Intelligent logistics data acquisition method and system

Abstract

The invention relates to the technical field of intelligent logistics, and discloses an intelligent logistics data acquisition method and system, and the method comprises the steps: determining the information of an object pet, collecting the data of the object pet through a detection unit, uploading the related information to a cloud end, detecting the environment parameters in a pet consignment process through the detection unit, setting an environment stability index, and carrying out the collection of the environment stability index. The method comprises the following steps of: establishing an environment stability index for pet consignment environment change, determining a calm heart rate according to a pet object, normalizing the data, obtaining the influence weight of the heart rate and the environment stability index on the heart rate of the pet when the pet is calm, and obtaining the predicted heart rate of the pet by constructing a weighted average formula. The environment stability index and the calm heart rate of the object pet are combined, the change of the heart rate of the pet is predicted, logistics personnel are assisted to take care of the pet, the working intensity of the logistics personnel is reduced, and the pet obtains a good consignment environment.

Description

Technical Field

[0001] The present invention relates to the field of smart logistics technology, and specifically to a smart logistics data collection method and system. Background Art

[0002] Smart logistics refers to a modern logistics model that uses intelligent technologies such as smart software and hardware, the Internet of Things, and big data to achieve refined, dynamic, and visual management of all aspects of logistics, improve the intelligent analysis and decision-making and automated operation execution capabilities of the logistics system, and enhance the efficiency of logistics operations. Pet consignment is part of logistics. Nowadays, more and more people are raising pets in society. Pets are not only people's property, but also their spiritual sustenance.

[0003] In the link of pet consignment in logistics, the existing monitoring can only be used to monitor the status of the pet. When observing the status of the pet, only the surface physiological status of the pet can be obtained, and the psychological and physiological status of the pet cannot be fundamentally judged. It is necessary to measure the heart rate in combination with a heart rate meter, and judge the status of the pet based on the monitoring image and the heart rate value. For example, in the Chinese invention patent with application number CN115104548B, a pet behavior adjustment and human-pet interaction method and device based on multimedia information technology are disclosed. Specifically, the sound collection unit and the sensor unit in the pet collar are started according to the pet behavior monitoring instruction, and the pet heart rate tested by the heart rate sensor and the pet temperature obtained by the temperature sensor are judged in real time whether they meet the health conditions, which solves the problem that the current intelligent interaction technology and devices lack judgment on the needs of pets.

[0004] However, during the shipping process, the heart rate monitor must be tied to the pet in real time. Different binding strengths will cause mental stress to the pet. At the same time, the pet may break free from the heart rate monitor during shipping, and some types of pets are not suitable for wearing the monitor for a long time. All of the above factors have become obstacles to caring for pets during shipping, and a good pet shipping environment cannot be created. Once an accident occurs to the pet, logistics personnel cannot provide timely treatment and treatment. At the same time, they cannot predict the pet's physiological state based on environmental factors and cannot make judgments in advance. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the deficiencies in the prior art, the present invention provides a smart logistics data collection method and system, which predicts changes in the pet's heart rate based on changes in the pet's shipping environment, assists logistics personnel in taking care of the pet, and provides the pet with a good shipping environment.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a smart logistics data collection method, comprising the following steps:

[0009] Determine the information of the target pet, collect the data of the target pet through the detection unit, and upload the relevant information to the cloud, and record the pet owner's soothing voice to the cloud; wherein, the heart rate of the pet when it is calm is detected through a time period, and the calm heart rate value PB is obtained, and the type, gender and weight information of the pet are stored in the server cloud;

[0010] The environmental parameters of the pet during consignment are detected by the detection unit, including the acceleration A of the current consignment carrier, the temperature T and the noise DB in the consignment device. According to the parameter changes of acceleration A, temperature T and noise DB in continuous time, the heart rate at the same time is detected. By analyzing the relationship between environmental parameters and the heart rate of the pet, a mathematical model of the environmental stability index is established;

[0011] Obtain the threshold of the environmental stability index PL when the pet is panicked, set it as the environmental threshold P1, collect the parameters of the current consignment environment, obtain the value of the current environmental stability index PL through the formula, evaluate the relationship between the environmental stability index PL and the environmental threshold P1 and provide feedback;

[0012] By collecting the data of the pet's calm heart rate PB and calculating the environmental stability index PL in the current consignment environment, the weights of the pet's calm heart rate PB and the environmental stability index PL on the pet's heart rate are obtained through data normalization, and the pet's predicted heart rate PM is obtained by constructing a weighted average formula, and the panic threshold P2 of the heart rate when the pet is panicked is obtained in advance, and the relationship between the pet's predicted heart rate PM and the panic threshold P2 is evaluated and fed back;

[0013] The environmental stability index PL during pet consignment is adjusted through an optimization algorithm, and measures are taken to soothe the pet, so that the pet's predicted heart rate PM shows favorable changes.

[0014] Preferably, under the environment where the temperature T and the noise DB parameters remain unchanged, the detection unit Detect acceleration A in a time period to obtain a data set of acceleration A and a corresponding data set of heart rate values;

[0015] Under the environment where the acceleration A and temperature T parameters remain unchanged, the detection unit The noise DB is detected in a time period to obtain a data set of the noise DB and a corresponding data set of heart rate values;

[0016] Under the condition that the acceleration A and noise DB parameters remain unchanged, the detection unit The temperature T is detected in a time period to obtain a data set of temperature T and a corresponding data set of heart rate values, and the mathematical relationship between the above parameter change values ​​and the heart rate value change values ​​is analyzed using the hierarchical analysis method.

[0017] Preferably, an environmental stability index PL is set, and the environmental stability index PL is related to the parameters in the shipping environment. After normalizing and cleaning the above environmental parameter data, the weight coefficients of acceleration A, temperature T and noise DB are obtained, which are respectively , After dimensionless processing, the correlation formula between the environmental stability index PL and the above parameters is as follows:

[0018] ;

[0019] in, , , , , is the constant correction factor, 0.74 1.81.

[0020] Preferably, before shipping, the pet is calmed by soothing it. At this time, the heart rate is detected by the detection unit according to a preset period to obtain a set of heart rate values. The average is calculated based on this set of values ​​to obtain the average heart rate PB in the calm state.

[0021] Preferably, the pet's predicted heart rate PM evaluation is associated with the environmental stability index PL and the pet's calm heart rate PB, and the association formula is as follows:

[0022] ;

[0023] in, and are the weight coefficients of the environmental stability index PL and the pet's calm heart rate PB, , , is the constant correction factor, 5.38 9.62, compare the pet's predicted heart rate PM with the pet's panic heart rate threshold PP and provide feedback on the result.

[0024] Preferably, the predicted heart rate PM value is calculated, and the heart rate panic threshold P2 is pre-set by observing the pet's state and detecting the pet's heart rate, and is divided into a first panic threshold and a second panic threshold according to the situation, wherein the heart rate panic threshold P2 Second panic threshold;

[0025] When the heart rate panic threshold P2 The first panic threshold indicates that the pet's heart rate is expected to rise and it will panic. The situation is medium-urgent and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment.

[0026] When the second panic threshold Predicted heart rate PM means that the pet's heart rate is expected to rise and it will panic. The situation is serious and urgent, and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment;

[0027] When the predicted heart rate PM When the heart rate panic threshold is P2, it means that the pet's heart rate is expected to be good, and a feedback instruction is issued to remind the logistics personnel to maintain the current consignment environment.

[0028] Preferably, At time intervals, information on environmental parameters is collected periodically to obtain continuous environmental stability index values ​​PL sorted by time. By obtaining continuous predicted heart rate PM values, the values ​​of predicted heart rate PM values ​​higher than the heart rate panic threshold P2 are recorded as abnormal values. The continuous time of abnormal values ​​of the predicted heart rate PM is counted and recorded as the crisis time KT. Combined with the duration of the crisis time KT and the physiological state of the pet, the results are evaluated and fed back.

[0029] Preferably, the heart rate panic threshold PP is set The duration of the predicted heart rate PM is the crisis time KT. The pet panic tolerance time is set in advance according to the pet's basic physiological information and registered as the first time , Second Time and the third time ,

[0030] when Crisis Time KT Second time , the warning is evaluated and fed back as a first-level crisis, indicating that the pet's condition is a mild emergency;

[0031] when Crisis Time KT The third time , the warning is evaluated and fed back as a second-level crisis, indicating that the pet's situation is moderately urgent;

[0032] when Crisis time KT, the assessment and feedback warning is the third level crisis, indicating that the pet's condition is severely urgent.

[0033] Preferably, the warning priority generated by the crisis time KT is greater than the warning priority generated by the environmental stability index PL. After the warning feedback, the value of the temperature T is changed by an external temperature control device, the acceleration A of the vehicle is changed, the propagation of noise is changed by an external sound insulation device, and the pet owner's soothing voice is played, so that the pet's predicted heart rate PM is close to or equal to the heart rate mean PB.

[0034] To achieve the above objectives, the present invention is implemented through the following technical solutions: a smart logistics data collection system, including a detection unit, a processing unit and an execution unit;

[0035] The detection unit includes an acceleration module, a temperature module, a noise module and a heart rate module, wherein the acceleration module is used to collect the acceleration of the consignment carrier, the temperature module is used to collect the consignment environment temperature T, the noise module is used to collect the consignment environment noise DB, and the heart rate module is used to collect the pet's calm heart rate PB and heart rate panic threshold P2;

[0036] The processing unit includes a data analysis module and a calculation module. The data analysis module is used to analyze the data detected by the detection unit. The calculation module is used to clean, normalize and calculate the collected data and transmit the results to the execution unit.

[0037] The execution unit includes a control module and an early warning module. The control module is used to control the audio player, the external temperature control device and the external sound insulation device. The early warning module is used to transmit an early warning signal to the mobile terminal of the logistics personnel.

[0038] (III) Beneficial effects

[0039] The present invention provides a method having the following beneficial effects:

[0040] (1) The present invention independently detects the temperature, vehicle acceleration and noise parameter information in the consignment device before the pet is consigned, as well as the changes in the heart rate of the pet at the corresponding environmental parameters, to obtain the influence of the environmental parameters on the heart rate of the pet. During the consignment process, by setting the environmental threshold, the parameters of the current consignment environment are collected to obtain the environmental stability index, and the environmental stability index is evaluated with the environmental threshold to achieve the effect of predicting the rise and fall of the pet's heart rate, so that the logistics personnel can obtain the rise and fall trend of the pet's heart rate in advance, ensuring that the logistics personnel can handle it in time, ensuring that the pet can be well taken care of, and ensuring a good consignment environment for the pet.

[0041] (2) The present invention detects and observes the heart rate threshold of the pet when it is frightened in advance, predicts the heart rate of the pet by using the environmental stability coefficient and the pet's calm heart rate, and compares the predicted heart rate with the heart rate threshold of the pet when it is frightened. This can more intuitively analyze the current physiological state of the pet. According to the changes in environmental parameters and the changes in heart rate, logistics personnel can adjust the shipping environment in a targeted manner to achieve the effects of fast speed, strong targeting and high efficiency.

[0042] (3) By calculating the time when the pet's heart rate is predicted to be at an abnormal value, the crisis time is deduced, the crisis time is judged, and a warning signal is issued according to the situation, so that pets in abnormal conditions can get help in time. It can also avoid the impact of changes in pet heart rate caused by short-term environmental changes on logistics personnel, thereby reducing the workload of logistics personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of a flow chart of a smart logistics data collection method of the present invention;

[0044] Figure 2 This is a structural schematic diagram of an intelligent logistics data collection system of the present invention. DETAILED DESCRIPTION

[0045] 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.

[0046] See also Figure 1 The present invention provides a smart logistics data collection method, comprising the following steps:

[0047] Determine the information of the target pet, collect the data of the target pet through the detection unit, and upload the relevant information to the cloud, and record the pet owner's soothing voice to the cloud; wherein, the heart rate of the pet when it is calm is detected through a time period, and the calm heart rate value PB is obtained, and the type, gender and weight information of the pet are stored in the server cloud;

[0048] The environmental parameters of the pet during consignment are detected by the detection unit, including the acceleration A of the current consignment carrier, the temperature T and the noise DB in the consignment device. According to the parameter changes of acceleration A, temperature T and noise DB in continuous time, the heart rate at the same time is detected. By analyzing the relationship between environmental parameters and the heart rate of the pet, a mathematical model of the environmental stability index is established;

[0049] Obtain the threshold of the environmental stability index PL when the pet is panicked, set it as the environmental threshold P1, collect the parameters of the current consignment environment, obtain the value of the environmental stability index PL through the formula, evaluate the relationship between the environmental stability index PL and the environmental threshold P1 and provide feedback;

[0050] By collecting the data of the pet's calm heart rate PB and calculating the environmental stability index PL in the current consignment environment, the weights of the pet's calm heart rate PB and the environmental stability index PL on the pet's heart rate are obtained through data normalization, and the pet's predicted heart rate PM is obtained by constructing a weighted average formula, and the panic threshold P2 of the heart rate when the pet is panicked is obtained in advance, and the relationship between the pet's predicted heart rate PM and the panic threshold P2 is evaluated and fed back;

[0051] The environmental stability index PL during pet consignment is adjusted through an optimization algorithm, and measures are taken to soothe the pet, so that the pet's predicted heart rate PM shows favorable changes.

[0052] Under the environment where the temperature T and noise DB parameters remain unchanged, the detection unit Detect acceleration A in a time period to obtain a data set of acceleration A and a corresponding data set of heart rate values;

[0053] Under the environment where the acceleration A and temperature T parameters remain unchanged, the detection unit The noise DB is detected in a time period to obtain a data set of the noise DB and a corresponding data set of heart rate values;

[0054] Under the condition that the acceleration A and noise DB parameters remain unchanged, the detection unit The temperature T is detected in a time period to obtain a data set of temperature T and a corresponding data set of heart rate values, and the mathematical relationship between the above parameter change values ​​and the heart rate value change values ​​is analyzed using the hierarchical analysis method.

[0055] The environmental stability index PL is set. The environmental stability index PL is related to the parameters in the shipping environment. After normalizing and cleaning the above environmental parameter data, the weight coefficients of acceleration A, temperature T and noise DB are obtained, which are respectively , After dimensionless processing, the correlation formula between the environmental stability index PL and the above parameters is as follows:

[0056] ;

[0057] in, , , , , is the constant correction factor, 0.74 1.81.

[0058] Before shipping, the pet is calmed by soothing it. The heart rate is detected by the detection unit according to a preset period to obtain a set of heart rate values. The average is calculated based on this set of values ​​to obtain the average heart rate PB in the calm state.

[0059] The pet's predicted heart rate PM assessment is associated with the environmental stability index PL and the pet's calm heart rate PB, and the correlation formula is as follows:

[0060] ;

[0061] in, and are the weight coefficients of the environmental stability index PL and the pet's calm heart rate PB, , 1.33, is the constant correction factor, 5.38 9.62, compare the pet's predicted heart rate PM with the pet's panic heart rate threshold PP and provide feedback on the result.

[0062] Calculate the predicted heart rate PM value, and pre-set the heart rate panic threshold P2 by observing the pet's state and detecting the pet's heart rate. According to the situation, it is divided into the first panic threshold and the second panic threshold. Among them, the heart rate panic threshold P2 First panic threshold Second panic threshold;

[0063] When the heart rate panic threshold P2 Predicted heart rate PM The first panic threshold indicates that the pet's heart rate is expected to rise and it will panic. The situation is medium-urgent and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment.

[0064] When the second panic threshold Predicted heart rate PM means that the pet's heart rate is expected to rise and it will panic. The situation is serious and urgent, and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment;

[0065] When the predicted heart rate PM When the heart rate panic threshold is P2, it means that the pet's heart rate is expected to be good, and a feedback instruction is issued to remind the logistics personnel to maintain the current consignment environment.

[0066] by At time intervals, information on environmental parameters is collected periodically to obtain continuous environmental stability index values ​​PL sorted by time. By obtaining continuous predicted heart rate PM values, the values ​​of predicted heart rate PM values ​​higher than the heart rate panic threshold P2 are recorded as abnormal values. The continuous time of abnormal values ​​of the predicted heart rate PM is counted and recorded as the crisis time KT. Combined with the duration of the crisis time KT and the physiological state of the pet, the results are evaluated and fed back.

[0067] Set the heart rate panic threshold PP The duration of the predicted heart rate PM is the crisis time KT. The pet panic tolerance time is set in advance according to the pet's basic physiological information and registered as the first time , Second Time and the third time ,

[0068] when Crisis Time KT Second time , the warning is evaluated and fed back as a first-level crisis, indicating that the pet's condition is a mild emergency;

[0069] when Crisis Time KT The third time , the warning is evaluated and fed back as a second-level crisis, indicating that the pet's situation is moderately urgent;

[0070] when Crisis time KT, the assessment and feedback warning is the third level crisis, indicating that the pet's condition is severely urgent.

[0071] The warning priority generated by the crisis time KT is greater than the warning priority generated by the environmental stability index PL. After the warning feedback, the value of the temperature T is changed through the external temperature control device, the acceleration A of the vehicle is changed, the propagation of the noise is changed through the external sound insulation device, and the pet owner's soothing voice is played, so that the pet's predicted heart rate PM is close to or equal to the heart rate mean PB.

[0072] See also Figure 2 ,The present invention provides a smart logistics data collection system, including a detection unit, a processing unit and an execution unit;

[0073] The detection unit includes an acceleration module, a temperature module, a noise module and a heart rate module, wherein the acceleration module is used to collect the acceleration of the consignment carrier, the temperature module is used to collect the consignment environment temperature T, the noise module is used to collect the consignment environment noise DB, and the heart rate module is used to collect the pet's calm heart rate PB and heart rate panic threshold P2;

[0074] The processing unit includes a data analysis module and a calculation module. The data analysis module is used to analyze the data detected by the detection unit. The calculation module is used to clean, normalize and calculate the collected data and transmit the results to the execution unit.

[0075] The execution unit includes a control module and an early warning module. The control module is used to control the audio player, the external temperature control device and the external sound insulation device. The early warning module is used to transmit early warning signals to the mobile terminal of the logistics personnel.

[0076] Before shipping, the logistics staff will record the pet's type, gender and weight information, calm the pet down first, and use a heart rate monitor to detect multiple sets of heart rates of the pet within a continuous period of time. The average value is used to obtain the calm heart rate value PB, and the above data information is uploaded to the server cloud for subsequent use or reference by pets with the same information; environmental parameters include three parameters: vehicle acceleration A, ambient temperature T and ambient noise DB. Before shipping, the environmental parameters are periodically detected over time, and two of the parameters are kept unchanged, while the other parameter is changed, and the corresponding heart rate changes are recorded. The degree of influence of the above three data on the heart rate is obtained through data normalization and data cleaning, and the weight coefficient is obtained after tempering. The environmental stability coefficient is obtained according to the weighted average algorithm, and the heart rate threshold of the pet when it is panicked is obtained by observing the pet's state and heart rate value, and it is divided into the first A panic threshold and a second panic threshold are set, and the above information is recorded in the server. During the consignment process, there is no need for the pet to wear a heart rate monitor. By detecting environmental parameters and combining external image monitoring technology, the pet's heart rate changes can be inferred. When the predicted heart rate PM is abnormal, the logistics personnel control the temperature in the environment through an external temperature control device, and soundproof the consignment environment through an external sound insulation device. By controlling the stability of the consignment vehicle, the acceleration change is reduced, and the pet can be soothed by playing the pet owner's soothing voice. By counting the duration of the pet's predicted heart rate abnormal value, it is recorded as the crisis time KT. When the crisis time KT is too long, the early warning module will give priority to feedback such warnings to the logistics personnel, so that the logistics personnel can check the corresponding pets first and take corresponding measures to achieve fast and more efficient care of the pets and provide the pets with a good consignment environment.

[0077] The analytic hierarchy process, referred to as AHP, is a decision-making method that decomposes elements related to decision-making into levels such as goals, criteria, and plans, and then conducts qualitative and quantitative analysis. This method is particularly suitable for target systems with hierarchical and staggered evaluation indicators, and decision-making problems whose target values ​​are difficult to describe quantitatively.

[0078] The core of the hierarchical analysis method is to decompose complex decision-making problems into different hierarchical structures, including the target layer, criterion layer, sub-criterion layer and solution layer. By solving the eigenvector of the judgment matrix, the priority weight of each element at each level to an element at the previous level can be determined, and then the final weight of each alternative plan to the overall goal can be recursively merged through the weighted sum method. The one with the largest final weight is the optimal plan.

[0079] 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.

[0080] 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.

[0081] 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 smart logistics data collection method, characterized by: The following steps are included: Determine the information of the target pet, collect the data of the target pet through the detection unit, and upload the relevant information to the cloud, and record the pet owner's soothing voice to the cloud; wherein, the heart rate of the pet when it is calm is detected through a time period, and the calm heart rate value PB is obtained, and the type, gender and weight information of the pet are stored in the server cloud; The environmental parameters of the pet during consignment are detected by the detection unit, including the acceleration A of the current consignment carrier, the temperature T and the noise DB in the consignment device. According to the parameter changes of acceleration A, temperature T and noise DB in continuous time, the heart rate at the same time is detected. By analyzing the relationship between environmental parameters and the heart rate of the pet, a mathematical model of the environmental stability index is established; Obtain the threshold of the environmental stability index PL when the pet is panicked, set it as the environmental threshold P1, collect the parameters of the current consignment environment, obtain the value of the environmental stability index PL through the formula, evaluate the relationship between the environmental stability index PL and the environmental threshold P1 and provide feedback; By collecting the data of the pet's calm heart rate PB and calculating the environmental stability index PL in the current consignment environment, the weights of the pet's calm heart rate PB and the environmental stability index PL on the pet's heart rate are obtained through data normalization, and the pet's predicted heart rate PM is obtained by constructing a weighted average formula, and the panic threshold P2 of the heart rate when the pet is panicked is obtained in advance, and the relationship between the pet's predicted heart rate PM and the panic threshold P2 is evaluated and fed back; The environmental stability index PL during pet consignment is adjusted through an optimization algorithm, and measures are taken to soothe the pet, so that the pet's predicted heart rate PM shows favorable changes.

2. According to claim 1, a smart logistics data collection method is characterized by: Under the environment where the temperature T and noise DB parameters remain unchanged, the detection unit Detect acceleration A in a time period to obtain a data set of acceleration A and a corresponding data set of heart rate values; Under the environment where the acceleration A and temperature T parameters remain unchanged, the detection unit The noise DB is detected in a time period to obtain a data set of the noise DB and a corresponding data set of heart rate values; Under the condition that the acceleration A and noise DB parameters remain unchanged, the detection unit The temperature T is detected in a time period to obtain a data set of temperature T and a corresponding data set of heart rate values, and the mathematical relationship between the above parameter change values ​​and the heart rate value change values ​​is analyzed using the hierarchical analysis method.

3. The method for collecting intelligent logistics data according to claim 1 is characterized in that: The environmental stability index PL is set. The environmental stability index PL is related to the parameters in the shipping environment. After normalizing and cleaning the above environmental parameter data, the weight coefficients of acceleration A, temperature T and noise DB are obtained, which are respectively After dimensionless processing, the correlation formula between the environmental stability index PL and the above parameters is as follows: ; in, , , 1, , is the constant correction factor, 0.74 1.

81.

4. The method for collecting intelligent logistics data according to claim 1 is characterized in that: Before shipping, the pet is calmed by soothing it. The heart rate is detected by the detection unit according to a preset period to obtain a set of heart rate values. The average is calculated based on this set of values ​​to obtain the average heart rate PB in the calm state.

5. The method for collecting intelligent logistics data according to claim 1 is characterized in that: The pet's predicted heart rate PM assessment is associated with the environmental stability index PL and the pet's calm heart rate PB, and the correlation formula is as follows: ; in, and are the weight coefficients of the environmental stability index PL and the pet's calm heart rate PB, 1, 1.33, is the constant correction factor, 5.38 9.62, compare the pet's predicted heart rate PM with the pet's panic heart rate threshold PP and provide feedback on the result.

6. A smart logistics data collection method according to claim 5, characterized in that: Calculate the predicted heart rate PM value, and pre-set the heart rate panic threshold P2 by observing the pet's state and detecting the pet's heart rate. The heart rate panic threshold P2 is divided into the first panic threshold and the second panic threshold according to the situation. First panic threshold Second panic threshold; When the heart rate panic threshold P2 Predicted heart rate PM The first panic threshold indicates that the pet's heart rate is expected to rise and it will panic. The situation is medium-urgent and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment. When the second panic threshold Predicted heart rate PM means that the pet's heart rate is expected to rise and the pet will panic. The situation is serious and urgent, and a feedback instruction is issued to remind the logistics personnel to pre-process the consignment environment; When the predicted heart rate PM When the heart rate panic threshold is P2, it means that the pet's heart rate is expected to be good, and a feedback instruction is issued to remind the logistics personnel to maintain the current consignment environment.

7. The method for collecting intelligent logistics data according to claim 6 is characterized in that: by At time intervals, information on environmental parameters is collected periodically to obtain continuous environmental stability index values ​​PL sorted by time. By obtaining continuous predicted heart rate PM values, the values ​​of predicted heart rate PM values ​​higher than the heart rate panic threshold P2 are recorded as abnormal values. The continuous time of abnormal values ​​of the predicted heart rate PM is counted and recorded as the crisis time KT. Combined with the duration of the crisis time KT and the physiological state of the pet, the results are evaluated and fed back.

8. The method for collecting intelligent logistics data according to claim 7 is characterized in that: Set the heart rate panic threshold The duration of the predicted heart rate PM is the crisis time KT. The pet panic tolerance time is set in advance according to the pet's basic physiological information and registered as the first time , Second Time and the third time , when Crisis time Second time , the warning is evaluated and fed back as a first-level crisis, indicating that the pet's condition is a mild emergency; when Crisis time The third time , the warning is evaluated and fed back as a second-level crisis, indicating that the pet's situation is moderately urgent; when Crisis time KT, the assessment and feedback warning is the third level crisis, indicating that the pet's condition is severely urgent.

9. The method for collecting intelligent logistics data according to claim 8 is characterized in that: The warning priority generated by the crisis time KT is greater than the warning priority generated by the environmental stability index PL. After the warning feedback, the value of the temperature T is changed through the external temperature control device, the acceleration A of the vehicle is changed, the propagation of the noise is changed through the external sound insulation device, and the pet owner's soothing voice is played, so that the pet's predicted heart rate PM is close to or equal to the heart rate mean PB.

10. A smart logistics data collection system, applied to the smart logistics data collection system according to any one of claims 1 to 9, characterized in that: It includes a detection unit, a processing unit and an execution unit; The detection unit includes an acceleration module, a temperature module, a noise module and a heart rate module, wherein the acceleration module is used to collect the acceleration of the consignment carrier, the temperature module is used to collect the consignment environment temperature T, the noise module is used to collect the consignment environment noise DB, and the heart rate module is used to collect and record the pet's calm heart rate PB and heart rate panic threshold P2; The processing unit includes a data analysis module and a calculation module. The data analysis module is used to analyze the data detected by the detection unit. The calculation module is used to clean, normalize and calculate the collected data and transmit the results to the execution unit. The execution unit includes a control module and an early warning module. The control module is used to control the audio player, the external temperature control device and the external sound insulation device. The early warning module is used to transmit an early warning signal to the mobile terminal of the logistics personnel.

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