A monitoring and early warning method for cold chain logistics using smart phones

Abstract

The present invention discloses a monitoring and early warning method for cold chain logistics using a smart phone, which relates to the technical field of cold chain logistics, including obtaining the volume proportion of each type of goods to be transported in the cold chain logistics, the maximum storage temperature, the minimum storage temperature, the maximum humidity and the minimum humidity, calculating the initial transportation temperature W1 and the humidity S1, and setting the initial control environment conditions of the cold chain logistics. The real-time temperature and real-time humidity are obtained to calculate the real-time adjustment environment abnormality index, and an environmental adjustment abnormality warning is sent to the smart phone terminal; after receiving the environmental adjustment abnormality warning, the temperature and operating time of the temperature and humidity adjustment equipment are collected, the equipment temperature abnormality coefficient is calculated, the equipment operation is judged according to the equipment temperature abnormality coefficient, and the corresponding safety warning processing strategy is selected. Once the equipment temperature abnormality is found, the appropriate safety warning processing strategy can be quickly selected to reduce the impact on the cold chain logistics.

Description

Technical Field

[0001] The present invention relates to the technical field of cold chain logistics, and in particular to a monitoring and early warning method for cold chain logistics using a smart phone. Background Art

[0002] With the rapid development of modern logistics, cold chain logistics is becoming increasingly important as a key link to ensure the quality of high-value, perishable goods such as fresh food and pharmaceutical products. However, even slight fluctuations in environmental parameters during cold chain logistics may have a significant impact on the quality of goods. Therefore, the real-time monitoring and early warning of environmental parameters throughout the cold chain logistics process has become a technical challenge that the industry needs to solve urgently. Smartphones, as an indispensable tool in modern people's daily lives, have powerful computing and processing capabilities, rich sensor interfaces, and convenient mobile Internet connection functions, providing a new solution for cold chain logistics environmental monitoring.

[0003] In the Chinese invention application with application publication number CN114838767A, a temperature and humidity intelligent monitoring system and method for cold chain logistics is disclosed, which solves the technical problem in the prior art that the temperature and humidity range that affects the distribution cannot be accurately analyzed during the distribution process of cold chain logistics, resulting in reduced accuracy of numerical monitoring. The system performs real-time data analysis on the corresponding monitoring object to determine whether the temperature and humidity of the monitoring object during the current distribution process are normal, thereby analyzing whether the corresponding environment of the monitoring object has an impact on the distribution product, which is conducive to improving the eligibility and safety of the distribution and enhancing the distribution product.

[0004] Delivery quality; Conduct external impact analysis on the monitored object, and analyze in real time the impact of the external environment on the internal environment of the monitored object, thereby improving the accuracy of temperature and humidity monitoring, and at the same time enhancing the delivery qualification of the monitored object; Conduct benefit analysis on the monitoring of the monitored object, and analyze the efficiency of data monitoring in real time.

[0005] In the above invention application, real-time data analysis is performed on the corresponding monitoring object to determine whether the temperature and humidity of the monitoring object during the current distribution process are normal, so as to analyze whether the corresponding environment of the monitoring object has an impact on the distribution product. However, in the cold chain logistics process, human factors (such as improper operation, negligence, etc.) or abnormal equipment operation may also affect the monitoring results.

[0006] To this end, the present invention provides a monitoring and early warning method for cold chain logistics using a smart phone. Summary of the invention

[0007] In view of the shortcomings of the prior art, the present invention provides a monitoring and early warning method for cold chain logistics using a smart phone. The present invention obtains the volume proportion of each type of cold chain logistics to be transported. , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity , calculate the real-time adjustment environment abnormality index , sends an environmental adjustment abnormality warning to the smartphone. After receiving the environmental adjustment abnormality warning, the temperature and operating time of the temperature and humidity adjustment equipment are collected, the equipment temperature abnormality coefficient Sw is calculated, and the equipment operation is judged based on the equipment temperature abnormality coefficient Sw. And the corresponding safety warning processing strategy is selected, which can more accurately locate the source of the environmental adjustment abnormality. Once the equipment temperature abnormality is found, the appropriate safety warning processing strategy can be quickly selected, such as issuing an emergency shutdown command, switching to backup equipment, etc., to restore normal temperature and humidity control as quickly as possible, reduce the impact on cold chain logistics, and thus solve the technical problems recorded in the background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A monitoring and early warning method for cold chain logistics using a smart phone, comprising the following steps:

[0009] Get the volume ratio of each type of goods to be transported in cold chain logistics , Storage Maximum Temperature Minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity ;

[0010] Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors , Real-time change rate and real-time variance , combined with the cold chain logistics transportation time Ys to calculate the real-time adjustment of the environmental abnormality index , sending abnormal warning of environmental adjustment to the smartphone;

[0011] After receiving the abnormal environmental adjustment warning, the temperature and operating time of the temperature and humidity adjustment equipment are collected, the equipment temperature abnormality coefficient Sw is calculated, the equipment operation is judged based on the equipment temperature abnormality coefficient Sw, and the corresponding safety warning processing strategy is selected.

[0012] Furthermore, the volume ratio of each type of goods to be transported in the cold chain logistics is obtained. , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transportation temperature W1 and humidity S1:

[0013] in, a Indicates the sequence number of each type of cold chain logistics cargo to be transported. a =1, 2, …, m .

[0014] Furthermore, the initial transport temperature W1 and humidity S1 are used as the initial control environment conditions for the cold chain logistics, the temperature and humidity adjustment equipment is started, and the temperature and humidity sensors are used to periodically detect the real-time temperature of the cold chain logistics. and real-time humidity . Temperature and humidity regulating equipment includes refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment.

[0015] Furthermore, the decay period of each cargo at different temperatures and humidities was determined through decay experiments, and the Pearson correlation coefficient between temperature and humidity and the decay period was calculated, which was recorded as the decay factor. f1, f2 .

[0016] The decay test is to prepare enough cargo samples and ensure that there are enough samples for repeated experiments under each temperature and humidity condition. During the experiment, the appearance, smell, texture and other sensory characteristics of the cargo are regularly observed and the data are recorded.

[0017] The collected data are analyzed using statistical software or data analysis methods to determine the decay period of the goods at different temperatures and humidity.

[0018] The Pearson Correlation Coefficient, also known as the Pearson product-moment correlation coefficient (PPMCC or PCCs), is a statistic proposed by British mathematician Karl Pearson to measure the degree of linear correlation between two variables. Its value range is between -1 and 1. The closer the absolute value is to 1, the stronger the linear relationship between the two variables.

[0019] Further, get the real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors : in, i Indicates the time sequence number of real-time temperature or real-time humidity data. i =1, 2, …, n .

[0020] Furthermore, according to the real-time adjustment error Calculate real-time rate of change and real-time variance : And count all the real-time change rates and real-time variances after the cold chain logistics starts to transport, and get the average change rate of this cold chain logistics and the mean variance .

[0021] Furthermore, a timer is used to obtain the transportation time Ys of cold chain logistics, combined with real-time adjustment error , Real-time change rate and real-time variance , calculate the real-time adjustment environment abnormality index :

[0022]

[0023] in, The estimated transportation time of this cold chain logistics is obtained by inputting the transportation starting point into the navigation software. is the adjustment error threshold, taking the mean of all real-time adjustment errors, is the change rate threshold, taking the average of all real-time change rates, is the variance threshold, taking the mean of all real-time variances.

[0024] Furthermore, when the environmental abnormality index is adjusted in real time Exceed When the cold chain logistics storage environment is abnormal, it indicates that the abnormal environment adjustment is abnormal, and an environmental adjustment abnormality warning is sent to the smartphone.

[0025] Furthermore, after receiving the abnormal warning of environmental adjustment, the temperature sensors are used to collect the temperatures T1, T2, T3 and T4 of the refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment respectively, and the operation time Sc1, Sc2, Sc3 and Sc4 of each equipment in the cold chain logistics process is obtained according to the equipment operation records, and the equipment temperature weights k1, k2, k3 and k4 are calculated:

[0026]

[0027] The calculation formulas for the corresponding device temperature weights k1, k2, k3 and k4 are as above.

[0028] Furthermore, the temperatures T1, T2, T3, T4, and the equipment temperature weights k1, k2, k3, and k4 of the refrigeration equipment, heating equipment, humidification equipment, and dehumidification equipment are obtained, and the equipment temperature anomaly coefficient Sw is calculated:

[0029]

[0030] in, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, It is the normal operating temperature of the refrigeration equipment.

[0031] Furthermore, the device temperature anomaly coefficient Sw is obtained, the device operation is judged according to the device temperature anomaly coefficient Sw, and the corresponding safety warning processing strategy is selected, specifically:

[0032] When Sw When the device is running normally, it will provide feedback that all devices are running normally and no action is needed. Just continue to monitor to prevent any abnormal situation.

[0033] when When the device is operating abnormally, it will report that the device is operating abnormally and send a secondary safety warning command to the smartphone to adjust the device operating parameters or take other cooling measures.

[0034] when When multiple devices are found to be operating abnormally, a first-level safety warning command is sent to the smartphone, which immediately stops the device for inspection and eliminates safety hazards.

[0035] in, It is the average value of the temperature anomaly coefficient Sw of all devices.

[0036] (III) Beneficial effects

[0037] The present invention provides a monitoring and early warning method for cold chain logistics using a smart phone, which has the following beneficial effects:

[0038] 1. Obtain the volume ratio of each type of goods to be transported in the cold chain logistics , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity , you can set the transportation temperature and humidity suitable for all goods, thereby minimizing the risk of goods being damaged by environmental changes. This is especially important for perishable foods such as meat, seafood, vegetables and fruits, because inappropriate temperature and humidity will cause rapid decay.

[0039] 2. Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors , Real-time change rate and real-time variance , combined with the cold chain logistics transportation time Ys to calculate the real-time adjustment of the environmental abnormality index , sending environmental adjustment abnormal warnings to smartphones can promptly detect and deal with potential environmental problems, reduce the risk of cargo damage or decay, and help managers optimize cold chain logistics processes and improve transportation efficiency and quality.

[0040] 3. After receiving the abnormal environmental adjustment warning, collect the temperature and operating time of the temperature and humidity adjustment equipment, calculate the equipment temperature abnormality coefficient Sw, make a judgment on the equipment operation based on the equipment temperature abnormality coefficient Sw, and select the corresponding safety warning processing strategy, which can more accurately locate the source of the abnormal environmental adjustment. Once the equipment temperature is abnormal, it can quickly select the appropriate safety warning processing strategy, such as issuing an emergency shutdown command, switching to backup equipment, etc., to restore normal temperature and humidity control as quickly as possible and reduce the impact on cold chain logistics. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention is a flow chart of a method for monitoring and early warning cold chain logistics using a smart phone. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] See also Figure 1 The present invention provides a monitoring and early warning method for cold chain logistics using a smart phone, comprising the following steps:

[0044] Step 1: Obtain the volume ratio of each type of goods to be transported in the cold chain logistics , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity .

[0045] The step 1 includes the following contents:

[0046] Step 101: Obtain the volume ratio of each type of cold chain logistics cargo to be transported based on the cold chain logistics management data, the standards and specifications of the cold chain logistics industry , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transportation temperature W1 and humidity S1:

[0047]

[0048] in, a Indicates the sequence number of each type of cold chain logistics cargo to be transported. a =1, 2, …, m .

[0049] Step 102: Use the initial transport temperature W1 and humidity S1 as the initial control environment conditions for the cold chain logistics, start the temperature and humidity adjustment equipment, and use the temperature and humidity sensors to periodically detect the real-time temperature of the cold chain logistics. and real-time humidity . Temperature and humidity regulating equipment includes refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment.

[0050] When using, combine the contents in steps 101 and 102:

[0051] Get the volume ratio of each type of goods to be transported in cold chain logistics , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity , you can set the transportation temperature and humidity suitable for all goods, thereby minimizing the risk of goods being damaged by environmental changes. This is especially important for perishable foods such as meat, seafood, vegetables and fruits, because inappropriate temperature and humidity will cause rapid decay.

[0052] Step 2: Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors , Real-time change rate and real-time variance , combined with the cold chain logistics transportation time Ys to calculate the real-time adjustment of the environmental abnormality index , sending abnormal environmental adjustment warnings to smartphones.

[0053] The step 2 includes the following contents:

[0054] Step 201: Determine the decay period of each type of cargo at different temperatures and humidities through decay experiments, calculate the Pearson correlation coefficient between temperature and humidity and the decay period, and record it as the decay factor. f1, f2 .

[0055] The decay test is to prepare enough cargo samples and ensure that there are enough samples for repeated experiments under each temperature and humidity condition. During the experiment, the appearance, smell, texture and other sensory characteristics of the cargo are regularly observed and the data are recorded.

[0056] The collected data are analyzed using statistical software or data analysis methods to determine the decay period of the goods at different temperatures and humidity.

[0057] The Pearson Correlation Coefficient, also known as the Pearson product-moment correlation coefficient (PPMCC or PCCs), is a statistic proposed by British mathematician Karl Pearson to measure the degree of linear correlation between two variables. Its value range is between -1 and 1. The closer the absolute value is to 1, the stronger the linear relationship between the two variables.

[0058] Step 202: Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors :

[0059]

[0060] in, i Indicates the time sequence number of real-time temperature or real-time humidity data. i =1, 2, …, n .

[0061] Step 203: Adjust the error in real time Calculate real-time rate of change and real-time variance :

[0062]

[0063] And count all the real-time change rates and real-time variances after the cold chain logistics starts to transport, and get the average change rate of this cold chain logistics and the mean variance .

[0064] Step 204: Use a timer to obtain the cold chain logistics transportation time Ys, and adjust the error in real time , Real-time change rate and real-time variance , calculate the real-time adjustment environment abnormality index :

[0065]

[0066] in, The estimated transportation time of this cold chain logistics is obtained by inputting the transportation starting point into the navigation software. is the adjustment error threshold, taking the mean of all real-time adjustment errors, is the change rate threshold, taking the average of all real-time change rates, is the variance threshold, taking the mean of all real-time variances.

[0067] Step 205: When real-time adjustment of environmental abnormality index Exceed When the cold chain logistics storage environment is abnormal, it indicates that the abnormal environment adjustment is abnormal, and an environmental adjustment abnormality warning is sent to the smartphone.

[0068] When using, combine the contents in steps 201 to 205:

[0069] Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors , Real-time change rate and real-time variance , combined with the cold chain logistics transportation time Ys to calculate the real-time adjustment of the environmental abnormality index , sending environmental adjustment abnormal warnings to smartphones can promptly detect and deal with potential environmental problems, reduce the risk of cargo damage or decay, and help managers optimize cold chain logistics processes and improve transportation efficiency and quality.

[0070] Step 3: After receiving the abnormal environmental adjustment warning, collect the temperature and operating time of the temperature and humidity adjustment equipment, calculate the equipment temperature abnormality coefficient Sw, make a judgment on the equipment operation based on the equipment temperature abnormality coefficient Sw, and select the corresponding safety warning processing strategy.

[0071] The step three includes the following contents:

[0072] Step 301: After receiving the abnormal warning of environmental adjustment, use temperature sensors to collect the temperatures T1, T2, T3 and T4 of the refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment respectively, and obtain the operation time Sc1, Sc2, Sc3 and Sc4 of each equipment in the cold chain logistics process according to the equipment operation record, and calculate the equipment temperature weights k1, k2, k3 and k4:

[0073]

[0074] The calculation formulas for the corresponding device temperature weights k1, k2, k3 and k4 are as above.

[0075] Step 302: Obtain the temperatures T1, T2, T3, T4, and the device temperature weights k1, k2, k3, and k4 of the refrigeration device, heating device, humidification device, and dehumidification device, and calculate the device temperature anomaly coefficient Sw:

[0076]

[0077] in, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, It is the normal operating temperature of the refrigeration equipment.

[0078] Step 303: Obtain the device temperature anomaly coefficient Sw, make a judgment on the device operation based on the device temperature anomaly coefficient Sw, and select a corresponding safety warning processing strategy, specifically:

[0079] When Sw When the device is running normally, it will provide feedback that all devices are running normally and no action is needed. Just continue to monitor to prevent any abnormal situation.

[0080] when When the device is operating abnormally, it will report that the device is operating abnormally and send a secondary safety warning command to the smartphone to adjust the device operating parameters or take other cooling measures.

[0081] when When multiple devices are found to be operating abnormally, a first-level safety warning command is sent to the smartphone, which immediately stops the device for inspection and eliminates safety hazards.

[0082] in, It is the average value of the temperature anomaly coefficient Sw of all devices.

[0083] When using, combine the contents in steps 301 to 303:

[0084] After receiving the abnormal environmental adjustment warning, the temperature and operating time of the temperature and humidity adjustment equipment are collected, the equipment temperature abnormality coefficient Sw is calculated, the equipment operation is judged based on the equipment temperature abnormality coefficient Sw, and the corresponding safety warning processing strategy is selected. It can more accurately locate the source of the abnormal environmental adjustment. Once the equipment temperature is abnormal, it can quickly select the appropriate safety warning processing strategy, such as issuing an emergency shutdown command, switching to backup equipment, etc., to restore normal temperature and humidity control as quickly as possible and reduce the impact on cold chain logistics.

[0085] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for monitoring and early warning of cold chain logistics using a smart phone, characterized in that: The steps include: Get the volume ratio of each type of goods to be transported in cold chain logistics , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transport temperature W1 and humidity S1, set the initial control environment conditions for cold chain logistics, start the temperature and humidity adjustment equipment, and detect the real-time temperature of cold chain logistics and real-time humidity ; Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors , Real-time change rate and real-time variance , combined with the cold chain logistics transportation time Ys to calculate the real-time adjustment of the environmental abnormality index , sending abnormal warning of environmental adjustment to the smartphone; Use the timer to obtain the transportation time Ys of cold chain logistics, combined with real-time adjustment error , Real-time change rate and real-time variance , calculate the real-time adjustment environment abnormality index : in, The estimated transportation time of this cold chain logistics is obtained by inputting the transportation starting point into the navigation software. is the adjustment error threshold, taking the mean of all real-time adjustment errors, is the change rate threshold, taking the average of all real-time change rates, is the variance threshold, taking the mean of all real-time variances; When adjusting the environmental abnormality index in real time Exceed When the cold chain logistics storage environment is abnormal, an abnormal environment adjustment warning is sent to the smartphone. After receiving the abnormal warning of environmental adjustment, the temperature and operation time of the temperature and humidity adjustment equipment are collected, the temperature abnormality coefficient Sw of the equipment is calculated, the operation of the equipment is judged according to the temperature abnormality coefficient Sw of the equipment, and the corresponding safety warning processing strategy is selected; Get the temperatures T1, T2, T3, T4, equipment temperature weights k1, k2, k3 and k4 of the refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment, and calculate the equipment temperature anomaly coefficient Sw: in, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, is the normal operating temperature of the refrigeration equipment, It is the normal operating temperature of the refrigeration equipment.

2. According to claim 1, a method for monitoring and early warning of cold chain logistics using a smart phone is characterized by: Get the volume ratio of each type of goods to be transported in cold chain logistics , Storage Maximum Temperature , minimum temperature , maximum humidity and minimum humidity , calculate the initial transportation temperature W1 and humidity S1: in, a Indicates the sequence number of each type of cold chain logistics cargo to be transported. a =1, 2, …, m .

3. According to claim 2, a method for monitoring and early warning of cold chain logistics using a smart phone is characterized in that: Get real-time temperature , Real-time humidity , decay factor f1, f2, Initial transport temperature W1 and humidity S1, analysis of real-time adjustment errors : in, i Indicates the time sequence number of real-time temperature or real-time humidity data. i =1, 2, …, n .

4. The method for monitoring and early warning of cold chain logistics using a smart phone according to claim 3, characterized in that: Adjust the error in real time Calculate real-time rate of change and real-time variance : And count all the real-time change rates and real-time variances after the cold chain logistics starts to transport, and get the average change rate of this cold chain logistics and the mean variance .

5. According to claim 1, a method for monitoring and early warning of cold chain logistics using a smart phone is characterized by: After receiving the abnormal environmental adjustment warning, the temperature sensors are used to collect the temperatures T1, T2, T3 and T4 of the refrigeration equipment, heating equipment, humidification equipment and dehumidification equipment respectively, and the operation time Sc1, Sc2, Sc3 and Sc4 of each equipment in the cold chain logistics process is obtained according to the equipment operation records, and the equipment temperature weights k1, k2, k3 and k4 are calculated: The calculation formulas for the corresponding device temperature weights k1, k2, k3 and k4 are as above.

6. The method for monitoring and early warning of cold chain logistics using a smart phone according to claim 1, characterized in that: Obtain the device temperature anomaly coefficient Sw, make a judgment on the device operation based on the device temperature anomaly coefficient Sw, and select the corresponding safety warning processing strategy, specifically: when When the device is running normally, it will be reported that no action is needed. when When the device is abnormal, it will send a secondary safety warning command to the smartphone. when When multiple devices are abnormal, a first-level safety warning command is issued to the smartphone. in, It is the average value of the temperature anomaly coefficient Sw of all devices.

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