Vegetable transportation data management method

Abstract

The invention relates to the technical field of data management, in particular to a vegetable transportation data management method, which comprises the following steps of: setting a plurality of sensors corresponding to environmental parameters for monitoring in real time and uploading the data to a management terminal; the management terminal determines abnormal data and normal data, uploads the normal data to a database for storage and backup, and determines whether to give an abnormal early warning to the abnormal data based on the maximum delay duration and fluctuation frequency of the abnormal data within a preset duration; determining an early warning method for the abnormal data based on the change rate of the abnormal data sending the abnormal early warning and whether the abnormal data has associated abnormal data; determining whether to adjust the vegetable transportation data management process parameters or not based on the loss rate of the vegetables in the preset period and the early warning effective rate; according to the invention, the authenticity of vegetable transportation data monitored by the sensor is analyzed, so that the authenticity of a real vegetable transportation environment state is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a vegetable transportation data management method. Background Art

[0002] Vegetables are an important food that is indispensable in people's daily lives, and their transportation is crucial. However, due to improper transportation data management during transportation, vegetables are damaged. Therefore, vegetable transportation data management has become a problem that needs to be solved urgently. Traditional vegetable transportation data management methods usually use sensors to monitor the vegetable transportation environment, and check in real time based on sensor data whether the vegetable transportation environment meets the transportation standards. Not only is the accuracy and efficiency low, but the vegetables still cannot be accurately protected.

[0003] Chinese patent application publication number: CN110648069A discloses a vegetable quality analysis system based on a transport vehicle, including a temperature detection module, a humidity detection module, a bacteria detection module, an image acquisition module, a screening preprocessing module, a data modeling module, a data processing module, an analysis and evaluation module and a display terminal. The invention provides a vegetable quality analysis system based on a transport vehicle, which detects the temperature, humidity, bacteria types and bacteria quantity in the vegetable storage environment and extracts the red, green and blue components in the vegetable image in combination with the screening preprocessing module to calculate the vegetable quality coefficient and display the quality changes during the vegetable storage process. It has the characteristics of high quality detection accuracy and good real-time performance, which is convenient for managers to intuitively understand the quality changes of vegetables during the storage process, provide reliable reference data for the storage of vegetables, and provide the best storage environment according to the quality of vegetables, so as to optimize the quality of vegetables and reduce losses.

[0004] It can be seen that the existing technology has the problem that when using sensors to monitor environmental parameters of vegetables during transportation, the sensors may have data distortion due to interference from the transportation environment. The above technical solution does not perform authenticity analysis on the sensor monitoring data, resulting in the monitoring data being unable to reflect the actual environmental status, leading to inaccurate abnormal monitoring, and thus causing a high damage rate of transported vegetables. Summary of the invention

[0005] To this end, the present invention provides a vegetable transportation data management method to overcome the problem in the prior art that when using sensors to monitor environmental parameters of vegetables during transportation, the sensors may have data distortion due to interference from the transportation environment. The above technical solution does not perform authenticity analysis on the sensor monitoring data, resulting in the monitoring data being unable to reflect the actual environmental status, resulting in inaccurate abnormal monitoring, and thus causing a high damage rate of transported vegetables.

[0006] To achieve the above object, the present invention provides a vegetable transportation data management method, comprising:

[0007] Based on the characteristic information of the vegetables to be transported and the transportation route information, the types and ranges of the transportation environment parameters of the vegetables to be transported are determined, and a plurality of sensors corresponding to the environmental parameters are set to monitor the transportation environment parameters in real time and upload the monitored data to the management terminal;

[0008] The management terminal determines the abnormal data and normal data of the sensor based on the range of the transportation environment parameters of the vegetables to be transported, and uploads the normal data to a database for storage and backup. The management terminal determines whether to issue an abnormal warning for the abnormal data based on the maximum delay time and fluctuation frequency of the abnormal data within a preset time period;

[0009] Determining to issue a vibration abnormality warning, an electromagnetic interference warning, or a transportation environment abnormality warning for the abnormal data based on a change rate of the abnormal data for which the abnormal warning is issued and whether the abnormal data for which the abnormal warning is issued has associated abnormal data;

[0010] Based on the loss rate of vegetables after transportation within the preset period and the early warning efficiency, determine whether to adjust the parameters of the vegetable transportation data management process.

[0011] Further, the determining of the type and range of the transportation environment parameters of the vegetables to be transported includes:

[0012] Collect characteristic information of different types of vegetables, including the influence of temperature, humidity, oxygen content and carbon dioxide content, and determine the types of transportation environment parameters for the vegetables to be transported;

[0013] Collect transportation route information, including route length, altitude changes, temperature and humidity changes, and preset transportation time;

[0014] Simulate temperature and humidity changes under different transportation durations and transportation routes;

[0015] According to the simulated vegetable status, the range of transportation environment parameters under the preset transportation time and transportation route is determined.

[0016] Further, the management terminal determines the abnormal data and normal data of the sensor including:

[0017] Determining that the real-time data is abnormal data according to a comparison result that the real-time data is not within the range of the transportation environment parameters;

[0018] The real-time data is determined to be normal data according to a comparison result that the real-time data is within the range of the transportation environment parameters.

[0019] Further, the management terminal determines whether to issue an abnormal warning for the abnormal data, including:

[0020] According to the comparison result that the maximum delay time of the abnormal data within the preset time period is greater than or equal to the preset delay time period, or the fluctuation frequency of the abnormal data is greater than or equal to the preset fluctuation frequency, it is determined to issue an abnormal warning for the abnormal data.

[0021] Furthermore, the fluctuation frequency of the abnormal data is determined according to the ratio of the duration of occurrence of abnormal data of the same type within a preset time period to the preset time period.

[0022] Further, the management terminal determines to issue a vibration abnormality warning, an electromagnetic interference warning, or a transportation environment abnormality warning for the abnormal data, including:

[0023] Determining to issue a vibration abnormality warning for the abnormal data according to a comparison result that a change rate of the abnormal data for issuing the abnormal warning is greater than or equal to a preset change rate;

[0024] Determining to issue an electromagnetic interference warning for the abnormal data according to a comparison result that a change rate of the abnormal data for which the abnormal warning is issued is less than a preset change rate and that the abnormal data for which the abnormal warning is issued does not have abnormal associated data;

[0025] According to the comparison result that the change rate of the abnormal data for issuing the abnormal warning is less than the preset change rate and the abnormal data for issuing the abnormal warning has abnormal associated data, a maximum difference analysis of the timestamps of the associated abnormal data is determined.

[0026] Furthermore, the determination of the abnormal associated data includes:

[0027] Collect environmental parameter data monitored by sensors, including temperature, humidity, oxygen concentration, and abnormal warning data issued by sensors;

[0028] Identify abnormal data points in the sensor data based on the above data, which data points indicate that environmental parameters are outside of a preset range or other abnormal conditions;

[0029] Analyze the correlation between abnormal data points and determine the correlation rules between abnormal data;

[0030] Extracting features associated with the abnormal data, the features including timestamps, sensor locations, and environmental parameter values;

[0031] Based on the characteristics of the abnormal data and the correlation analysis results, the abnormal correlation data of the abnormal data is determined.

[0032] Furthermore, the determining of the maximum difference analysis of the timestamps of the associated abnormal data includes:

[0033] Determining to issue a transportation environment abnormality warning for the abnormal data according to a comparison result in which the maximum difference of the timestamps of the associated abnormal data is greater than or equal to a preset difference;

[0034] According to the comparison result that the maximum difference of the timestamps of the associated abnormal data is less than the preset difference, it is determined to issue an electromagnetic interference warning for the abnormal data.

[0035] Furthermore, when determining whether to adjust the parameters of the vegetable transportation data management process, it is determined that the vegetable transportation data management process parameters need to be adjusted based on the comparison result that the loss rate of vegetables after transportation is completed within a preset period is greater than or equal to the preset loss rate or the early warning efficiency is less than the preset early warning efficiency, wherein the vegetable transportation data management process parameters include a preset delay duration, a preset fluctuation frequency, a preset change rate and a preset difference.

[0036] Furthermore, the adjustment amount of the preset delay time is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset fluctuation frequency is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset change rate is positively correlated with the early warning effectiveness, and the adjustment amount of the preset difference is negatively correlated with the early warning effectiveness.

[0037] Compared with the prior art, the beneficial effect of the present invention lies in that the present invention can monitor the changes of abnormal data in real time through the management terminal, and respond to abnormal situations in time according to the set conditions, which helps to reduce delays and deal with problems in time. By considering the fluctuation frequency, it can avoid false alarms caused by instantaneous data fluctuations or short-term abnormal situations, improve the accuracy and reliability of abnormal warnings, and determine whether to issue an abnormal warning. It is necessary to comprehensively consider the delay time and fluctuation frequency of the abnormal data, which helps to improve the efficiency and accuracy of the warning, ensure that only abnormal situations that really need attention will trigger warnings, thereby improving the authenticity of the data monitored by the sensor.

[0038] Furthermore, by analyzing the change rate and correlation of abnormal data, the management terminal of the present invention can realize refined monitoring of different types of abnormal situations such as vibration, electromagnetic interference and transportation environment, thereby improving the accuracy and sensitivity of monitoring. According to the change rate of abnormal data and the associated abnormal data, the management terminal can respond to different types of abnormal situations more quickly. By comprehensively analyzing the change rate and correlation of abnormal data, false alarms caused by instantaneous fluctuations or isolated abnormal data can be reduced, and the accuracy and reliability of early warnings can be improved. Different types of early warnings are issued according to the type of abnormal data, which helps management personnel to better allocate resources and take countermeasures, thereby improving the efficiency and cost control of problem handling during transportation. By issuing vibration abnormality early warnings, electromagnetic interference early warnings or transportation environment abnormality early warnings, different types of potential risks and problems can be effectively identified and responded to, thereby improving the safety and stability of the transportation process. Different types of early warnings are issued based on the change rate of abnormal data and the correlation between abnormal data, thereby avoiding the problem that when using sensors to monitor environmental parameters of vegetables during transportation, the sensor monitoring data cannot reflect the actual environmental state due to interference from the transportation environment, resulting in inaccurate abnormal monitoring, thereby resulting in a high damage rate of transported vegetables.

[0039] Furthermore, the present invention can optimize the vegetable transportation process, reduce the vegetable loss rate, and improve transportation efficiency and quality by adjusting management parameters according to the loss rate and early warning effectiveness. Based on the vegetable loss rate and early warning effectiveness within a preset period, the management terminal can monitor the transportation situation in real time and adjust parameters in time to reduce vegetable losses. By optimizing data management parameters, the vegetable loss rate can be reduced, the cost caused by the loss can be reduced, and the transportation efficiency can be improved. Adjusting management parameters can improve the accuracy of the early warning system, ensuring that only abnormal situations that really need attention will trigger early warnings, reduce false alarm rates, and improve the efficiency of monitoring and responding to abnormal situations, ensuring that vegetables remain in good condition during transportation. By adjusting parameters, the quality and freshness of vegetables during transportation can be improved, increasing product competitiveness.

[0040] Furthermore, according to the comparison result that the loss rate of vegetables after the transportation is completed within the preset period is greater than or equal to the preset loss rate and the early warning efficiency is greater than or equal to the preset early warning efficiency, the present invention indicates that the loss rate of vegetables is large due to the failure to issue an early warning in time during the transportation process. At this time, the preset delay time and the preset fluctuation frequency are adjusted by the first adjustment coefficient so as to issue an early warning in time. According to the comparison result that the loss rate of vegetables after the transportation is completed within the preset period is less than the preset loss rate and the early warning efficiency is less than the preset early warning efficiency, it indicates that the early warning method is inaccurately selected during the transportation of vegetables, resulting in low early warning efficiency. At this time, the corresponding preset threshold is adjusted by the corresponding adjustment coefficient according to the early warning efficiency of the corresponding early warning method. The authenticity of the sensor monitoring data is improved through the above method, thereby reducing the damage rate of the transported vegetables. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention is a flowchart of the method for managing vegetable transportation data according to an embodiment of the present invention;

[0042] Figure 2 A workflow diagram for determining whether the data of a plurality of sensors corresponding to the environmental parameters monitored are normal data or abnormal data in the vegetable transportation data management method according to an embodiment of the present invention;

[0043] Figure 3 This is a workflow diagram for determining whether to issue an abnormal warning for abnormal data in the vegetable transportation data management method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0045] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0046] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0047] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] See also Figure 1-Figure 3 As shown, Figure 1 The present invention is a flowchart of the method for managing vegetable transportation data according to an embodiment of the present invention; Figure 2 A workflow diagram for determining whether the data of a plurality of sensors corresponding to the environmental parameters monitored are normal data or abnormal data in the vegetable transportation data management method according to an embodiment of the present invention; Figure 3This is a workflow diagram for determining whether to issue an abnormal warning for abnormal data in the vegetable transportation data management method according to an embodiment of the present invention.

[0049] The vegetable transportation data management method according to the embodiment of the present invention comprises:

[0050] Step S1, based on the characteristic information of the vegetables to be transported and the transportation route information, determine the type and range of the transportation environment parameters of the vegetables to be transported, set a number of sensors corresponding to the environmental parameters to monitor the transportation environment parameters in real time and upload the monitored data to the management terminal;

[0051] Step S2, the management terminal determines the abnormal data and normal data of the sensor based on the range of the transportation environment parameters of the vegetables to be transported, the management terminal uploads the normal data to the database for storage and backup, and the management terminal determines whether to issue an abnormal warning for the abnormal data based on the maximum delay time and fluctuation frequency of the abnormal data within a preset time;

[0052] Step S3, determining to issue a vibration abnormality warning, an electromagnetic interference warning or a transportation environment abnormality warning for the abnormal data based on the change rate of the abnormal data for which the abnormal warning is issued and whether there is any associated abnormal data for the abnormal data for which the abnormal warning is issued;

[0053] Step S4, determining whether to adjust the parameters of the vegetable transportation data management process based on the loss rate of vegetables after transportation within a preset period and the early warning efficiency.

[0054] The transportation environment parameters described in the embodiment of the present invention include but are not limited to "temperature, humidity and gas concentration", the gas includes but is not limited to ethylene, oxygen and carbon dioxide, the sensors set up to monitor the environmental parameters include but are not limited to "temperature corresponding to temperature sensor, humidity corresponding to humidity sensor and gas concentration corresponding to gas sensor", the management terminal includes but is not limited to "cloud server, mobile APP and Web platform", and the preset transportation time is the transportation time calculated according to the transportation route.

[0055] Specifically, in step S1, determining the type and range of the transportation environment parameters of the vegetables to be transported includes:

[0056] Collect characteristic information of different types of vegetables, including the influence of temperature, humidity, oxygen content and carbon dioxide content, and determine the types of transportation environment parameters for the vegetables to be transported;

[0057] Collect transportation route information, including route length, altitude changes, temperature and humidity changes, and preset transportation time;

[0058] Simulate temperature and humidity changes under different transportation durations and transportation routes;

[0059] According to the simulated vegetable status, the range of transportation environment parameters under the preset transportation time and transportation route is determined.

[0060] In the embodiment of the present invention, it is assumed that the vegetables to be transported are broccoli. By consulting agricultural scientific research materials and consulting professional growers, it is learned that broccoli is sensitive to temperature, and the suitable transportation temperature is between 0°C and 4°C; the humidity requirement is also high, and the suitable humidity is about 90% to 95%; at the same time, there are certain requirements for oxygen content and carbon dioxide content. Too high carbon dioxide content will affect the quality of broccoli. Therefore, the types of transportation environment parameters of broccoli are determined to be temperature, humidity, oxygen content and carbon dioxide content; taking the transportation from vegetable production area A to sales area B as an example, the transportation route length is 500 kilometers. By querying map software and weather forecast, it is learned that the route will pass through some mountainous areas, and the altitude changes between 500 meters and 1500 meters. According to historical meteorological data, the temperature and humidity along the way vary greatly, and high temperature and high humidity or low temperature and low humidity may occur. The preset transportation time is two days; it is simulated that during the transportation process, the temperature may fluctuate between -5℃ and 30℃, and the humidity varies between 60% and 95%. The environmental test chamber can also be used to simulate similar transportation conditions to observe the state changes of broccoli under different temperature and humidity conditions; through simulation and observation, it is found that broccoli is in good condition when the temperature is 0℃ to 4℃, the humidity is 90% to 95%, the oxygen content is moderate, and the carbon dioxide content is low. Combined with the preset transportation time and transportation route, the transportation environment parameter range of broccoli on this transportation route is determined as follows: temperature 0℃ to 4℃, humidity 90% to 95%, oxygen content is maintained at normal air levels, and carbon dioxide content is controlled as much as possible within the range of 0.03%-1%.

[0061] The vegetable status in the embodiment of the present invention includes good and damaged. The good vegetable status includes but is not limited to "the color difference between the vegetables after transportation and the vegetables before transportation is less than 2 and the vegetables after transportation do not emit any peculiar smell". The damaged vegetable status includes but is not limited to "the color difference between the vegetables after transportation and the vegetables before transportation is greater than or equal to 2 or the vegetables after transportation emit any peculiar smell". The vegetable status can be determined by comparing the vegetable image after transportation with the vegetable image before transportation.

[0062] Specifically, in step S2, when determining the abnormal data and normal data of the several sensors corresponding to the environmental parameters, the management terminal determines the abnormal data and normal data of the several sensors corresponding to the environmental parameters according to the comparison result of the real-time data of the several sensors corresponding to the environmental parameters and the range of the transport environmental parameters;

[0063] When the real-time data of a plurality of sensors corresponding to the environmental parameters are not within the range of the transport environmental parameters, the management terminal determines that the real-time data is abnormal data;

[0064] When the real-time data of a plurality of sensors corresponding to the environmental parameters are within the range of the transport environmental parameters, the management terminal determines that the real-time data is normal data.

[0065] Specifically, in step S2, when determining whether to issue an abnormal warning for the abnormal data, the management terminal determines whether to issue an abnormal warning for the abnormal data according to the maximum delay duration and fluctuation frequency of the abnormal data within a preset duration;

[0066] When the maximum delay time of the abnormal data within the preset time is greater than or equal to the preset delay time or the fluctuation frequency of the abnormal data is greater than or equal to the preset fluctuation frequency, the management terminal determines to issue an abnormal warning for the abnormal data;

[0067] When the maximum delay duration of the abnormal data within the preset duration is less than the preset delay duration and the fluctuation frequency of the abnormal data is less than the preset fluctuation frequency, the management terminal determines not to issue an abnormal warning for the abnormal data.

[0068] In the embodiment of the present invention, the value range of the preset time length is set to 60 seconds-240 seconds, and the value of the preset time length is preferably 100 seconds. The value range of the preset delay time length is set to 30 seconds-100 seconds, and the value of the preset delay time length is preferably 40 seconds. The fluctuation frequency of the abnormal data is determined according to the ratio of the occurrence duration of abnormal data of the same type within the preset duration to the preset duration. The value range of the preset fluctuation frequency is set to 0.4-1, and the value range of the preset fluctuation frequency is preferably 0.58, but the above values ​​are not limited thereto, and those skilled in the art may also adjust the values ​​according to actual needs.

[0069] The present invention can monitor the changes of abnormal data in real time through the management terminal, and respond to abnormal situations in time according to the set conditions, which helps to reduce delays and deal with problems in time. By considering the fluctuation frequency, it can avoid false alarms caused by instantaneous data fluctuations or short-term abnormal situations, improve the accuracy and reliability of abnormal warnings, and determine whether to issue an abnormal warning. It is necessary to comprehensively consider the delay time and fluctuation frequency of the abnormal data, which helps to improve the efficiency and accuracy of the warning, ensure that only abnormal situations that really need attention will trigger warnings, thereby improving the authenticity of the data monitored by the sensor.

[0070] Specifically, in step S3, when it is determined to issue an abnormal warning for the abnormal data, the management terminal determines to issue a vibration abnormality warning, an electromagnetic interference warning or a transportation environment abnormality warning for the abnormal data according to the change rate of the abnormal data for which the abnormal warning is issued and whether there is associated abnormal data with the abnormal data for which the abnormal warning is issued;

[0071] When the change rate of the abnormal data for issuing the abnormal warning is greater than or equal to the preset change rate, determining to issue a vibration abnormality warning for the abnormal data;

[0072] When the change rate of the abnormal data for which the abnormal warning is issued is less than the preset change rate and there is abnormal associated data in the abnormal data for which the abnormal warning is issued, determining to issue an electromagnetic interference warning for the abnormal data;

[0073] When the change rate of the abnormal data for issuing the abnormal warning is less than the preset change rate and there is no abnormal associated data for the abnormal data for issuing the abnormal warning, a maximum difference analysis of the timestamps of the associated abnormal data is determined.

[0074] Specifically, in step S3, when analyzing the maximum difference of the timestamps of the associated abnormal data, it is determined whether to issue a transportation environment abnormality warning or an electromagnetic interference warning for the abnormal data according to the comparison result of the maximum difference of the timestamps of the associated abnormal data and the preset difference;

[0075] When the maximum difference of the timestamps of the associated abnormal data is greater than or equal to a preset difference, determining to issue a transportation environment abnormality warning for the abnormal data;

[0076] When the maximum difference of the timestamps of the associated abnormal data is less than a preset difference, it is determined to issue an electromagnetic interference warning for the abnormal data.

[0077] In the embodiment of the present invention, the rate of change of the abnormal data for issuing the abnormal warning is determined by the ratio of the maximum change amount of the abnormal data to the change time, the preset change rate is based on the historical average value of the change rate of the abnormal data monitored by the corresponding sensor during the vegetable transportation process, the maximum difference of the timestamps of the associated abnormal data is the difference obtained by subtracting the timestamp of the earliest abnormal data from the timestamp of the last abnormal data, the value range of the preset difference is set to 10-200 seconds, and the value of the preset difference is preferably 100 seconds, but the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0078] The abnormal associated data of the abnormal data for issuing the abnormal warning in the embodiment of the present invention can be determined according to the following method, including:

[0079] Collect environmental parameter data monitored by sensors, including temperature, humidity, oxygen concentration, and abnormal warning data issued by sensors;

[0080] Identify abnormal data points in the sensor data based on the above data, which data points indicate that environmental parameters are outside of a preset range or other abnormal conditions;

[0081] Analyze the correlation between abnormal data points and determine the correlation rules between abnormal data;

[0082] Extracting features associated with the abnormal data, the features including timestamps, sensor locations, and environmental parameter values;

[0083] Based on the characteristics of the abnormal data and the correlation analysis results, the abnormal correlation data of the abnormal data is determined.

[0084] In the embodiment of the present invention, during the transportation process, the sensor continuously monitors the environmental parameters, and the collected temperature data are: 1°C, 2°C, 3°C, 5°C, 4°C, 6°C, 7°C, 8°C; the humidity data are: 90%, 91%, 92%, 88%, 90%, 85%, 80%, 75%; the oxygen concentration data is stable at around 21%; at the same time, the sensor issues an abnormal warning when the temperature reaches 7°C and the humidity drops to 75%; the preset temperature range is 2°C-5°C, and the humidity range is 85%-95%. By comparison, it is found that 6℃, 7℃, 8℃ in the temperature data and 80% and 75% in the humidity data are abnormal data points, because these data points indicate that the environmental parameters exceed the preset range; it is observed that with the passage of time, the temperature gradually increases while the humidity gradually decreases; further analysis shows that the humidity begins to drop significantly only after the temperature rises to a certain level, indicating that the increase in temperature may be a factor leading to the decrease in humidity, and it is determined that there is a certain correlation between the abnormal data; for these abnormal data, the extracted features are as follows: Timestamp: When the temperature is 6℃, the corresponding timestamp is 5 hours and 30 minutes after the start of transportation; When the humidity is 80%, the corresponding timestamp is 5 hours and 45 minutes after the start of transportation; Sensor location: distributed in different locations of the truck compartment, but mainly concentrated in the location near the air outlet of the refrigeration equipment; Environmental parameter values: The abnormal temperature data are 6℃, 7℃, 8℃, and the abnormal humidity data are 80% and 75%; Based on the characteristics of the abnormal data and the results of the correlation analysis, it can be determined that temperature and humidity are abnormally correlated data.

[0085] In the embodiment of the present invention, when it is determined that a vibration abnormality warning is issued for the abnormal data, the sensor installation position and circuit connection are checked to determine whether the sensor data is abnormal data due to vibration during transportation causing the sensor to fall from the installation position or the circuit connection is loosened; when it is determined that an electromagnetic interference warning is issued for the abnormal data, the machine that can emit electromagnetic interference is shut down; when it is determined that a transportation environment abnormality warning is issued for the abnormal data, it is checked whether the vegetable transportation environment has changed making it unsuitable for transporting vegetables.

[0086] By analyzing the change rate and correlation of abnormal data, the management terminal of the present invention can realize refined monitoring of different types of abnormal situations such as vibration, electromagnetic interference and transportation environment, improve the accuracy and sensitivity of monitoring, and according to the change rate of abnormal data and the associated abnormal data, the management terminal can respond to different types of abnormal situations more quickly, and by comprehensively analyzing the change rate and correlation of abnormal data, it can reduce false alarms caused by instantaneous fluctuations or isolated abnormal data, and improve the accuracy and reliability of early warnings. Different types of early warnings are issued according to the type of abnormal data, which helps management personnel to better allocate resources and take countermeasures, and improve the efficiency and cost control of problem handling during transportation. By issuing vibration abnormality early warning, electromagnetic interference early warning or transportation environment abnormality early warning, different types of potential risks and problems can be effectively identified and responded to, and the safety and stability of the transportation process can be improved. Different types of early warnings are issued based on the change rate of abnormal data and the correlation between abnormal data, so as to avoid the problem that when using sensors to monitor environmental parameters of vegetables during transportation, the sensor monitoring data cannot reflect the real environmental state due to interference from the transportation environment, resulting in inaccurate abnormal monitoring, thereby causing a high damage rate of transported vegetables.

[0087] Specifically, in step S4, when determining whether to adjust the parameters of the vegetable transportation data management process, it is determined whether to adjust the parameters of the vegetable transportation data management process according to the loss rate of vegetables after transportation is completed within a preset period and the early warning efficiency;

[0088] When the loss rate of vegetables after transportation within a preset period is greater than or equal to the preset loss rate and the early warning efficiency is greater than or equal to the preset early warning efficiency, determining to adjust the parameters of the vegetable transportation data management process in a first adjustment manner;

[0089] When the loss rate of vegetables after transportation within a preset period is less than a preset loss rate and the early warning efficiency is less than a preset early warning efficiency, determining to adjust the parameters of the vegetable transportation data management process in a second adjustment manner;

[0090] When the loss rate of vegetables after transportation within a preset period is greater than or equal to the preset loss rate and the early warning efficiency is less than the preset early warning efficiency, determining to adjust the parameters of the vegetable transportation data management process in a first adjustment manner and a second adjustment manner respectively;

[0091] When the loss rate of vegetables after transportation within a preset period is less than a preset loss rate and the early warning efficiency is greater than or equal to the preset early warning efficiency, it is determined that there is no need to adjust the parameters of the vegetable transportation data management process.

[0092] In the embodiment of the present invention, the vegetable transportation data management process parameters include a preset delay time, a preset fluctuation frequency, a preset change rate and a preset difference. The preset period is set to transport vegetables 10 times. The loss rate of vegetables after the transportation is completed within the preset period is the ratio of the number of unqualified vegetables after the transportation is completed within the preset period to the total amount of vegetables. The early warning effectiveness rate is the ratio of the number of correct early warnings after the transportation of vegetables is completed within the preset period to the total number of early warnings. The unqualified vegetables include but are not limited to "vegetable discoloration, vegetable rot and vegetable mold". The correct early warning includes that the same abnormal data does not continue to appear after the corresponding early warning measures are taken after the early warning.

[0093] In the embodiment of the present invention, the value range of the preset loss rate is set to 0-0.3, and the value range of the preset loss rate is preferably 0.15. The value range of the preset early warning efficiency is set to 0.7-1, and the value range of the preset early warning efficiency is preferably 0.8, but the above values ​​are not limited to this, and technical personnel in this field can also adjust the values ​​according to actual needs.

[0094] The present invention can optimize the vegetable transportation process, reduce the vegetable loss rate, and improve the transportation efficiency and quality by adjusting the management parameters according to the loss rate and the early warning efficiency. Based on the vegetable loss rate and the early warning efficiency within a preset period, the management terminal can monitor the transportation situation in real time and adjust the parameters in time to reduce vegetable losses. By optimizing the data management parameters, the vegetable loss rate can be reduced, the cost caused by the loss can be reduced, and the transportation efficiency can be improved. Adjusting the management parameters can improve the accuracy of the early warning system, ensuring that only abnormal situations that really need attention will trigger early warnings, reduce the false alarm rate, improve the efficiency of monitoring and responding to abnormal situations, and ensure that vegetables remain in good condition during transportation. By adjusting the parameters, the quality and freshness of vegetables during transportation can be improved, and the competitiveness of products can be increased.

[0095] Specifically, when the vegetable transportation data management process parameters are adjusted in a first adjustment manner, it is determined that the preset delay time and the preset fluctuation frequency are adjusted in a first adjustment coefficient;

[0096] When the vegetable transportation data management process parameters are adjusted in the second adjustment mode, the corresponding preset threshold is adjusted by the corresponding adjustment coefficient according to the warning efficiency of the corresponding warning mode.

[0097] In the embodiment of the present invention, the adjustment of the corresponding preset threshold value with the corresponding adjustment coefficient is determined according to the warning efficiency of the corresponding warning method, including adjusting the preset change speed with the second adjustment coefficient when the warning efficiency of the vibration abnormality warning is lower than the preset warning efficiency, adjusting the preset difference with the second adjustment coefficient when the warning efficiency of the electromagnetic interference warning is lower than the preset warning efficiency, and adjusting the preset difference with the third adjustment coefficient when the warning efficiency of the transportation environment abnormality warning is lower than the preset warning efficiency.

[0098] In the embodiment of the present invention, the value range of the first adjustment coefficient is set to 0.8-0.98, the value range of the second adjustment coefficient is set to 0.82-0.99, the value range of the third adjustment coefficient is set to 1.01-1.22, the adjustment amount of the preset delay time is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset fluctuation frequency is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset change rate is positively correlated with the warning effectiveness, and the adjustment amount of the preset difference is negatively correlated with the warning effectiveness, but the above values ​​are not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0099] According to the comparison result that the loss rate of vegetables after the transportation is completed within the preset period is greater than or equal to the preset loss rate and the early warning efficiency is greater than or equal to the preset early warning efficiency, the present invention indicates that the vegetable loss rate is large due to the failure to issue an early warning in time during the transportation process. At this time, the preset delay time and the preset fluctuation frequency are adjusted with the first adjustment coefficient so as to issue an early warning in time. According to the comparison result that the loss rate of vegetables after the transportation is completed within the preset period is less than the preset loss rate and the early warning efficiency is less than the preset early warning efficiency, it indicates that the early warning method is inaccurately selected during the transportation of vegetables, resulting in low early warning efficiency. At this time, the corresponding preset threshold is adjusted with the corresponding adjustment coefficient according to the early warning efficiency of the corresponding early warning method. Through the above method, the authenticity of the sensor monitoring data is improved and the damage rate of the transported vegetables is reduced.

[0100] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0101] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A vegetable transportation data management method, characterized in that: include: Based on the characteristic information of the vegetables to be transported and the transportation route information, the types and ranges of the transportation environment parameters of the vegetables to be transported are determined, and a plurality of sensors corresponding to the environmental parameters are set to monitor the transportation environment parameters in real time and upload the monitored data to the management terminal; The management terminal determines the abnormal data and normal data of the sensor based on the range of the transportation environment parameters of the vegetables to be transported, and uploads the normal data to a database for storage and backup. The management terminal determines whether to issue an abnormal warning for the abnormal data based on the maximum delay time and fluctuation frequency of the abnormal data within a preset time period; Determining to issue a vibration abnormality warning, an electromagnetic interference warning, or a transportation environment abnormality warning for the abnormal data based on a change rate of the abnormal data for which the abnormal warning is issued and whether the abnormal data for which the abnormal warning is issued has associated abnormal data; Based on the loss rate of vegetables after transportation within the preset period and the early warning efficiency, determine whether to adjust the parameters of the vegetable transportation data management process.

2. The vegetable transportation data management method according to claim 1, characterized in that: Determining the type and range of the transportation environment parameters of the vegetables to be transported includes: Collect characteristic information of different types of vegetables, including the influence of temperature, humidity, oxygen content and carbon dioxide content, and determine the types of transportation environment parameters for the vegetables to be transported; Collect transportation route information, including route length, altitude changes, temperature and humidity changes, and preset transportation time; Simulate temperature and humidity changes under different transportation durations and transportation routes; According to the simulated vegetable status, the range of transportation environment parameters under the preset transportation time and transportation route is determined.

3. The vegetable transportation data management method according to claim 2, characterized in that: The management terminal determines the abnormal data and normal data of the sensor including: Determining that the real-time data is abnormal data according to a comparison result that the real-time data is not within the range of the transportation environment parameters; The real-time data is determined to be normal data according to a comparison result that the real-time data is within the range of the transportation environment parameters.

4. The vegetable transportation data management method according to claim 3 is characterized in that: The management terminal determines whether to issue an abnormal warning for the abnormal data, including: According to the comparison result that the maximum delay time of the abnormal data within the preset time period is greater than or equal to the preset delay time period, or the fluctuation frequency of the abnormal data is greater than or equal to the preset fluctuation frequency, it is determined to issue an abnormal warning for the abnormal data.

5. The vegetable transportation data management method according to claim 4, characterized in that: The fluctuation frequency of the abnormal data is determined according to the ratio of the duration of occurrence of abnormal data of the same type within a preset duration to the preset duration.

6. The vegetable transportation data management method according to claim 5, characterized in that: The management terminal determines to issue a vibration abnormality warning, an electromagnetic interference warning, or a transportation environment abnormality warning for the abnormal data, including: Determining to issue a vibration abnormality warning for the abnormal data according to a comparison result that a change rate of the abnormal data for issuing the abnormal warning is greater than or equal to a preset change rate; Determining to issue an electromagnetic interference warning for the abnormal data according to a comparison result that a change rate of the abnormal data for which the abnormal warning is issued is less than a preset change rate and that the abnormal data for which the abnormal warning is issued does not have abnormal associated data; According to the comparison result that the change rate of the abnormal data for issuing the abnormal warning is less than the preset change rate and the abnormal data for issuing the abnormal warning has abnormal associated data, a maximum difference analysis of the timestamps of the associated abnormal data is determined.

7. The vegetable transportation data management method according to claim 6, characterized in that: The determination of the abnormal associated data includes: Collect environmental parameter data monitored by sensors, including temperature, humidity, oxygen concentration, and abnormal warning data issued by sensors; Identify abnormal data points in the sensor data based on the above data, which data points indicate that environmental parameters are outside of a preset range or other abnormal conditions; Analyze the correlation between abnormal data points and determine the correlation rules between abnormal data; Extracting features associated with the abnormal data, the features including timestamps, sensor locations, and environmental parameter values; Based on the characteristics of the abnormal data and the correlation analysis results, the abnormal correlation data of the abnormal data is determined.

8. The vegetable transportation data management method according to claim 6, characterized in that: The determining of the maximum difference analysis of the timestamps of the associated abnormal data includes: Determining to issue a transportation environment abnormality warning for the abnormal data according to a comparison result in which the maximum difference of the timestamps of the associated abnormal data is greater than or equal to a preset difference; According to the comparison result that the maximum difference of the timestamps of the associated abnormal data is less than the preset difference, it is determined to issue an electromagnetic interference warning for the abnormal data.

9. The vegetable transportation data management method according to claim 8, characterized in that: When determining whether to adjust the parameters of the vegetable transportation data management process, it is determined that the vegetable transportation data management process parameters need to be adjusted based on the comparison result that the loss rate of vegetables after transportation is completed within a preset period is greater than or equal to the preset loss rate or the early warning efficiency is less than the preset early warning efficiency, wherein the vegetable transportation data management process parameters include a preset delay duration, a preset fluctuation frequency, a preset change rate and a preset difference.

10. The vegetable transportation data management method according to claim 9, characterized in that: The adjustment amount of the preset delay time is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset fluctuation frequency is negatively correlated with the loss rate of vegetables after the transportation is completed within the preset period, the adjustment amount of the preset change rate is positively correlated with the early warning effectiveness, and the adjustment amount of the preset difference is negatively correlated with the early warning effectiveness.

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