Intelligent packaging fresh-keeping control method and system

Abstract

The application discloses an intelligent packaging preservation control method and system, relates to the field of intelligent packaging preservation control, and is used for ensuring the safety of goods and the authenticity of data under a complex transportation environment and comprises the following steps: collecting environment parameter data of sensitive sensors and stable sensors in an intelligent packaging box; identifying reading abnormity of the sensitive sensors; acquiring readings of the stable sensors when the reading abnormity of the sensitive sensors is identified; judging whether the reading abnormity of the sensitive sensors is an illusion caused by mechanical vibration or real environment change of goods according to the readings of the sensitive sensors and the readings of the stable sensors; if the reading abnormity of the sensitive sensors is judged to be the illusion caused by the mechanical vibration, then preservation intervention on the intelligent packaging box is inhibited; and if the reading abnormity of the sensitive sensors is judged to be the real environment change of the goods, then preservation intervention on the intelligent packaging box is executed.

Description

Technical Field

[0001] This invention relates to the field of intelligent packaging preservation control, and in particular to an intelligent packaging preservation control method and system. Background Technology

[0002] In modern logistics systems, environmental control requirements are extremely stringent for high-value, time-sensitive biological agents during transportation. To meet these needs, a highly intelligent transport packaging box has emerged. This box is designed as an edge node in the cold chain network, capable of sensing the environment, making autonomous decisions, and executing corresponding operations. They typically incorporate multiple high-precision sensors, such as temperature and humidity sensors, as well as wireless communication modules for data transmission and active preservation elements, such as semiconductor cooling chips or gas management systems. Under normal circumstances, these intelligent boxes periodically collect internal environmental data according to a preset strategy and report it to a central monitoring platform via the network. Simultaneously, they actively control the internal environment as needed to ensure the goods are always stored under optimal conditions.

[0003] However, when the sensitive sensors inside the cargo generate instantaneous signal anomalies (such as noise or drift) under continuous high-intensity mechanical vibration and impact, how to design a data reporting and preservation collaborative control method that can effectively identify and distinguish these illusions caused by physical interference from changes in the cargo's actual environment, thereby avoiding unnecessary preservation interventions and misleading alarms based on inaccurate information, and ensuring the safety of cargo and the authenticity of data in complex transportation environments, is an urgent technical problem to be solved. Summary of the Invention

[0004] This invention provides an intelligent packaging preservation control method to ensure the safety of goods and the authenticity of data in complex transportation environments.

[0005] In a first aspect, to address the aforementioned technical problems, this invention provides an intelligent packaging preservation control method, comprising: collecting environmental parameter data from a sensitive sensor and a stable sensor inside an intelligent packaging box; the sensitive sensor is a sensor sensitive to mechanical vibration; the stable sensor is a sensor insensitive to mechanical vibration; identifying abnormal readings of the sensitive sensor, including readings exceeding a preset threshold or rapid fluctuations in readings; rapid fluctuations refer to fluctuations in reading amplitude exceeding a fluctuation amplitude threshold within a preset time period; acquiring the reading of the stable sensor when an abnormal reading of the sensitive sensor is detected; determining, based on the readings of the sensitive sensor and the stable sensor, whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment; wherein, if the reading of the sensitive sensor is abnormal and the reading of the stable sensor remains stable, it is determined to be a false alarm caused by mechanical vibration; if the reading of the sensitive sensor is abnormal and the reading of the stable sensor fluctuates synchronously, it is determined to be a real change in the cargo's environment; if it is determined to be a false alarm caused by mechanical vibration, then suppressing preservation intervention on the intelligent packaging box; if it is determined to be a real change in the cargo's environment, then executing preservation intervention on the intelligent packaging box.

[0006] Optionally, based on the readings of the sensitive sensor and the stable sensor, determine whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment. This includes: analyzing the readings of the sensitive sensor to identify its vibration interference characteristics; analyzing the readings of the stable sensor to identify its periodic fluctuation characteristics; and determining whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment based on the readings of the sensitive sensor, the stable sensor, the vibration interference characteristics of the sensitive sensor, and the periodic fluctuation characteristics of the stable sensor. Specifically, if the reading of the sensitive sensor is abnormal, but the reading of the stable sensor remains stable, it is determined to be a false alarm caused by mechanical vibration. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the sensitive sensor displays vibration interference characteristics while the stable sensor simultaneously displays periodic fluctuation characteristics, then the abnormal reading of the sensitive sensor is determined to be a false alarm caused by combined interference. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the stable sensor displays non-periodic continuous fluctuations, then the abnormal reading of the sensitive sensor is determined to be a real change in the cargo's environment.

[0007] Optionally, the readings of the stable sensor are analyzed to identify the periodic fluctuation characteristics of the stable sensor, including: identifying extreme points in the reading sequence of the stable sensor; the extreme points are peak points or valley points; calculating the time interval between extreme points; if the distribution characteristics of the time intervals show that there are one or more concentrated intervals, and the number of intervals in the concentrated intervals reaches a preset proportion, then the periodic fluctuation characteristics of the stable sensor are identified.

[0008] Optionally, the readings of the sensitive sensor are analyzed to identify the vibration interference characteristics of the sensitive sensor, including: acquiring the reading sequence of the sensitive sensor within a preset time window; calculating the fluctuation amplitude of the reading sequence based on the reading sequence, the fluctuation amplitude reflecting the overall deviation of the reading sequence; calculating the instantaneous rate of change of the reading sequence based on the reading sequence, the instantaneous rate of change reflecting the intensity of continuous change of the reading sequence; if the fluctuation amplitude exceeds a preset first threshold and the instantaneous rate of change exceeds a preset second threshold, then the sensitive sensor is identified as exhibiting vibration interference characteristics.

[0009] Optionally, calculating the fluctuation amplitude of the reading sequence includes: dividing a preset time window into multiple sub-time windows; calculating the fluctuation amplitude of the reading sequence within each sub-time window; and obtaining the maximum value from the fluctuation amplitudes of the multiple sub-time windows as the fluctuation amplitude of the reading sequence.

[0010] Optionally, for the reading sequence within each sub-time window, the fluctuation amplitude is calculated, including: calculating the statistical dispersion of the reading sequence within the sub-time window, and using the statistical dispersion as the fluctuation amplitude of the reading sequence within the sub-time window.

[0011] Optionally, calculating the instantaneous rate of change of the reading sequence includes: acquiring the data of the reading sequence within a preset sliding window; calculating the difference between adjacent readings within the sliding window based on the data within the sliding window, obtaining multiple differences; calculating the statistics of the multiple differences, and using the statistics as the instantaneous rate of change; the statistics are one of the following: median, truncated mean, interquartile range.

[0012] Optionally, the method further includes: obtaining the type of judgment result based on the judgment result; if the type of judgment result is an artifact caused by mechanical vibration or an artifact caused by compound interference, determining the degree of influence of the artifact based on the fluctuation amplitude of the reading sequence of the sensitive sensor; if the type of judgment result is a change in the actual environment of the goods, determining the degree of change in the actual environment of the goods based on the fluctuation amplitude of the reading sequence of the stable sensor; constructing a quality mark, the quality mark including an indication of the type of judgment result and an indication of the degree of influence of the artifact or an indication of the degree of change in the actual environment of the goods; attaching the quality mark to the reading of the sensitive sensor, and reporting the reading and the quality mark to the remote monitoring platform.

[0013] Optionally, the degree of influence of the artifact is determined, including: monitoring the duration of vibration interference characteristics displayed by the sensitive sensor; monitoring the frequency of vibration interference characteristics displayed by the sensitive sensor; determining the level of the artifact based on the fluctuation amplitude, duration, frequency of occurrence, and level mapping relationship of the reading sequence of the sensitive sensor, and determining the level of the artifact as the degree of influence of the artifact; the level mapping relationship includes the mapping relationship between different fluctuation amplitudes, different durations, different frequencies of occurrence, and different levels.

[0014] Secondly, this invention provides an intelligent packaging preservation control system for intelligent packaging boxes, the intelligent packaging boxes including sensitive sensors and stable sensors, the system comprising: The data acquisition module is used to collect environmental parameter data from sensitive and stable sensors inside the smart packaging box; the sensitive sensors are those that are sensitive to mechanical vibration; the stable sensors are those that are not sensitive to mechanical vibration. The anomaly detection module is used to identify reading anomalies of sensitive sensors. Reading anomalies include readings exceeding preset thresholds or readings exhibiting rapid fluctuations. Rapid fluctuations refer to readings fluctuating more than a fluctuation amplitude threshold within a preset time period. The auxiliary data acquisition module is used to acquire the readings of the stable sensor when an abnormal reading of the sensitive sensor is detected. The judgment module is used to determine whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment, based on the readings of the sensitive sensor and the stable sensor. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration; if the reading of the sensitive sensor is abnormal, while the reading of the stable sensor fluctuates synchronously, it is determined to be a change in the actual environment of the goods. An intervention suppression module is used to suppress the preservation intervention of the smart packaging box if the phenomenon is determined to be caused by mechanical vibration. The intervention execution module is used to perform preservation intervention on the smart packaging box if it is determined that there is a real change in the goods' environment.

[0015] Compared with the prior art, the present invention has the following beneficial effects: This application provides an intelligent packaging preservation control method that effectively solves the problem in existing technologies where intelligent packaging boxes misjudge changes in the actual environment of goods due to abnormal readings of sensitive sensors in complex mechanical vibration environments by introducing a collaborative working mechanism between sensitive and stable sensors. Specifically, when an abnormal reading of a sensitive sensor is detected, the method obtains the reading of a stable sensor as a reference and, based on the linkage between the two readings, accurately determines whether the abnormality is a false alarm caused by mechanical vibration or a real change in the goods' environment. If it is determined to be a false alarm caused by mechanical vibration, unnecessary preservation interventions are suppressed; if it is determined to be a real change in the goods' environment, corresponding preservation interventions are executed. Accordingly, this application can significantly improve the accuracy of intelligent packaging boxes in judging environmental changes, avoid triggering unnecessary preservation measures due to misjudgments, thereby effectively saving energy and preservation consumables and reducing operating costs. At the same time, by avoiding false alarms, the frequency of receiving misleading alarms by logistics managers and quality control personnel is reduced, improving the accuracy and efficiency of decision-making, and ultimately effectively avoiding unnecessary resource waste and potential economic losses, demonstrating significant practical value and economic benefits. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of a smart packaging preservation control method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of another intelligent packaging preservation control method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of an intelligent packaging and preservation control system provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0018] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0019] The following specific embodiments will provide a detailed description and explanation of an intelligent packaging preservation control method provided in this application.

[0020] Reference Figure 1 This invention provides an intelligent packaging preservation control method, comprising the following steps: S1 collects environmental parameter data from sensitive and stable sensors inside the smart packaging box; The environmental parameters may include, but are not limited to, temperature, humidity, oxygen concentration, carbon dioxide concentration, and volatile organic compound (VOC) concentration. Among them, sensitive sensors are those that are sensitive to mechanical vibration; stable sensors are those that are not sensitive to mechanical vibration. For example, sensitive sensors can be electrochemical sensors used to monitor oxygen, carbon dioxide, or volatile organic compounds (VOCs), or certain types of optical sensors. When these sensors are subjected to vibration, their internal sensitive elements or optical paths may experience slight disturbances, resulting in unstable output signals. Stable sensors can be resistance thermometers (RTDs) or thermistors used to monitor temperature, or certain types of humidity sensors. These sensors typically have a more robust structure or a more stable measurement principle, making them less susceptible to mechanical vibration.

[0021] As one possible implementation, the system can acquire temperature and humidity data inside the smart packaging box through stable sensors, and acquire oxygen concentration and volatile organic compound data inside the smart packaging box through sensitive sensors, thereby obtaining environmental parameter data inside the smart packaging box.

[0022] Data acquisition can be achieved in a variety of ways. For example, sensors can be programmed to periodically send readings to the control unit of the smart packaging box at preset time intervals (e.g., every 1 minute, 5 minutes, or 10 minutes).

[0023] As another implementation, the sensor can also be configured to trigger data acquisition and reporting when a significant change in environmental parameters is detected. The acquired data can be stored in the control unit's local memory for subsequent processing and analysis.

[0024] S2. Identify abnormal readings from sensitive sensors; Abnormal readings include readings exceeding preset thresholds or readings exhibiting rapid fluctuations; rapid fluctuations refer to readings whose fluctuation amplitude within a preset time period exceeds the fluctuation amplitude threshold. As one possible implementation, the system could have a microcontroller continuously monitor the real-time readings of all "sensitive sensors" and calculate the absolute difference between the current sampling point and the previous sampling point. If this difference exceeds a preset "fluctuation threshold," i.e., |current reading - previous reading| > fluctuation threshold, then a rapid fluctuation is considered to exist, thereby identifying an abnormal reading of the sensitive sensor. In one example, when the current reading of any "sensitive sensor" exceeds a preset safety threshold (e.g., oxygen concentration is higher than 2.5%), or when its value fluctuates abnormally rapidly in a very short period of time, the system will initially mark it as "abnormal reading of sensitive sensor". In one example, for an oxygen sensor, a rapid fluctuation is considered to exist if the difference between two consecutive readings exceeds 0.1%.

[0025] S3. When an abnormal reading is detected in the sensitive sensor, obtain the reading of the stable sensor; As one possible implementation, the system can immediately trigger the acquisition of readings from the stable sensor when the reading of the sensitive sensor is identified as abnormal, or obtain the reading of the stable sensor from the most recent historical readings of the stable sensor; For example, if the sensitive sensor collects data every 10 seconds and the stable sensor collects data every 30 seconds, when the sensitive sensor malfunctions, the system can immediately request the stable sensor to collect additional data, or directly use the most recently collected data from the stable sensor.

[0026] S4. Based on the readings of the sensitive sensor and the stable sensor, determine whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration; if the reading of the sensitive sensor is abnormal, while the reading of the stable sensor fluctuates synchronously, it is determined to be a change in the actual environment of the goods. As one possible implementation, in the first scenario, if the reading of the sensitive sensor is abnormal while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration. In this case, since the reading of the stable sensor (e.g., a temperature sensor) does not change significantly, it indicates that the actual environment (e.g., temperature) inside the smart packaging box is stable. Therefore, the abnormal reading of the sensitive sensor is likely caused by external mechanical vibration interfering with its sensitive element, rather than a change in the actual environment of the goods. For example, if the oxygen sensor reading fluctuates drastically when the smart packaging box is bumped during transportation, but the temperature sensor reading remains unchanged, it can be inferred that the abnormal oxygen reading is a false alarm. As another possible implementation, in the second scenario, if the readings of the sensitive sensor are abnormal and the readings of the stable sensor fluctuate synchronously, it is determined that the actual environment of the goods has changed. In this case, both the readings of the sensitive and stable sensors show synchronous abnormal fluctuations, indicating that the actual environment inside the smart packaging box may indeed have changed, such as a simultaneous increase or decrease in temperature and oxygen concentration. This is usually caused by changes in the external environment or a malfunction in the internal preservation system of the packaging box.

[0027] For example, when a smart packaging box is placed in a high-temperature environment, the temperature sensor reading rises, and at the same time, the oxygen sensor reading also changes due to the temperature rise, which can be judged as a real change in the environment of the goods.

[0028] As another possible implementation, the system can determine whether the abnormal readings of the sensitive sensor are a false alarm caused by mechanical vibration or a real change in the cargo's environment based on the following steps: S41. Analyze the readings of the sensitive sensor and identify the vibration interference characteristics of the sensitive sensor.

[0029] As one possible implementation, the system can analyze the reading sequences of sensitive sensors to extract specific patterns or indicators that can characterize the impact of mechanical vibration, and use these specific patterns or indicators as vibration interference features. For example, vibration interference characteristics can manifest as rapid, high-frequency, irregular fluctuations in the reading sequence, or large instantaneous changes within a short period of time. The aim is to more accurately confirm whether abnormal readings of sensitive sensors are indeed caused by mechanical vibration.

[0030] S42. Analyze the readings of the stable sensor and identify the periodic fluctuation characteristics of the stable sensor; Analyzing the readings of stable sensors and identifying their periodic fluctuation characteristics involves analyzing the reading sequences of stable sensors to identify regular, recurring fluctuation patterns. These periodic fluctuations may originate from engine vibrations in the transport vehicle, periodic bumps during vehicle operation, or the cyclical operation of the cooling / heating system inside the smart packaging box. These fluctuations typically do not represent a deterioration in the actual environment of the goods. The purpose is to distinguish between background noise or non-critical periodic disturbances and genuine environmental changes.

[0031] S43. Based on the readings of the sensitive sensor, the readings of the stable sensor, the vibration interference characteristics of the sensitive sensor, and the periodic fluctuation characteristics of the stable sensor, determine whether the abnormal reading of the sensitive sensor is a false image caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the sensitive sensor shows vibration interference characteristics, and the stable sensor shows periodic fluctuation characteristics at the same time, then the abnormal reading of the sensitive sensor is judged to be an illusion caused by composite interference. In this case, although both sensors fluctuate, the fluctuations have specific vibration and periodic characteristics, indicating that this is not a deterioration of the actual environment of the cargo, but the result of the combined effect of mechanical vibration and some periodic background interference. If the reading of the sensitive sensor is abnormal and the reading of the stable sensor fluctuates synchronously, and the stable sensor shows non-periodic continuous fluctuation, then the abnormal reading of the sensitive sensor is determined to be a change in the actual environment of the goods. Understandably, the above technical solution enables more accurate identification and differentiation of sensor reading anomalies caused by mechanical vibration, combined interference, and changes in the actual environment of the goods. This significantly improves the accuracy of judgment, effectively avoids invalid or unnecessary preservation interventions due to misjudgment, thereby reducing operating costs, extending the lifespan of preservation equipment, and ensuring the timeliness and effectiveness of goods preservation.

[0032] S5. If the phenomenon is determined to be caused by mechanical vibration, then suppress the intervention on the preservation of the smart packaging box. As one possible implementation, the system can stop any unnecessary preservation measures to suppress interference with the preservation of the smart packaging box; For example, inert gas will not be injected, and refrigeration or heating devices will not be activated. This suppression mechanism avoids energy waste and unnecessary interference with cargo caused by misjudgment.

[0033] S6. If it is determined that there is a real change in the environment of the goods, then implement the preservation intervention on the smart packaging box; As one possible implementation, the system can activate corresponding preservation measures based on a preset preservation strategy; For example, activating the gas management system to regulate the gas composition inside the container, or activating the refrigeration / heating device to regulate the temperature inside the container, thereby ensuring that the goods are in optimal storage conditions and preventing them from deteriorating or being damaged.

[0034] In some preferred embodiments, a specific example is given below. Suppose a smart packaging box is transporting a batch of medicines that are sensitive to temperature and humidity.

[0035] In one scenario, the reading of a sensitive temperature sensor suddenly exhibits rapid, irregular fluctuations, while the reading of a stable temperature sensor remains stable. By analyzing the reading of the sensitive temperature sensor, the system identifies typical vibration interference characteristics (e.g., high-frequency, high-amplitude transient jumps). Because the stable temperature sensor reading remains stable, the system determines that the anomaly is a glitch caused by mechanical vibration, thus suppressing any temperature regulation intervention on the packaging box.

[0036] In another scenario, both the sensitive and stable temperature sensor readings exhibited synchronized fluctuations. Further system analysis revealed that the fluctuations in the sensitive temperature sensor contained significant vibration interference characteristics (e.g., sharp peaks and troughs), while the fluctuations in the stable temperature sensor displayed periodic fluctuation characteristics (e.g., small, regular rises and falls at fixed intervals, possibly caused by the cyclical operation of the transport vehicle's air conditioning system). In this case, the system determined that the abnormal readings were a spurious sign caused by combined interference, thus suppressing unnecessary preservation interventions and avoiding misjudgments caused by the superposition of background noise and vibration.

[0037] In another scenario, the readings of both the sensitive and stable temperature sensors exhibited synchronized fluctuations. System analysis revealed that the stable temperature sensor readings displayed non-periodic, continuous fluctuations (e.g., a sustained, slow temperature increase without a clear periodic pattern). In this case, the system determined that the anomaly represented a change in the actual environment of the goods and immediately implemented preservation interventions, such as activating the cooling system within the packaging box to protect the quality of the medicine.

[0038] Understandably, through this dual-sensor collaborative judgment mechanism, the method of this application can accurately distinguish between external physical interference and internal environmental changes, thereby avoiding over-intervention or under-intervention caused by misjudgment in traditional solutions, and significantly improving the accuracy and efficiency of intelligent packaging preservation control. The various modules work closely together to form a closed-loop intelligent judgment and control system, ensuring the reliability of goods preservation in dynamic and complex logistics environments.

[0039] In one possible design, such as Figure 2 As shown, in order to analyze the readings of a stable sensor and identify the periodic fluctuation characteristics of the stable sensor, this application may further include the following steps: S101. Identify extreme points in the reading sequence of the stable sensor; Among them, extreme points are either peak points or valley points; As one possible implementation, the system can employ peak-valley detection algorithms from signal processing, such as methods based on derivatives, sliding window maximum / minimum values, or local regression, to identify extreme points in the reading sequences of stable sensors.

[0040] S102, Calculate the time interval between extreme points; As one possible implementation, the system can calculate the time interval between consecutive peak points as the time interval between extreme points; Alternatively, the system can calculate the time interval between consecutive valley points as the time interval between extreme points.

[0041] S103. If the distribution characteristics of the time interval show that there are one or more concentrated intervals, and the number of intervals in the concentrated intervals reaches a preset proportion, then the periodic fluctuation characteristics of the stable sensor are identified. As one possible implementation, the system can construct a histogram of time intervals to observe whether there are obvious peak intervals. If the number of intervals within the peak interval reaches a preset proportion, it indicates that the time interval is repeated, thus indicating the periodicity of the readings. The preset ratio can be set according to the actual application scenario and the required periodic intensity of recognition to ensure the accuracy of recognition; In this way, it is possible to distinguish between real fluctuations caused by environmental factors (such as periodic changes in temperature and humidity) and random noise or non-periodic interference, thus providing a key basis for subsequent judgment on whether the abnormal readings of sensitive sensors are artifacts caused by composite interference. In one possible design, in order to analyze the readings of the sensitive sensor and identify the vibration interference characteristics of the sensitive sensor, this application further includes the following steps: S201. Obtain the reading sequence of the sensitive sensor within a preset time window; The preset time window refers to a continuous time interval used to analyze the readings of the sensitive sensor. Its length can be set according to the actual application scenario and the required level of analysis, for example, it can be set to several seconds to tens of seconds. This reading sequence contains environmental parameter data, such as temperature, humidity, or gas concentration, continuously collected by the sensitive sensor within this time window.

[0042] S202. Calculate the fluctuation amplitude of the reading sequence based on the reading sequence; The fluctuation amplitude reflects the overall deviation of the reading sequence.

[0043] As one possible implementation, the system can divide a preset time window into multiple sub-time windows; calculate the fluctuation amplitude of the reading sequence within each sub-time window; and obtain the maximum value from the fluctuation amplitudes of the multiple sub-time windows as the fluctuation amplitude of the reading sequence.

[0044] It should be noted that the preset time window refers to the time period used to acquire the reading sequence of sensitive sensors. For example, it can be a relatively long time period, such as several seconds, tens of seconds, or even several minutes.

[0045] To capture the fluctuation characteristics in the reading sequence more precisely, the preset time window is further subdivided into multiple shorter sub-time windows. For example, a 10-second preset time window can be divided into 10 one-second sub-time windows, or 20 0.5-second sub-time windows. The length and number of sub-time windows can be flexibly configured according to the actual application scenario and the vibration characteristics to be detected.

[0046] Specifically, the fluctuation amplitude is calculated independently for the reading sequence within each sub-time window.

[0047] For example, the statistical dispersion of the reading sequence within a sub-time window is calculated, and the statistical dispersion is used as the fluctuation range of the reading sequence within the sub-time window.

[0048] Among them, statistical dispersion can be such as standard deviation, variance, range (the difference between the maximum and minimum values), mean absolute deviation, etc.

[0049] By calculating the fluctuation amplitude of each sub-time window, local intensity information of reading fluctuations in different time periods can be obtained.

[0050] The purpose of this approach is to ensure that even if vibration disturbances exhibit drastic fluctuations only within a brief sub-time window throughout the entire preset time window, these drastic fluctuations can be effectively captured and reflected in the final fluctuation amplitude index. For example, if the reading fluctuation amplitude within a certain sub-time window is significantly higher than that in other sub-time windows, then this maximum value will be used as the representative fluctuation amplitude for subsequent vibration disturbance feature identification.

[0051] In some preferred embodiments, a specific example is given below. Suppose a sensitive sensor acquires a sequence of readings within a preset 10-second time window. If a conventional single calculation method is used, such as calculating the standard deviation of the readings within these 10 seconds, the standard deviation for the entire 10 seconds may be insufficient to highlight the impact when the mechanical vibration only causes a severe shock between the 3rd and 4th seconds, while the readings remain relatively stable in other time periods. However, according to the solution of this application, the preset 10-second time window can be divided into 10 sub-time windows of 1 second each. The system calculates the reading fluctuation amplitude (e.g., using standard deviation or range) within each 1-second sub-time window. Suppose that in the sub-time window between the 3rd and 4th seconds, due to mechanical vibration, the calculated reading fluctuation amplitude is 0.8, while in the other sub-time windows, the fluctuation amplitude is between 0.1 and 0.2. The maximum value, 0.8, from the fluctuation amplitudes of these 10 sub-time windows is taken as the fluctuation amplitude of the entire reading sequence. This fluctuation amplitude of 0.8 is significantly higher than the average value that might be obtained by traditional single calculation methods, thus more accurately indicating the presence of severe mechanical vibration interference. Therefore, the system can more sensitively identify this instantaneous vibration interference characteristic, providing more reliable data support for subsequent judgments.

[0052] S203. Calculate the instantaneous rate of change of the reading sequence based on the reading sequence.

[0053] The instantaneous rate of change reflects the degree of drastic change in the reading sequence.

[0054] As one possible implementation, the system can calculate the difference between adjacent readings, the average of the absolute values ​​of the differences, or perform differentiation or difference operations on the reading sequence, and then calculate the instantaneous rate of change of the reading sequence.

[0055] As another possible implementation, the system can acquire data of the reading sequence within a preset sliding window; calculate the difference between adjacent readings within the sliding window based on the data in the sliding window to obtain multiple differences; calculate the statistics of the multiple differences and use the statistics as the instantaneous rate of change.

[0056] The statistics include one of the following: median, cutoff mean, interquartile range.

[0057] This process involves calculating the differences between adjacent readings within a sliding window, resulting in multiple differences. Specifically, for each consecutive pair of readings within the sliding window, the difference between the subsequent reading and the preceding reading is calculated. These differences reflect the magnitude of change in the readings over a very short period; the larger the absolute value, the more drastic the change in the reading.

[0058] The truncated mean refers to removing a portion of the maximum and minimum values ​​before calculating the average of multiple differences (for example, removing the highest and lowest 5% or 10% of the difference). This method also reduces the interference of outliers on the calculation results, making the assessment of instantaneous rate of change more stable and accurate.

[0059] The interquartile range (IQR) refers to the difference between the third quartile and the first quartile of multiple differences. IQR reflects the middle 50% dispersion of a dataset. For asymmetric distributions or difference sequences containing outliers, it can more robustly reflect the range of data fluctuations than the standard deviation, thus effectively characterizing the instantaneous rate of change.

[0060] S204. If the fluctuation amplitude exceeds the preset first threshold and the instantaneous change rate exceeds the preset second threshold, the sensitive sensor will display vibration interference characteristics.

[0061] The preset first threshold and the preset second threshold are judgment criteria pre-set based on experience, experiments, or historical data. When the reading sequence of a sensitive sensor simultaneously exhibits a large overall deviation (fluctuation amplitude) and drastic continuous changes (instantaneous rate of change), this is usually a typical manifestation of mechanical vibration interfering with the sensor readings.

[0062] The above technical solution enables a more detailed and comprehensive analysis of the readings from sensitive sensors, thereby more accurately identifying the interference characteristics caused by mechanical vibration on the sensor readings. This precise identification capability helps to effectively distinguish between the artifacts caused by mechanical vibration and the actual changes in the goods' environment, avoiding unnecessary preservation interventions due to misjudgment, thus improving the accuracy and efficiency of the intelligent packaging preservation control system.

[0063] However, in practical applications, simply identifying the type of anomaly may not be sufficient to meet the needs of refined management and remote monitoring. For example, different degrees of simulated mechanical vibration or varying amplitudes of real environmental changes may require different levels of attention or follow-up processing. Existing solutions lack mechanisms for quantitatively assessing and effectively reporting these anomalies, thus limiting the remote monitoring platform's ability to conduct in-depth analysis and provide accurate responses to anomalies.

[0064] In this regard, this application also includes the following steps: S301. Based on the judgment result, obtain the type of the judgment result.

[0065] The types of judgment results may include, but are not limited to: illusions caused by mechanical vibration, illusions caused by combined interference, and changes in the actual environment of the goods.

[0066] S302. If the type of the judgment result is an artifact caused by mechanical vibration or an artifact caused by compound interference, then the degree of influence of the artifact is determined according to the fluctuation amplitude of the reading sequence of the sensitive sensor.

[0067] The fluctuation amplitude reflects the overall deviation of the sensitive sensor readings over a specific time period, and its magnitude can directly quantify the intensity of interference caused by artifacts to the sensor readings. For example, the larger the fluctuation amplitude, the more severe the impact of mechanical vibration or combined interference on the sensitive sensor, and the higher the degree of its impact.

[0068] The degree of impact can be divided into several levels, such as "mild", "moderate", and "severe".

[0069] As one possible implementation, the system can monitor the duration of vibration interference characteristics displayed by the sensitive sensor and the frequency of occurrence of vibration interference characteristics displayed by the sensitive sensor; and determine the level to which the artifact belongs based on the fluctuation amplitude, duration, frequency of occurrence and level mapping relationship of the reading sequence of the sensitive sensor, and determine the level to which the artifact belongs as the degree of influence of the artifact.

[0070] The level mapping relationship includes the mapping relationship between different fluctuation amplitudes, different durations, different frequencies of occurrence, and different levels.

[0071] In some preferred embodiments, a specific example is given below. Suppose that during the transportation of a smart packaging box, a sensitive sensor exhibits rapid fluctuations in its readings over a certain period, identified as a vibration interference feature. The system first detects that this vibration interference feature lasts for 5 minutes, and that similar features have occurred 3 times in the past hour. Simultaneously, the fluctuation amplitude of the sensor's reading sequence is calculated to be 0.8 (assuming a preset threshold of 0.5). At this point, the system will make a judgment based on a preset level mapping relationship. For example, this mapping relationship might define: a fluctuation amplitude greater than 0.7, a duration greater than 3 minutes, and an occurrence frequency greater than 2 times / hour constitutes a severe impact level; a fluctuation amplitude greater than 0.5, a duration greater than 1 minute, and an occurrence frequency greater than 1 time / hour constitutes a moderate impact level; and other situations constitute a slight impact level. Based on the data in the above example (fluctuation amplitude 0.8, duration 5 minutes, occurrence frequency 3 times / hour), the system will determine the level of the artifact to be "severe impact level" and classify this level as the degree of impact of the artifact. In this way, even if the amplitude of two vibration disturbances is the same, if one lasts longer or occurs more frequently, its impact will be assessed more significantly, thus making the assessment of the illusion closer to the actual situation and providing a more refined reference for subsequent decision-making.

[0072] S303. If the judgment result is a change in the actual environment of the goods, the degree of change in the actual environment of the goods shall be determined based on the fluctuation range of the reading sequence of the stable sensor.

[0073] For example, if the temperature rises by 10°C within 10 minutes, it might be classified as "rapid temperature rise, high degree of change." A quality flag is then created, containing an indication of the type of "actual environmental change of the goods" and the degree of change for "rapid temperature rise, high degree of change." This quality flag is reported to a remote monitoring platform along with the raw readings from the sensitive sensors. Upon receiving this information, the remote platform immediately identifies it as a genuine temperature anomaly and, based on the "rapid temperature rise, high degree of change" indication, triggers emergency preservation interventions, such as activating the cooling system or issuing an emergency alarm, to prevent spoilage of the goods.

[0074] S304. Construct quality tags.

[0075] Among them, quality markings include indications of the type of judgment result and indications of the degree of influence of the illusion or the degree of change in the actual environment of the goods.

[0076] S305. Attach a quality mark to the reading of the sensitive sensor and report the reading and quality mark to the remote monitoring platform.

[0077] In some preferred embodiments, a specific example is given below. Suppose a smart packaging box is transporting a batch of biological products that are sensitive to both temperature and vibration.

[0078] When a smart packaging box travels on rough terrain, the readings of sensitive sensors (e.g., a highly sensitive temperature sensor whose readings are easily affected by mechanical vibration) may fluctuate drastically, such as jumping from 20°C to 25°C and back to 20°C in a short period of time, while the readings of stable sensors (e.g., a temperature sensor mounted on a vibration-damping structure, or a humidity sensor that is not sensitive to vibration) remain stable at around 20°C. In this case, the system determines that the abnormal readings of the sensitive sensors are artifacts caused by mechanical vibration. Furthermore, the system determines the degree of influence of the artifact based on the fluctuation range of the sensitive sensor reading sequence (e.g., calculating its standard deviation or peak-to-valley difference). If the fluctuation range is large, it may be identified as "moderate vibration interference"; if the fluctuation range is small, it may be "minor vibration interference". Subsequently, a quality label is constructed, containing an indication of the type of "artifact caused by mechanical vibration" and an indication of the degree of influence of "moderate vibration interference". This quality label is reported to a remote monitoring platform along with the raw readings of the sensitive sensors. After receiving this information, the remote platform can identify that the temperature anomaly is not a real environmental change, but a normal disturbance during transportation, thereby avoiding unnecessary preservation interventions. It can also assess the suitability of the transportation route based on the degree of "moderate vibration interference".

[0079] For example, when a smart packaging box enters a high-temperature warehouse, the readings of both sensitive and stable sensors may rise synchronously and continuously, for instance, from 20°C to 30°C. In this case, the system will determine that the abnormal readings of the sensitive sensors indicate a change in the actual environment of the goods. Further, the system will determine the degree of this change based on the fluctuation range of the stable sensor reading sequence (e.g., calculating its average rate of increase or total increase over a specific time period). For example, if the temperature rises by 10°C within 10 minutes, it might be classified as "rapid temperature rise, high degree of change." Subsequently, a quality flag is constructed, containing an indication of the type of "change in the actual environment of the goods" and an indication of the degree of change for "rapid temperature rise, high degree of change." This quality flag will be reported to a remote monitoring platform along with the raw readings of the sensitive sensors. Upon receiving this information, the remote platform will immediately identify this as a genuine temperature anomaly and, based on the "rapid temperature rise, high degree of change" indication, trigger emergency preservation intervention measures, such as activating the cooling system or issuing an emergency alarm, to prevent spoilage of the goods.

[0080] like Figure 3 As shown in the figure, this invention also provides an intelligent packaging preservation control system. The system includes: The data acquisition module is used to collect environmental parameter data from sensitive and stable sensors inside the smart packaging box; the sensitive sensors are those that are sensitive to mechanical vibration; the stable sensors are those that are not sensitive to mechanical vibration. The anomaly detection module is used to identify reading anomalies of sensitive sensors. Reading anomalies include readings exceeding preset thresholds or readings exhibiting rapid fluctuations. Rapid fluctuations refer to readings fluctuating more than a fluctuation amplitude threshold within a preset time period. The auxiliary data acquisition module is used to acquire the readings of the stable sensor when an abnormal reading of the sensitive sensor is detected. The judgment module is used to determine whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment, based on the readings of the sensitive sensor and the stable sensor. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration; if the reading of the sensitive sensor is abnormal, while the reading of the stable sensor fluctuates synchronously, it is determined to be a change in the actual environment of the goods. An intervention suppression module is used to suppress the preservation intervention of the smart packaging box if the phenomenon is determined to be caused by mechanical vibration. The intervention execution module is used to perform preservation intervention on the smart packaging box if it is determined that there is a real change in the goods' environment.

[0081] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0082] Terminal devices can be computing devices such as desktop computers, laptops, PDAs, and smart tablets. Terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that the above-described components are merely examples of terminal devices and do not constitute a limitation on the terminal device. The device may include more or fewer components than described above, or a combination of certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0083] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device through various interfaces and lines.

[0084] Memory can be used to store computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). In addition, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, SmartMedia Card (SMC), Secure Digital (SD) card, Flash Card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0085] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0086] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0087] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention in detail. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for controlling the preservation of food in intelligent packaging, used in an intelligent packaging box, the intelligent packaging box comprising a sensitive sensor and a stable sensor, characterized in that, include: The system collects environmental parameter data from the sensitive sensor and the stable sensor inside the smart packaging box; the sensitive sensor is a sensor sensitive to mechanical vibration. The stable sensor is a sensor that is insensitive to mechanical vibration; The system identifies abnormal readings of the sensitive sensor, including readings exceeding a preset threshold or rapid fluctuations in the readings; rapid fluctuations refer to readings whose amplitude within a preset time period exceeds a fluctuation amplitude threshold. When an abnormal reading is detected in the sensitive sensor, the reading of the stable sensor is obtained; Based on the readings of the sensitive sensor and the stable sensor, determine whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration; if the reading of the sensitive sensor is abnormal, while the reading of the stable sensor fluctuates synchronously, it is determined to be a change in the actual environment of the goods. If the phenomenon is determined to be an artifact caused by the mechanical vibration, then the intervention on the preservation of the smart packaging box is suppressed. If it is determined that the actual environment of the goods has changed, then an intervention to preserve the freshness of the smart packaging box is performed; The step of determining whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment, based on the readings of the sensitive sensor and the stable sensor, includes: Analyze the readings of the sensitive sensor to identify the vibration interference characteristics of the sensitive sensor; Analyze the readings of the stable sensor to identify the periodic fluctuation characteristics of the stable sensor; Based on the readings of the sensitive sensor, the readings of the stable sensor, the vibration interference characteristics of the sensitive sensor, and the periodic fluctuation characteristics of the stable sensor, determine whether the abnormal readings of the sensitive sensor are an illusion caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by the mechanical vibration. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the sensitive sensor displays the vibration interference characteristics, and the stable sensor simultaneously displays the periodic fluctuation characteristics, then the abnormal reading of the sensitive sensor is determined to be an artifact caused by composite interference. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the stable sensor shows non-periodic continuous fluctuation, then the abnormal reading of the sensitive sensor is determined to be a change in the actual environment of the goods.

2. The intelligent packaging preservation control method according to claim 1, characterized in that, The analysis of the readings of the stable sensor and the identification of the periodic fluctuation characteristics of the stable sensor include: Extreme points are identified in the reading sequence of the stable sensor; the extreme points are either peak points or valley points. Calculate the time interval between the extreme points; If the distribution characteristics of the time intervals show that there are one or more concentrated intervals, and the number of intervals in the concentrated intervals reaches a preset proportion, then the periodic fluctuation characteristics of the stable sensor are identified.

3. The intelligent packaging preservation control method according to claim 1, characterized in that, The analysis of the readings of the sensitive sensor and the identification of the vibration interference characteristics of the sensitive sensor include: Obtain the reading sequence of the sensitive sensor within a preset time window; Based on the reading sequence, the fluctuation amplitude of the reading sequence is calculated, and the fluctuation amplitude reflects the overall deviation of the reading sequence; Based on the reading sequence, the instantaneous rate of change of the reading sequence is calculated, and the instantaneous rate of change reflects the degree of drastic continuous change of the reading sequence; If the fluctuation amplitude exceeds a preset first threshold and the instantaneous change rate exceeds a preset second threshold, then the sensitive sensor is identified to display the vibration interference characteristics.

4. The intelligent packaging preservation control method according to claim 3, characterized in that, The calculation of the fluctuation amplitude of the reading sequence includes: The preset time window is divided into multiple sub-time windows; For each of the sub-time windows, calculate its fluctuation amplitude; The maximum value among the fluctuation amplitudes of the multiple sub-time windows is taken as the fluctuation amplitude of the reading sequence.

5. The intelligent packaging preservation control method according to claim 4, characterized in that, The calculation of the fluctuation amplitude for the reading sequence within each sub-time window includes: Calculate the statistical dispersion of the reading sequence within the sub-time window, and use the statistical dispersion as the fluctuation amplitude of the reading sequence within the sub-time window.

6. The intelligent packaging preservation control method according to claim 3, characterized in that, The calculation of the instantaneous rate of change of the reading sequence includes: Acquire the data of the reading sequence within a preset sliding window; Based on the data within the sliding window, calculate the difference between adjacent readings within the sliding window to obtain multiple differences; Calculate the statistics of the plurality of differences and use the statistics as the instantaneous rate of change; the statistics are one of the following: median, cut-off mean, interquartile range.

7. The intelligent packaging preservation control method according to claim 1, characterized in that, The method further includes: Based on the judgment result, obtain the type of the judgment result; If the type of the judgment result is an artifact caused by the mechanical vibration or an artifact caused by the composite interference, then the degree of influence of the artifact is determined according to the fluctuation amplitude of the reading sequence of the sensitive sensor. If the type of the judgment result is the actual environmental change of the goods, then the degree of the actual environmental change of the goods is determined according to the fluctuation amplitude of the reading sequence of the stable sensor. Construct quality markers, which include an indication of the type of judgment result and an indication of the degree of influence of the illusion or an indication of the degree of change in the actual environment of the goods; The quality marker is attached to the reading of the sensitive sensor, and the reading and the quality marker are reported to the remote monitoring platform.

8. The intelligent packaging preservation control method according to claim 7, characterized in that, Determining the degree of influence of the illusion includes: The duration of the vibration disturbance characteristics displayed by the sensitive sensor is monitored; The frequency of occurrence of the vibration interference characteristics is monitored by the sensitive sensor. Based on the fluctuation amplitude of the reading sequence of the sensitive sensor, the duration, the occurrence frequency, and the level mapping relationship, the level to which the artifact belongs is determined, and the level to which the artifact belongs is determined as the degree of influence of the artifact; the level mapping relationship includes the mapping relationship between different fluctuation amplitudes, different durations, different occurrence frequencies, and different levels.

9. An intelligent packaging preservation control system for an intelligent packaging box, the intelligent packaging box comprising a sensitive sensor and a stable sensor, characterized in that, The system includes: The data acquisition module is used to collect environmental parameter data of the sensitive sensor and the stable sensor inside the smart packaging box; the sensitive sensor is a sensor that is sensitive to mechanical vibration; the stable sensor is a sensor that is not sensitive to mechanical vibration. An anomaly detection module is used to detect abnormal readings of the sensitive sensor. The abnormal readings include readings exceeding a preset threshold or readings exhibiting rapid fluctuations. Rapid fluctuations refer to readings fluctuating within a preset time period with an amplitude greater than a fluctuation amplitude threshold. An auxiliary data acquisition module is used to acquire the reading of the stable sensor when an abnormal reading of the sensitive sensor is detected. The judgment module is used to determine, based on the readings of the sensitive sensor and the stable sensor, whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by mechanical vibration; if the reading of the sensitive sensor is abnormal, while the reading of the stable sensor fluctuates synchronously, it is determined to be a change in the actual environment of the goods. The step of determining whether the abnormal reading of the sensitive sensor is a false alarm caused by mechanical vibration or a real change in the cargo's environment, based on the readings of the sensitive sensor and the stable sensor, includes: Analyze the readings of the sensitive sensor to identify the vibration interference characteristics of the sensitive sensor; Analyze the readings of the stable sensor to identify the periodic fluctuation characteristics of the stable sensor; Based on the readings of the sensitive sensor, the readings of the stable sensor, the vibration interference characteristics of the sensitive sensor, and the periodic fluctuation characteristics of the stable sensor, determine whether the abnormal readings of the sensitive sensor are an illusion caused by mechanical vibration or a real change in the cargo's environment. If the reading of the sensitive sensor is abnormal, while the reading of the stable sensor remains stable, it is determined to be an artifact caused by the mechanical vibration. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the sensitive sensor displays the vibration interference characteristics, and the stable sensor simultaneously displays the periodic fluctuation characteristics, then the abnormal reading of the sensitive sensor is determined to be an artifact caused by composite interference. If the reading of the sensitive sensor is abnormal, and the reading of the stable sensor fluctuates synchronously, and the stable sensor shows non-periodic continuous fluctuation, then the abnormal reading of the sensitive sensor is determined to be a change in the actual environment of the goods. An intervention suppression module is used to suppress the preservation intervention on the smart packaging box if the phenomenon is determined to be caused by the mechanical vibration. The intervention execution module is used to perform preservation intervention on the smart packaging box if it is determined that there is a change in the actual environment of the goods.

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