment scheme based on the future temperature distribution characteristics in response to the future temperature distribution characteristics not meeting the preset temperature conditions; generate an adjustment command based on the temperature adjustment scheme; and control the refrigeration device to adjust the temperature inside the smart container based on the adjustment command.

[0055] Temperature distribution data 210 refers to data relating to the temperature at various locations within the container. In some embodiments, the temperature distribution data can be acquired using a thermal imaging device. The thermal imaging device can be at least one infrared thermal imager.

[0056] In some embodiments, the processor can pre-divide the internal space of the smart container based on temperature distribution data to obtain multiple temperature zones. For example, the internal space of the smart container can be divided into multiple sub-regions based on preset division rules, and the temperature of each sub-region can be determined based on temperature distribution data. A clustering algorithm can then be used to obtain multiple temperature zones and their corresponding temperature values. For example, clustering can be performed based on the temperature difference between a sub-region and its neighboring sub-regions. At least one sub-region with a temperature difference within a target temperature range can be grouped into a cluster, and the region corresponding to this cluster can be considered as a temperature zone. The temperature value of this temperature zone is the average of the temperatures of the aforementioned at least one sub-region. Neighboring sub-regions refer to regions that share a common edge with the aforementioned sub-regions. The preset division criteria include the division shape and division area, which can be preset manually.

[0057] Temperature distribution characteristic 224 refers to the distribution characteristics of temperature distribution data inside the container.

[0058] In some embodiments, temperature distribution characteristics can be represented by a temperature distribution characteristic map.

[0059] A temperature distribution feature map can include nodes and edges. Nodes can represent temperature regions within the enclosure, and node features can include the temperature value, area, and location of the temperature region. Edges can represent any two temperature regions connected together, and edge features can include the distance between the temperature regions.

[0060] In some embodiments, the processor can predict future temperature distribution characteristics based on current temperature distribution characteristics 227.

[0061] Future temperature distribution characteristic 227 refers to the temperature distribution characteristics of a container at a future point in time. Future temperature distribution characteristics can include the temperature distribution over future times.

[0062] In some embodiments, future temperature distribution characteristics can be predicted based on historical temperature distribution characteristics. Historical temperature distribution characteristics refer to the temperature distribution characteristics and their changes over a past period. The processor can determine future temperature distribution characteristics based on the average of historical temperature distribution characteristics corresponding to at least one historical moment.

[0063] In some embodiments, the future temperature distribution characteristics can be predicted by prediction model 220.

[0064] In some embodiments, the prediction model 220 may include a feature extraction layer 222 and a prediction layer 226. The prediction model may be a machine learning model; for example, the feature extraction layer may be a convolutional neural network (CNN) model, and the prediction layer may be a graph convolutional network (GNN) model.

[0065] In some embodiments, the input to the feature extraction layer 222 may include the palletizing method design diagram 221-1, and the output may be the palletizing feature vector 223.

[0066] Palletizing method design diagram 221-1 refers to a schematic diagram of a pre-set goods stacking method. For example, perishable goods are arranged far away from the container doors where air circulation is more frequent. Palletizing method design diagrams can be based on manual pre-setting.

[0067] The palletizing feature vector 223 can characterize the features of the palletizing method. For example, the stacking direction, the quantity of goods, etc.

[0068] In some embodiments, the input to the prediction layer 226 may include the current temperature distribution feature 224, the palletizing feature vector 223, and the environmental feature 225, etc., and the output may be at least one future temperature distribution feature 227 at a future time.

[0069] In some embodiments, the input to the prediction layer 226 further includes a future time sequence, which includes at least one preset future time.

[0070] Environmental characteristic 225 refers to data related to the external environment in which the smart container is located. Environmental characteristics may include transportation mode, transportation vibration level, and the temperature, humidity, altitude, and atmospheric pressure of the current environment in which the container is located. Among these, the transportation mode can be determined by obtaining human input, while the transportation vibration level, temperature, humidity, altitude, and atmospheric pressure can be obtained based on corresponding sensors.

[0071] In some embodiments, the processor can train a prediction model based on a large number of labeled training samples. For example, multiple labeled training samples can be input into an initial prediction model, a loss function can be constructed using the labels and the results of the initial prediction model, and the parameters of the initial prediction model can be iteratively updated based on the loss function using gradient descent or other methods. Model training is complete when preset conditions are met, resulting in a trained prediction model. These preset conditions may include loss function convergence, the number of iterations reaching a threshold, etc.

[0072] In some embodiments, training samples may include a sample stacking pattern design diagram, historical first-time sample temperature distribution characteristics, sample environmental characteristics, and sample stacking feature vectors, as well as historical second-time data. Training samples can be obtained based on historical data.

[0073] In some embodiments, the tag can be a temperature distribution feature at a second historical time, which may include at least one historical moment later than the first historical time. In some embodiments, the tag can be obtained by constructing a temperature distribution feature map based on historical temperature distribution data.

[0074] In some embodiments, the input to the prediction model may also include air quality data 221-2. More information about air quality data and its acquisition can be found in [reference needed]. Figure 4 The relevant description in the document.

[0075] In some embodiments of this specification, the processor also uses air quality data as input to the prediction model, taking into account more factors that may affect the model output, thus improving the accuracy of the model output.

[0076] Some embodiments in this specification predict future temperature distribution characteristics using predictive models, adaptively taking into account the influence of factors such as stacking methods, which can more accurately predict future temperature distribution characteristics and improve computational efficiency.

[0077] In some embodiments, the processor may determine a temperature adjustment scheme 240 based on the future temperature distribution characteristics in response to the future temperature distribution characteristics not meeting the preset temperature condition 230.

[0078] The preset temperature condition 230 can include the condition that the difference between the temperature values ​​of any two temperature regions at any future time is less than a temperature threshold. When the future temperature distribution characteristics do not satisfy the condition that the difference between the temperature values ​​of any two temperature regions is less than the temperature threshold, a temperature adjustment scheme needs to be determined.

[0079] Temperature adjustment plan 240 refers to the operational plan for adjusting the internal temperature of the intelligent container. The temperature adjustment plan may include at least the execution time, the number of exhaust vents to be adjusted and their location distribution, and the opening status of each electrically controlled valve.

[0080] In some embodiments, the processor can determine a temperature adjustment scheme based on a historical temperature adjustment scheme and by looking up a scheme table. The scheme table is constructed based on the temperature adjustment scheme at least once in the past and the future temperature distribution characteristics at least once in the past. The processor can compare the similarity between the future temperature distribution characteristics at the current moment and the future temperature distribution characteristics at least once in the past. When the similarity is greater than a similarity threshold, the historical temperature adjustment scheme corresponding to the future temperature distribution characteristics at least once in the past can be used as the current temperature adjustment scheme. The similarity threshold can be preset manually.

[0081] In some embodiments, the processor can determine a temperature adjustment region based on future temperature distribution characteristics, and then determine a temperature adjustment scheme based on that region. For more related content, please refer to... Figure 3 And its related descriptions.

[0082] In some embodiments, the processor may generate adjustment instructions 250 based on a temperature adjustment scheme, and control the refrigeration device to adjust the temperature inside the smart container based on the adjustment instructions.

[0083] An adjustment command is a command issued by the processor to control the cooling device to adjust the temperature. Adjustment commands can be related to the temperature adjustment scheme; for example, they may include when to start the adjustment, the number and location of the exhaust vents to be adjusted, and the opening status of each electronically controlled valve.

[0084] In some embodiments of this specification, the processor can predict future temperature distribution characteristics based on temperature distribution data using a predictive model, determine a temperature adjustment scheme, and control the refrigeration device to adjust the temperature. This not only allows for the acquisition of real-time temperature data and changes within the smart container but also enables adaptive temperature adjustments based on monitoring data, ensuring a consistently uniform temperature distribution inside the smart container.

[0085] Figure 3 This is a schematic diagram illustrating the determination of a temperature adjustment scheme according to some embodiments of this specification. For example... Figure 3 As shown, the process 300 for determining the temperature adjustment scheme may include the following:

[0086] In some embodiments, the processor may determine a target future time in response to a future temperature distribution feature not meeting a preset temperature condition; determine a temperature adjustment region for the target future time based on the temperature distribution feature at the target future time; and determine a temperature adjustment scheme based on the temperature adjustment region.

[0087] Future temperature distribution characteristic 270 refers to the temperature distribution characteristics inside the smart container at a future point in time. More details on future temperature distribution characteristics can be found in [link to relevant documentation]. Figure 2 And related content.

[0088] The target future time 310 refers to a specific point in the future. For example, a specific future time preset by the user.

[0089] In some embodiments, the processor can select the future moment with the highest confidence level (a higher confidence level than the confidence level threshold) from the future moments in which the temperature distribution characteristics do not meet the preset temperature conditions, and use it as the target future moment.

[0090] In some embodiments, the confidence level can be determined using a preset algorithm based on the time interval between the future and the current time, the complexity of the palletizing method, and the degree of transport vibration. The confidence level is negatively correlated with the time interval between the future and the current time, the complexity of the palletizing method, and the degree of transport vibration; that is, the longer the time interval, the more complex the palletizing method, and the greater the transport vibration, the lower the confidence level. The complexity of the palletizing method can be represented by a value between 1 and 10, with a higher value indicating a more complex palletizing method. The degree of transport vibration can be obtained based on environmental data; for details on environmental data, please refer to [link to relevant documentation]. Figure 2 The relevant description in the document.

[0091] The preset temperature condition 230 is used to determine whether the temperature of the smart container needs to be adjusted. The preset temperature condition includes at least reference thresholds related to the temperature of different temperature zones within the smart container. In some embodiments, different reference thresholds correspond to different goods within the smart container.

[0092] In some embodiments, the processor can extract two indicators based on the predicted temperature distribution characteristics: the cumulative difference between temperature values ​​in multiple temperature regions and the target temperature value, and the standard deviation of temperature values ​​in multiple temperature regions. Then, the two indicators are weighted and summed according to preset weights. If the summation result is greater than a reference threshold, the preset temperature condition is considered not met. The target temperature value refers to the target temperature required for different types of goods, preset in advance based on demand. The aforementioned preset weights can be determined based on prior experience or actual needs.

[0093] The temperature adjustment zone 330 refers to the area where the temperature needs to be adjusted.

[0094] In some embodiments, the processor may designate a region where the temperature value differs from the target temperature by more than a temperature threshold as the temperature adjustment region 330.

[0095] For the area where the temperature needs to be adjusted, the processor can execute a temperature adjustment scheme through a movable second exhaust duct to achieve the purpose of temperature regulation.

[0096] In some embodiments, the processor may determine a temperature adjustment scheme 360 ​​based on the temperature adjustment region 330. The temperature adjustment scheme includes at least one of the following: execution time, number of exhaust vents, location of exhaust vents, and opening degree of electrically controlled valves.

[0097] In some embodiments, the execution time of the scheme can be determined based on the target future time. For example, execution can begin 5 minutes before the target future time. The execution stop time can be determined based on the real-time temperature distribution characteristics within the smart container. For example, real-time temperature distribution characteristics are extracted from the real-time collected temperature distribution data of the smart container, and if the real-time temperature distribution characteristics meet preset temperature conditions, the operation stops. The real-time temperature distribution characteristics can be represented by a real-time temperature distribution characteristic map, and the method for determining the real-time temperature distribution characteristic map can be found in [reference needed]. Figure 3 Description of the temperature distribution characteristic spectrum in the text.

[0098] In some embodiments, the number of exhaust vents can be determined in a variety of feasible ways. For example, the number of exhaust vents can be determined based on the number of temperature-adjustable areas, such as one open exhaust vent for each temperature-adjustable area; or, for another example, the number of exhaust vents can be determined based on the difference between the temperature value of the temperature-adjustable area and the target temperature, with a larger difference being allocated more exhaust vents to that temperature-adjustable area.

[0099] In some embodiments, the location of the exhaust vent can be determined in the middle of the area where the temperature is to be adjusted. For example, the location of the exhaust vent can be determined at the center of the planar projection of the area where the temperature is to be adjusted. The projection center can be determined based on planar coordinates, for example, by establishing a Cartesian coordinate system with any point on the edge of the area where the temperature is to be adjusted as the origin, and determining the projection center based on this Cartesian coordinate system.

[0100] In some embodiments, the opening degree of the electrically controlled valve can be preset. For example, the processor can determine the opening degree of the electrically controlled valve based on historical data, combined with the current target temperature value and the number of exhaust vents.

[0101] During the cooling process inside the smart container, if the input of cooling air is unrestricted, the larger the opening of the electrically controlled valves, the more cooling air can pass through, and the better the cooling effect. However, in actual cooling, the amount of cooling air from the refrigeration unit is limited. When adjusting the temperature inside the smart container through the second exhaust duct, the cooling air goes to the main duct and at least one sub-duct. If the opening of the electrically controlled valves is not controlled, the ducts far from the refrigeration unit may face insufficient cooling air, affecting the cooling effect. Therefore, it is necessary to reasonably regulate the opening of the electrically controlled valves.

[0102] In some embodiments, the opening degree of the primary electrically controlled valve is related to the cumulative difference between multiple zone temperature values ​​and the target temperature value; the greater the cumulative difference, the greater the valve opening degree of the primary electrically controlled valve. Consequently, more cooling air is delivered to the housing through the main pipeline, resulting in a better cooling effect.

[0103] In some embodiments, the opening degree of the secondary electrically controlled valve is related to the rate of temperature change in the area where the exhaust vent is located; the faster the temperature changes, the larger the opening degree of the secondary electrically controlled valve. The rate of temperature change refers to the amount of temperature change per unit time.

[0104] In some embodiments, the rate of temperature change can be determined based on the historical temperatures of the region to be adjusted. For example, taking region A to be adjusted as an example, the historical temperatures corresponding to multiple historical times prior to the current time are obtained, a temperature change image is determined based on the historical temperatures corresponding to the multiple historical times, and the rate of temperature change is determined based on the average slope of the image corresponding to at least one time in the temperature change image.

[0105] In some embodiments of this specification, by reasonably configuring the opening degrees of the primary and secondary electrically controlled valves, it is beneficial to rationally distribute the cooling air produced by the refrigeration unit, making the distribution of cooling air more reasonable, thereby ensuring the supply of cooling air to each temperature-adjustable zone, and thus obtaining a better cooling effect.

[0106] In some embodiments of this specification, by determining the temperature adjustment area at a target future time, and using movable distributed air supply ducts to process the temperature adjustment area, the temperature can be adjusted in a targeted manner, by region and by situation, for areas that are not within the preset temperature range. This is more accurate and helps to efficiently control the temperature of the smart container within the target range.

[0107] It should be noted that the above description of the schematic diagram for determining the temperature adjustment scheme is for illustrative purposes only and does not limit the scope of this specification. Those skilled in the art can make various modifications and changes to the schematic diagram for determining the temperature adjustment scheme under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

[0108] Figure 4 These are schematic diagrams illustrating the performance of ventilation operations according to some embodiments of this specification. For example... Figure 4 As shown, the process of performing the ventilation operation 400 includes at least the following:

[0109] In some embodiments, in response to the state 410 of the smart container satisfying a first preset condition 420, the processor generates an initial ventilation command 430 and controls the air conditioning unit to perform an initial ventilation operation based on the initial ventilation command 430; in response to the state of the smart container satisfying a second preset condition 440, the processor acquires air quality data 460 through an air quality monitoring device; in response to the air quality data satisfying a first air quality condition 470-1, the processor generates a ventilation command 480 and controls the air conditioning unit to perform a ventilation operation based on the ventilation command; in response to the air quality data satisfying a second air quality condition 470-2, the processor generates a ventilation stop command 490 and controls the air conditioning unit to stop the ventilation operation based on the ventilation stop command.

[0110] The first preset condition 420 may include whether the smart container has been sealed. Once the smart container has been sealed, the processor can determine that the state 410 of the smart container meets the first preset condition.

[0111] When the state of the smart container meets the first preset condition, the processor can generate an initial ventilation command and control the air conditioning compartment to perform ventilation operation based on the initial ventilation command.

[0112] The initial ventilation command 430 refers to the command to perform the initial ventilation of the sealed smart container. The initial activation command may include the initial ventilation time, which can be preset based on historical experience.

[0113] The processor can send an initial ventilation command to the air conditioning chamber, controlling it to start operating. The incoming air is then processed into nitrogen-rich air by a membrane separator within the chamber, creating a low-oxygen environment. This low-oxygen environment helps preserve goods and reduces oxidation.

[0114] For more information on the ventilation process, please refer to this instruction manual. Figure 1 The relevant description in the document.

[0115] The second preset condition 450 may include whether the initial ventilation operation has been completed. In response to the completion of the initial ventilation operation, the processor can determine that the state 410 of the smart container meets the second preset condition.

[0116] When the state of the smart container meets the second preset condition, the processor can obtain air quality data through the air quality monitoring device.

[0117] Air Quality Data 460 refers to the concentration of various components in the air. For more information on Air Quality Data 460 and how it is obtained, please refer to [link to relevant documentation]. Figure 2 The relevant description in the document.

[0118] In some embodiments, when the air quality data meets the first air quality condition 470-1, the processor generates a ventilation command and controls the air conditioning unit to perform a ventilation operation based on the ventilation command.

[0119] The first air quality condition 470-11 is related to the concentration of each component in the air quality data. In some embodiments, the first air quality condition 470-1 includes whether the combined value of the air component concentrations exceeds a first threshold; if it is not less than the first threshold, the first air quality condition is met.

[0120] The composite value can be determined by weighted summation based on the concentrations of each component in the air quality data. The weights can be set based on historical experience, for example, carbon dioxide concentration and oxygen concentration have greater weights.

[0121] The first threshold can be determined based on historical experience; different types of goods correspond to different first thresholds.

[0122] Ventilation command 480 refers to the command to ventilate the smart container in operation.

[0123] In some embodiments, the ventilation command 480 controls the air conditioning compartment 440 to perform a ventilation operation, which includes at least opening the second and third electrically controlled valves and starting the intake fan to perform ventilation.

[0124] In some embodiments, when the air quality data meets the second air quality condition 470-2, the processor generates a ventilation stop command and controls the air conditioning unit to stop the ventilation operation based on the ventilation stop command.

[0125] The second air quality condition 470-2 is related to the concentration of each component in the air quality data. In some embodiments, the second air quality condition 470-2 includes whether the aforementioned composite value is less than a second threshold; if it is less than the second threshold, the second air quality condition is met.

[0126] The second threshold can be determined based on historical experience; different types of goods correspond to different second thresholds.

[0127] The ventilation stop command 490 is a command to stop the ventilation operation.

[0128] In some embodiments, in response to air quality data 460 satisfying a second air quality condition 470-22, the processor generates a ventilation stop command 490, and controls the air conditioning unit to stop ventilation operation based on the ventilation stop command.

[0129] Some embodiments in this specification, by setting multiple air quality conditions for initial ventilation, ventilation, and ventilation cessation operations, can accurately control the gas concentration range, making it more intelligent and economical. The multi-layer electronically controlled valve design not only improves sealing and prevents gas backflow but also provides different countermeasures for various temperatures, which helps save resources.

[0130] Figure 5 This is an exemplary block diagram of an intelligent container control system according to some embodiments of this specification.

[0131] like Figure 5 As shown, in some embodiments, the intelligent container control system 100 may include an acquisition module 510 and a control module 520.

[0132] In some embodiments, the acquisition module 510 can acquire monitoring data of the smart container based on the thermal imaging device and air quality detection device in the smart container.

[0133] In some embodiments, the control module 520 can adjust the internal environment of the smart container based on monitoring data, the internal environment including at least temperature and / or air quality.

[0134] In some embodiments, the control module 520 is further configured to control the refrigeration device to execute a temperature adjustment scheme based on a temperature adjustment command.

[0135] In some embodiments, the control module 520 is further configured to extract the temperature distribution characteristics at the current moment based on the temperature distribution data of the smart container; predict the future temperature distribution characteristics based on the temperature distribution characteristics; determine a temperature adjustment scheme based on the future temperature distribution characteristics in response to the future temperature distribution characteristics not meeting the preset temperature conditions; generate an adjustment command based on the temperature adjustment scheme; and control the refrigeration device to adjust the temperature inside the smart container based on the adjustment command.

[0136] In some embodiments, the control module 520 is further configured to, in response to the future temperature distribution characteristics not meeting the preset temperature conditions, determine a target future time; based on the temperature distribution characteristics of the target future time, determine a temperature adjustment area for the target future time; and based on the temperature adjustment area, determine a temperature adjustment scheme, wherein the temperature adjustment scheme includes at least one of execution time, number of exhaust vents, location of exhaust vents, and opening degree of electrically controlled valves.

[0137] In some embodiments, the control module 520 is further configured to: generate an initial ventilation command in response to the state of the smart container meeting a first preset condition; control the air conditioning compartment to perform an initial ventilation operation based on the initial ventilation command; acquire air quality data through an air quality monitoring device in response to the state of the smart container meeting a second preset condition; generate a ventilation command in response to the air quality data meeting a first air quality condition; control the air conditioning compartment to perform a ventilation operation based on the ventilation command; and generate a ventilation stop command in response to the air quality data meeting a second air quality condition; control the air conditioning compartment to stop the ventilation operation based on the ventilation stop command.

[0138] For further explanation of the functions of the aforementioned acquisition and control modules, please refer to this manual. Figures 2-3 And its related descriptions.

[0139] It should be understood that Figure 5 The system and its modules shown can be implemented in various ways.

[0140] It should be noted that the above description of the intelligent container control system and its modules is for convenience only and should not be construed as limiting this specification to the embodiments described. It is understood that those skilled in the art, after understanding the principles of the system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from these principles. In some embodiments, Figure 5 The acquisition module and control module disclosed in the document can be different modules in a system, or a single module can implement the functions of two or more of the above modules.

[0141] The basic concepts have been described above. Obviously, for those skilled in the art, the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0142] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0143] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0144] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0145] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0146] For each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, and documents, referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0147] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A smart container, characterized in that, Includes the enclosure, refrigeration unit, thermal imaging unit, air quality detection unit, air conditioning unit, and processor; The enclosure includes at least a floor and an air vent. The floor is a T-shaped panel. The air vent is equipped with a one-way pressure valve and a first electrically controlled valve. The opening and closing of the first electrically controlled valve is used to control whether the air inside the enclosure is discharged to the outside. The refrigeration unit includes at least an air inlet duct, an air outlet duct, and a refrigeration unit; An air-conditioned compartment includes at least an air conditioning unit, an air intake duct, an air intake fan, and a conveying duct; The air intake channel is equipped with a second electrically controlled valve, the opening and closing of which is used to control whether air is supplied into the chamber; The conveying channel is connected to the air inlet channel of the refrigeration unit, and the conveying channel is equipped with a third electrically controlled valve. The processor is configured as follows: Temperature distribution data of the smart container is obtained based on a thermal imaging device, and air quality data of the smart container is obtained based on an air quality detection device. The internal environment of the smart container is adjusted based on temperature distribution data and / or air quality data, including temperature and / or air quality; wherein, adjusting the temperature of the smart container includes: Based on temperature distribution data, the temperature distribution characteristics at the current moment are extracted, and the temperature distribution characteristics are represented by a temperature distribution feature map. Based on temperature distribution characteristics, a prediction model is used to predict future temperature distribution characteristics, including temperature distribution at future times. The prediction model includes a feature extraction layer and a prediction layer. The input of the feature extraction layer includes a palletizing method design diagram and air quality data, and the output includes a palletizing feature vector. The input of the prediction layer includes the temperature distribution characteristics at the current moment, the palletizing feature vector, and environmental characteristics, and the output includes the future temperature distribution characteristics at at least one future moment. In response to the fact that the future temperature distribution characteristics do not meet the preset temperature conditions, a temperature adjustment scheme is determined based on the future temperature distribution characteristics. Generate adjustment instructions based on the temperature adjustment scheme; Based on the adjustment instructions, the refrigeration unit is controlled to adjust the temperature inside the smart container.

2. The intelligent container as claimed in claim 1, characterized in that, The exhaust duct of the refrigeration unit includes a first exhaust duct and a second exhaust duct; The first and second exhaust ducts are installed side by side; The second exhaust duct is a distributed exhaust channel, including a main duct and sub-ducts; The main pipe and sub-pipes are located in the pipe storage layer, which is situated below the T-shaped plate. The T-shaped panel is equipped with an adjustable exhaust vent, and the duct storage layer is connected to the T-shaped panel through the exhaust vent.

3. The intelligent container as claimed in claim 1, characterized in that, The processor is further used for: In response to the future temperature distribution characteristics not meeting the preset temperature conditions, the target future time is determined; Based on the temperature distribution characteristics of the target at future time, determine the temperature adjustment area of ​​the target at future time; Based on the temperature to be adjusted area, a temperature adjustment plan is determined. The temperature adjustment plan includes at least one of the following: execution time, number of exhaust vents, location of exhaust vents, and opening degree of electrically controlled valves.

4. The intelligent container as claimed in claim 1, characterized in that, The processor is also used for: In response to the smart container meeting the first preset condition, an initial ventilation command is generated, and the air conditioning compartment is controlled to perform an initial ventilation operation based on the initial ventilation command. In response to the smart container meeting the second preset condition, air quality data is acquired through an air quality monitoring device. In response to the air quality data meeting the first air quality condition, a ventilation command is generated, and the air conditioning unit is controlled to perform a ventilation operation based on the ventilation command. The ventilation operation includes at least opening the second and third electrically controlled valves and starting the intake fan. In response to the air quality data meeting the second air quality condition, a ventilation stop command is generated, and the air conditioning unit is controlled to stop ventilation operation based on the ventilation stop command.

5. An intelligent container control system, characterized in that, Includes an acquisition module and a control module; The acquisition module is used to acquire monitoring data of the smart container based on the thermal imaging device and air quality detection device in the smart container; The control module is used to adjust the internal environment of the smart container based on temperature distribution data and / or air quality data, including temperature and / or air quality; wherein, adjusting the temperature of the smart container includes: Based on temperature distribution data, the temperature distribution characteristics at the current moment are extracted, and the temperature distribution characteristics are represented by a temperature distribution feature map. Based on temperature distribution characteristics, a prediction model is used to predict future temperature distribution characteristics, including temperature distribution at future times. The prediction model includes a feature extraction layer and a prediction layer. The input of the feature extraction layer includes a palletizing method design diagram and air quality data, and the output includes a palletizing feature vector. The input of the prediction layer includes the temperature distribution characteristics at the current moment, the palletizing feature vector, and environmental characteristics, and the output includes the future temperature distribution characteristics at at least one future moment. In response to the fact that the future temperature distribution characteristics do not meet the preset temperature conditions, a temperature adjustment scheme is determined based on the future temperature distribution characteristics. Generate adjustment instructions based on the temperature adjustment scheme; Based on the adjustment instructions, the refrigeration unit is controlled to adjust the temperature inside the smart container.

6. The intelligent container control system as described in claim 5, characterized in that, The control module is also used for: Based on the temperature adjustment command, the refrigeration unit is controlled to execute the temperature adjustment scheme.

7. The intelligent container control system as described in claim 5, characterized in that, The control module is further used for: In response to the future temperature distribution characteristics not meeting the preset temperature conditions, the target future time is determined; Based on the temperature distribution characteristics of the target at future time, determine the temperature adjustment area of ​​the target at future time; Based on the temperature to be adjusted area, a temperature adjustment plan is determined. The temperature adjustment plan includes at least one of the following: execution time, number of exhaust vents, location of exhaust vents, and opening degree of electrically controlled valves.

8. The intelligent container control system as described in claim 5, characterized in that, The control module is also used for: In response to the smart container meeting the first preset condition, an initial ventilation command is generated, and the air conditioning compartment is controlled to perform an initial ventilation operation based on the initial ventilation command. In response to the smart container meeting the second preset condition, air quality data is acquired through an air quality monitoring device. In response to the air quality data meeting the first air quality condition, a ventilation command is generated, and the air conditioning unit is controlled to perform a ventilation operation based on the ventilation command. In response to the air quality data meeting the second air quality condition, a ventilation stop command is generated, and the air conditioning unit is controlled to stop ventilation operation based on the ventilation stop command.

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