Wearable device data interaction system based on 5GRedCap

Abstract

The invention relates to the technical field of transportation management, and discloses a wearable device data interaction system based on 5GRedCap. Comprising the steps of collecting basic operation parameters, generating an operation event of the wearable device, judging whether an interaction management requirement is met or not, collecting interaction parameters of transportation personnel, recognizing abnormal moments, judging whether an interaction management mode is triggered or not, recognizing management parameters from the abnormal moments, and formulating and executing an interaction management instruction. Compared with the prior art, data support can be provided for interaction management between the management background and the transportation personnel, the problem of limitation or singleness in data interaction management is avoided, and the management background is helped to formulate correct and reasonable interaction management measures for the transportation personnel according to the actual transportation state and performance of the transportation personnel, so that the transportation efficiency is improved. The data interaction effect between the management background and the transportation personnel is further enhanced, and the management background is promoted to carry out more accurate, more timely and safer interaction management operation on the transportation personnel.

Description

Technical Field

[0001] The present invention relates to the technical field of transportation management, and more specifically, to a wearable device data interaction system based on 5GRedCap. Background Art

[0002] With the rapid development of 5G technology, its integration with wearable devices has shown an unprecedented broad prospect. At the same time, wearable devices equipped with 5GRedCap (Reduced Capability, lightweight technology) technology have also shown great potential in logistics and transportation production and management. By wearing wearable devices equipped with 5GRedCap technology by transportation personnel, multi-dimensional data collection and analysis of the transportation process in the logistics transportation process can be carried out, and finally a bridge for data interaction and management is provided between the management background and transportation personnel, so as to achieve efficient and safe interactive management effect between the management background and the logistics transportation process.

[0003] The patent application with reference publication number CN109345183A discloses a method and device for delivery management based on smart wearables, including receiving a wearable sensor message from a smart wearable device, connecting to a delivery server to start a delivery service, generating a monitoring instruction for starting smart monitoring and sending it to the smart wearable device, real-time positioning of delivery route information, real-time recording of the client's speed information, receiving real-time monitoring data from the smart wearable device, and sending the delivery route information, speed information, real-time monitoring data and the current client identifier to the delivery server. Based on the consistent positioning of the wearable device and the mobile device, it collects basic user information, delivery routes and historical delivery data collected by the smart wearable device, analyzes the user's safety factor during the delivery process, and pushes reasonable insurance and safety tips to the user based on the obtained safety factor, so as to provide personalized safety protection push for each delivery person; The existing data interaction system analyzes the real-time delivery safety of delivery personnel and provides safety protection for delivery personnel by collecting and analyzing real-time data from smart wearable devices and combining it with the historical delivery information of delivery personnel. However, by collecting real-time data from smart wearable devices, on the one hand, there are fewer data dimensions involved in data interaction, resulting in greater limitations in the data interaction and management process. On the other hand, when abnormal situations are discovered during the transportation process, there is a lack of reasonable and accurate interactive management operations, which makes it impossible for the management background to provide accurate and timely interactive management opinions and measures to the transportation personnel, thereby reducing the management efficiency in the transportation logistics process.

[0004] In view of this, the present invention proposes a wearable device data interaction system based on 5GRedCap to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solutions: a wearable device data interaction system based on 5GRedCap, applied to a cloud service platform, comprising: The first data collection module is used to collect basic operating parameters of the wearable device and generate operating events of the wearable device according to the basic operating parameters, where the basic operating parameters include battery power remaining, unit attenuation value and unit failure rate; The demand determination module is used to identify abnormalities in operation events, identify abnormal parameters in operation events, and determine whether the wearable device meets the interactive management requirements; The second data collection module is used to mark non-adjacent interaction moments in the interaction management cycle, and collect the interaction parameters of the transport personnel at the interaction moments through wearable devices. The interaction parameters include position offset value, speed peak value and physiological health value; The abnormality determination module is used to compare the interaction parameters with the corresponding safety values, identify the abnormal moment, and determine whether to trigger the interaction management mode based on the interaction triggering criteria. The management instruction module is used to identify management parameters from abnormal moments, formulate interactive management instructions, and control the orderly execution of interactive management instructions based on execution priorities.

[0006] Furthermore, the method for obtaining the unit attenuation value is: The battery management system is used to query the time when the power supply battery is discharged for the first time on the day, which is recorded as the starting time, and the period from the starting time to the current time is recorded as the discharge period; According to the preset discharge time, A non-adjacent discharge moments are marked in the discharge period, and the remaining power of the power supply battery at the A discharge moments is queried one by one to obtain A remaining power values; Subtract the residual value at the last discharge moment from the residual value at the next discharge moment in sequence to obtain A-1 residual attenuation values; Eliminate the maximum and minimum values ​​of the residual attenuation value, and The residual attenuation values ​​are accumulated and averaged, and compared with the preset discharge time to obtain the unit attenuation value; The expression for unit attenuation value is: ; In the formula, is the unit attenuation value, For the The margin attenuation value, The preset discharge time.

[0007] Furthermore, the method for obtaining the unit failure rate is: During the discharge period, all security logs in the security detection system are identified, and the security values ​​in the security logs are marked one by one; The security logs with security values ​​of "0-1", "1-0" and "0-0" are regarded as abnormal logs, and the number of abnormal logs is counted to obtain the fault quantity value; After comparing the fault value with the duration corresponding to the discharge period, the unit fault rate is obtained; The expression of unit failure rate is: ; In the formula, is the unit failure rate, is the fault value, is the duration corresponding to the discharge period.

[0008] Furthermore, the method for generating the running event is: Constructing a basic event with three event bits, and recording the three event bits as a first event bit, a second event bit, and a third event bit; Importing the remaining battery power, the unit attenuation value, and the unit failure rate into the first event bit, the second event bit, and the third event bit, respectively, to generate the first event bit, the second event bit, and the third event bit after importing; The first event bit, the second event bit and the third event bit after import are numbered in ascending order to generate a running event.

[0009] Furthermore, the method for identifying abnormal parameters is: According to the order from small to large, the battery power remaining, unit attenuation value and unit failure rate in the first event bit, the second event bit and the third event bit are sequentially identified for abnormality; When the battery power remaining is less than the lower limit of the remaining power, the battery power remaining is recorded as an abnormal parameter; When the unit attenuation value is greater than the unit attenuation upper limit value, the unit attenuation value is recorded as an abnormal parameter; When the unit failure rate is greater than the unit failure upper limit, the unit failure rate is recorded as an abnormal parameter; The method for determining whether the interactive management requirements are met is: When there are no abnormal parameters in the running event, it is determined that the interactive management requirements are met; When there are abnormal parameters in the running event, it is determined that the interactive management requirements are not met.

[0010] Furthermore, the method for obtaining the position offset value is: In chronological order, the locations of the transport personnel at B interaction moments are queried one by one through the built-in positioning system of the wearable device to obtain B real-time locations; The pre-planned standard operation route is searched through the map database, and the points corresponding to B interaction moments are marked one by one in the standard operation route to obtain B standard positions; The B real-time positions and the B standard positions are transferred to an electronic map, and the distances between the B real-time positions and the corresponding B standard positions are measured one by one by a scale to obtain B position offset values.

[0011] Furthermore, the method for obtaining the physiological health value is: At B interaction moments, the heart rate data, blood oxygen data and blood pressure data of the transport personnel are monitored respectively through the heart rate sensor, blood oxygen sensor and blood pressure sensor built into the wearable device to obtain B heart rate values, B blood oxygen values ​​and B blood pressure values; The heart rate values, blood oxygen values ​​and blood pressure values ​​that are not within the safe heart rate level, safe blood oxygen level and safe blood pressure level are recorded as healthy abnormal values, and the number of healthy abnormal values ​​is counted to obtain B abnormal values; At B interaction moments, B physiological health values ​​are calculated based on the sum of the number of abnormal values ​​and the heart rate value, blood oxygen value and blood pressure value; The expression of physiological health value is: ; In the formula, For the The physiological health value of each interaction moment, =1,2...B, For the The outliers at the interaction moment.

[0012] Furthermore, the method for identifying abnormal moments is: According to the order of acquisition time, the position offset value, velocity peak value and physiological health value of B interaction moments are compared with the displacement safety value, velocity safety value and health safety value respectively; When the position offset value at the Cth interaction moment is greater than the displacement safety value, the Cth interaction moment is recorded as an abnormal moment; When the speed peak value at the Cth interaction moment is greater than the speed safety value, the Cth interaction moment is recorded as an abnormal moment; When the physical health value at the Cth interaction moment is greater than the health safety value, the Cth interaction moment is recorded as an abnormal moment.

[0013] Furthermore, the interaction triggering criterion is: when there is a number continuous value greater than or equal to 3 or a number abnormal value greater than or equal to a number abnormal threshold, it is determined to trigger the interaction management mode; The method for determining whether to trigger the interactive management mode is: According to the chronological order, the B interaction moments are numbered and arranged in ascending order to generate a moment queue; Mark the numbers corresponding to the abnormal moments in the time queue one by one, record them as abnormal numbers, and count the number of numbers in the abnormal numbers that are in a continuous state, record them as number continuity values; When the serial number value is greater than or equal to 3, the interactive management mode is triggered; When the number continuous value is less than 3, the number of all abnormal numbers is counted and recorded as the number abnormal value; When the number abnormality value is greater than or equal to the number abnormality threshold, it is determined that the interactive management mode is triggered.

[0014] Furthermore, the interactive management instructions include position correction instructions, speed reduction instructions, and stop and rest instructions; The method for formulating the corrected position command, the speed reduction command and the stop and rest command is as follows: When the management parameter is a position offset value, a correction position instruction is formulated; When the management parameter reaches the speed peak, a speed reduction instruction is issued; When the management parameter reaches the physiological health value, a shutdown and rest instruction is issued; The execution priorities are: the priority of the stop and rest command is higher than the priority of the speed reduction and slow down command, and the priority of the speed reduction and slow down command is higher than the priority of the position correction command.

[0015] The technical effects and advantages of the wearable device data interaction system based on 5GRedCap of the present invention are as follows: The present invention collects basic operating parameters of wearable devices, generates operating events of wearable devices, identifies abnormalities in operating events, and determines whether wearable devices meet the needs of interactive management. It can analyze the basic operating status of wearable devices from a multi-dimensional data level, accurately and comprehensively determine whether the wearable devices can meet the needs of subsequent interactive management operations, thereby avoiding data calculation and analysis operations that do not meet subsequent needs in advance and accurately, reducing the computing burden of the data interaction system. At the same time, the wearable devices collect the interaction parameters of the transport personnel at the interaction time, compare the interaction parameters with the corresponding safety values ​​to identify abnormal moments, and determine whether to trigger the interactive management mode based on the interactive trigger criteria. The relevant data of the transport personnel in the transportation process can be comprehensively collected and analyzed, and the transport personnel can be accurately determined during transportation. The operation stability of the process is improved, and data support is provided for the subsequent interactive management between the management background and the transportation personnel, so as to improve the data interactive flow between the management background and the transportation personnel, avoid the problems of limitation or singularity in the data interactive management, and combine the management parameters identified from the abnormal moments to formulate interactive management instructions. Based on the execution priority, the interactive management instructions are controlled to be executed in an orderly manner, which can help the management background to formulate correct and reasonable interactive management measures for the transportation personnel according to their actual transportation status and performance, and provide safe transportation guidance to the transportation personnel remotely, thereby further deepening the data interaction effect between the management background and the transportation personnel, and promoting the management background to conduct more accurate, more timely and safer interactive management operations on the transportation personnel, thereby providing safety protection for the entire transportation process of the transportation personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of the architecture of a wearable device data interaction system based on 5GRedCap provided in Embodiment 1 of the present invention; Figure 2 A module schematic diagram of a wearable device data interaction system based on 5GRedCap provided in Embodiment 1 of the present invention; Figure 3 A flowchart of a wearable device data interaction method based on 5GRedCap provided in Embodiment 2 of the present invention; Figure 4 A schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0017] 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.

[0018] Example 1: Please refer to Figure 1 and Figure 2 As shown, the wearable device data interaction system based on 5GRedCap described in this embodiment is applied to a cloud service platform, including: The first data collection module collects basic operating parameters of the wearable device and generates operating events of the wearable device according to the basic operating parameters; the basic operating parameters include battery power remaining, unit attenuation value and unit failure rate; Wearable devices refer to smart devices that are integrated with 5GRedCap technology and worn by transportation personnel, and serve as data collection and data receiving terminals that provide interactive data to the cloud service platform. Basic operating parameters are data that can represent the basic state of the wearable device before performing data interaction operations, and serve as the basis for subsequent judgment on whether the wearable device meets the data interaction requirements. Specifically, the wearable device in this embodiment is a smart bracelet, which has built-in components such as a positioning chip, a power supply battery, a heart rate sensor, a blood oxygen sensor, and a blood pressure sensor.

[0019] Basic operating parameters include battery power remaining, unit attenuation value and unit failure rate; The remaining battery power refers to the remaining power of the wearable device's power supply battery at the current moment, which can be used as the maximum power that can be used in subsequent data interaction. The remaining battery power is obtained by querying the battery management system.

[0020] The unit attenuation value refers to the rate of decrease of the remaining battery power of the wearable device in a unit time, which can be used to indicate the usage of the battery power. The larger the unit attenuation value, the faster the rate of decrease of the battery power. The method to obtain the unit attenuation value is: The battery management system is used to query the time when the power supply battery is discharged for the first time on the day, which is recorded as the starting time, and the period from the starting time to the current time is recorded as the discharge period; According to the preset discharge time, A non-adjacent discharge moments are marked in the discharge period, and the remaining power of the power supply battery at the A discharge moments is queried one by one to obtain A remaining power values; the preset discharge time refers to the time span between two adjacent discharge moments, and can also indicate the corresponding time when the remaining power of the power supply battery changes sufficiently, ensuring that the remaining power of the power supply battery is more obvious and easy to collect; Subtract the residual value at the last discharge moment from the residual value at the next discharge moment in sequence to obtain A-1 residual attenuation values; Eliminate the maximum and minimum values ​​of the residual attenuation value, and The residual attenuation values ​​are accumulated and averaged, and compared with the preset discharge time to obtain the unit attenuation value; The expression for unit attenuation value is: ; In the formula, is the unit attenuation value, For the The margin attenuation value, The preset discharge time.

[0021] The unit failure rate refers to the number of failures that occur in the operating system of the wearable device per unit time, which can be used to indicate the safety of the operating system. The greater the unit failure rate, the worse the safety of the operating system. The method to obtain the unit failure rate is: During the discharge period, all safety logs in the safety detection system are identified, and the safety values ​​in the safety logs are marked one by one; the safety log is used to record the data of the safe operation status of the wearable device, and the safety value is the specific value of the safety log, thereby dividing the safety log into abnormal logs and non-abnormal logs; the safety values ​​include "0-1", "1-0", "0-0" and "1-1"; The security logs with security values ​​of "0-1", "1-0" and "0-0" are regarded as abnormal logs, and the number of abnormal logs is counted to obtain the fault quantity value; After comparing the fault value with the duration corresponding to the discharge period, the unit fault rate is obtained; The expression of unit failure rate is: ; In the formula, is the unit failure rate, is the fault value, is the duration corresponding to the discharge period.

[0022] After the basic operating parameters are obtained, operating events that can comprehensively represent the basic operating status of the wearable device can be generated based on the basic operating parameters, and by identifying and analyzing the operating events, it can be determined whether the basic operating status of the wearable device meets the subsequent data interaction and management requirements; The method for generating the run event is: A basic event with three event bits is constructed, and the three event bits are recorded as the first event bit, the second event bit, and the third event bit respectively; the basic event is used to construct the basis of the running event, and the basic event usually does not contain any substantial data. The event bit is used to limit the import position of the substantial data and ensure the accurate generation of subsequent running events; Importing the remaining battery power, the unit attenuation value, and the unit failure rate into the first event bit, the second event bit, and the third event bit, respectively, to generate the first event bit, the second event bit, and the third event bit after importing; The first event bit, the second event bit and the third event bit after import are numbered in ascending order to generate a running event.

[0023] It should be noted that the constructed operation events can represent the basic operating status of the wearable device from three aspects: battery remaining, battery attenuation and failure rate, thereby providing a basis for subsequent data interaction and management.

[0024] The demand determination module identifies abnormalities in operation events, identifies abnormal parameters in operation events, and determines whether the wearable device meets the interactive management requirements; Abnormality identification is used to identify whether the parameters in the event bit of the operation event are abnormal, so that the abnormal parameters can be recorded as abnormal parameters after abnormality identification, and the abnormal parameters can be used to determine whether the wearable device meets the interactive management requirements. The interactive management requirements refer to the wearable device being able to meet the basic requirements for subsequent data interactive management of transportation personnel and management background, thereby providing a basic basis for analysis of operation events and wearable devices; The method for identifying abnormal parameters is: According to the order from small to large, the battery power remaining, unit attenuation value and unit failure rate in the first event bit, the second event bit and the third event bit are sequentially identified for abnormality; When the remaining battery power is less than the lower limit of the remaining power, it means that the remaining power of the power supply battery of the wearable device cannot meet the subsequent use requirements, and the remaining battery power is recorded as an abnormal parameter; the lower limit of the remaining power refers to the minimum value of the power supply battery of the wearable device when meeting the interactive management requirements, so as to ensure that the power supply battery has sufficient power for use; When the unit attenuation value is greater than the unit attenuation upper limit, it means that the attenuation amplitude of the power supply battery of the wearable device cannot meet the subsequent use requirements, and the unit attenuation value is recorded as an abnormal parameter; the unit attenuation upper limit refers to the maximum value of the unit attenuation value of the wearable device when the interactive management requirements are met, so as to ensure that the power supply battery does not suffer from excessive attenuation; When the unit failure rate is greater than the upper limit of the unit failure, it means that the safety performance of the operating system of the wearable device cannot meet the subsequent use requirements, and the unit failure rate is recorded as an abnormal parameter. The upper limit of the unit failure refers to the maximum value of the unit failure rate of the wearable device when the interactive management requirements are met, to ensure that the smart device does not have a low safety phenomenon.

[0025] When abnormal parameters are identified, it is possible to determine whether the wearable device meets the interaction management requirements based on whether abnormal parameters exist in the running event, thereby providing accurate judgment for the subsequent data interaction collection, calculation and analysis operations; The method for determining whether the interactive management requirements are met is: When there are no abnormal parameters in the operation event, the basic operation status of the smart device is good at this time and can meet the requirements of subsequent data interaction management, and it is determined that the interaction management requirements are met; When there are abnormal parameters in the operation event, the basic operation status of the smart device at this time is not good and cannot meet the requirements of subsequent data interaction management, and it is determined that the interaction management requirements are not met.

[0026] In summary, as long as there are abnormal parameters in the running event, it means that the wearable device does not meet the interactive management requirements. When there are no abnormal parameters in the running event, it means that the wearable device meets the interactive management requirements and can meet subsequent further management requirements.

[0027] The second data collection module marks non-adjacent interaction moments in the interaction management cycle and collects the interaction parameters of the transport personnel at the interaction moments through wearable devices; the interaction parameters include position offset value, speed peak value and physiological health value; The interactive management cycle refers to the maximum time range for the interactive management of data by the transport personnel and the management background, which can provide a maximum limit for the duration of the interactive management of data. Since the interactive management cycle corresponds to a long time, in order to accurately collect data of the transport personnel within the interactive management cycle, it is necessary to mark the interaction time within the interactive management cycle so that the interaction time can be used as the time node for the transport personnel to collect and update data; Specifically, the interaction management cycle corresponds to a time period with a specific time span, and can provide sufficient time for the data interaction management between the management background and the transportation personnel. The starting point of the interaction management cycle is the current moment. The duration of the interaction management cycle is determined according to the duration corresponding to the actual management background performing remote data interaction and management of the transportation personnel. The duration between two adjacent interaction moments is the average duration of at least one change in the relevant data of the transportation personnel during the interaction management cycle, so that B non-adjacent interaction moments can be marked within the interaction management cycle; exemplarily, when the interaction management cycle is 2 minutes, the time span between two adjacent interaction moments is 10 seconds, and when the interaction management cycle is 3 minutes, the time span between two adjacent interaction moments is 20 seconds.

[0028] Interaction parameters refer to the relevant parameters of the wearable device at the interaction time that can affect the transportation personnel's participation in subsequent data interaction management, and serve as the basis for subsequent interaction management between the management background and the transportation personnel; The interaction parameters include position offset value, velocity peak value, and physiological health value; The position offset value refers to the distance offset between the real-time position of the transport personnel at B interaction moments and the calibrated route position, which can be used to represent the offset magnitude of the real-time position of the transport personnel; The method for obtaining the position offset value is: In chronological order, the locations of the transport personnel at B interaction moments are queried one by one through the built-in positioning system of the wearable device to obtain B real-time locations; The pre-planned standard operation route is queried through the map database, and the points corresponding to B interaction moments are marked one by one in the standard operation route to obtain B standard positions; the standard operation route refers to the standard transportation route automatically generated by the system during the transportation logistics process of the transportation personnel, and provides a reference for the analysis and calculation of the subsequent position offset value; The B real-time positions and the B standard positions are transferred to an electronic map, and the distances between the B real-time positions and the corresponding B standard positions are measured one by one by a scale to obtain B position offset values.

[0029] The speed peak refers to the maximum value of the transportation speed of the transportation personnel at B interaction moments, which can be used to represent the size of the real-time transportation speed of the transportation personnel; when the speed peak is to be obtained, the transportation speed before the current interaction moment is detected in real time by the speed sensor built into the wearable device, and the maximum value is taken to obtain it; exemplarily, when the speed peak at the fourth interaction moment is to be obtained, the speed sensor is used to detect the speed of the transportation personnel in the period from the third interaction moment to the fourth interaction moment, and the maximum speed is taken to obtain the speed peak.

[0030] The physiological health value refers to the value of the health level of the transport personnel corresponding to the physiological health data of the transport personnel at B interaction moments, which can be used to represent the health level of the transport personnel. The larger the physiological health value, the worse the physical health level of the transport personnel. The method for obtaining physiological health values ​​is: At B interaction moments, the heart rate data, blood oxygen data and blood pressure data of the transport personnel are monitored respectively through the heart rate sensor, blood oxygen sensor and blood pressure sensor built into the wearable device to obtain B heart rate values, B blood oxygen values ​​and B blood pressure values; The heart rate values, blood oxygen values ​​and blood pressure values ​​that are not within the safe heart rate level, safe blood oxygen level and safe blood pressure level are recorded as healthy abnormal values, and the number of healthy abnormal values ​​is counted to obtain B abnormal values; the safe heart rate level, safe blood oxygen level and safe blood pressure level refer to the range between the minimum and maximum values ​​of the heart rate, blood oxygen and blood pressure values ​​of the transport personnel in a physiologically healthy state, respectively, which can provide a numerical basis for the comparison and identification of the heart rate, blood oxygen and blood pressure values; At B interaction moments, B physiological health values ​​are calculated based on the sum of the number of abnormal values ​​and heart rate values, blood oxygen values, and blood pressure values; The expression of physiological health value is: ; In the formula, For the The physiological health value of each interaction moment, =1,2...B, For the The outliers at the interaction moment.

[0031] The abnormality determination module compares the interaction parameters with the corresponding safety values, identifies the abnormal moment, and determines whether to trigger the interaction management mode based on the interaction triggering criteria; The abnormal moment is used to represent the corresponding state of the interaction parameters contained in the interaction moment, that is, to represent the different states of each different interaction moment, so as to determine whether an abnormal interaction parameter appears in a certain interaction moment; The safety value is a standard value that is compared with each interaction parameter in specific magnitude and serves as a direct basis for determining abnormal moments; The method for identifying abnormal moments is: According to the order of acquisition time, the position offset value, velocity peak value and physiological health value of B interaction moments are compared with the displacement safety value, velocity safety value and health safety value respectively; When the position offset value at the Cth interaction moment is greater than the displacement safety value, it means that the deviation between the real-time position of the transport personnel at the Cth interaction moment and the standard position is large, and the Cth interaction moment is recorded as an abnormal moment; the displacement safety value refers to the maximum value of the position offset value of the transport personnel when the interaction management mode is not triggered, thereby providing a basis for the degree of position offset of the transport personnel; When the speed peak value at the Cth interaction moment is greater than the speed safety value, it means that the deviation between the real-time speed of the transport personnel at the Cth interaction moment and the standard speed is large, and the Cth interaction moment is recorded as an abnormal moment; the speed safety value refers to the maximum value of the speed peak value of the transport personnel when the interaction management mode is not triggered, thereby providing a basis for the degree of speed change of the transport personnel; When the physical health value at the Cth interaction moment is greater than the health safety value, it means that the deviation between the physical health level of the transport personnel at the Cth interaction moment and the standard health level is large, and the Cth interaction moment is recorded as an abnormal moment. The health safety value refers to the maximum value of the physical health value of the transport personnel when the interaction management mode is not triggered, thereby providing a basis for the physiological health level of the transport personnel.

[0032] After marking the abnormal moments, it is necessary to conduct an overall analysis of all abnormal moments, and determine whether to trigger the interactive management mode in the future based on the analysis results of the abnormal moments. The interactive management mode refers to a mode that can be triggered when the overall number of abnormal moments is large or the continuity is strong, and can perform data interactive management between the transportation personnel and the management background, so as to ensure that the management background can provide timely prompts to the transportation personnel wearing wearable devices, thereby enhancing the data interactive management effect between the management background and the transportation personnel; When determining whether to trigger the interactive management mode, it is necessary to ensure the accuracy of triggering the interactive management mode under the constraints of the interactive triggering criteria; The interactive triggering criteria are: when there is a number continuous value greater than or equal to 3 or a number abnormal value greater than or equal to the number abnormal threshold, the interactive management mode is determined to be triggered; thus, the interactive management mode is effectively and accurately triggered to ensure that the correct handling measures can be taken in a timely and accurate manner when one of the abnormal phenomena occurs; The method for determining whether to trigger the interactive management mode is: According to the chronological order, the B interaction moments are numbered and arranged in ascending order to generate a moment queue; Mark the numbers corresponding to the abnormal moments in the time queue one by one, record them as abnormal numbers, and count the number of numbers in the abnormal numbers that are in a continuous state, record them as number continuity values; When the serial number value is greater than or equal to 3, it means that there are at least three consecutive abnormal moments with adjacent numbers in the moment queue, and the interactive management mode is triggered; When the number continuous value is less than 3, the number of all abnormal numbers is counted and recorded as the number abnormal value; When the number abnormal value is greater than or equal to the number abnormal threshold, it means that the number of abnormal moments in the moment queue exceeds the maximum value under normal circumstances, and the interactive management mode is triggered. The number abnormal threshold is used to represent the maximum value of the number abnormal value when the interactive management mode is not triggered, so as to provide a comparison basis for the total number of abnormal moments and ensure the accuracy of the determination of triggering the interactive management mode.

[0033] It should be noted that the situation where the number continuous value is greater than or equal to 3 or the number abnormal value is greater than or equal to the number abnormal threshold may exist at the same time, or only one of the situations may exist. Regardless of whether they exist at the same time or only one of them exists, it is necessary to trigger the interactive management mode at this time, so as to provide the management background with prompts for data interactive management and strengthen the remote interaction and management effect between the management background and the transportation personnel.

[0034] The management instruction module identifies management parameters from abnormal moments, formulates interactive management instructions, and controls the orderly execution of interactive management instructions based on execution priorities; Management parameters refer to the specific interaction parameters that cause the interaction moment to be identified as an abnormal moment, and serve as the corresponding data for the subsequent interaction management between the transportation personnel and the management background, thereby providing a basis for the formulation and execution of subsequent instructions; Specifically, when the position offset value is greater than the displacement safety value, the position offset value is recorded as a management parameter; when the speed peak value is greater than the speed safety value, the speed peak value is recorded as a management parameter; when the physical health value is greater than the health safety value, the physical health value is recorded as a management parameter.

[0035] After the management parameters are identified, interactive management instructions need to be formulated according to the specific types of management parameters, so that the interactive management instructions can achieve data interaction and management effects between the management background and the transportation personnel, ensuring that the management background has effective control over the transportation process of the transportation personnel; Interactive management instructions include position correction instructions, speed reduction and slow-down instructions, and stop and rest instructions; position correction instructions refer to instructions that require the current transport position of the transport personnel to be corrected, speed reduction and slow-down instructions refer to instructions that require the transport personnel to slow down the transport speed, and stop and rest instructions refer to instructions that require the transport personnel to stop transporting and rest; The method for formulating the corrected position command, the speed reduction command and the stop and rest command is as follows: When the management parameter is a position offset value, it means that the real-time position of the transport personnel needs to be corrected, and a correction position instruction is formulated; When the management parameter is the speed peak, it means that the real-time transportation speed of the transport personnel needs to be reduced, and a speed reduction instruction is formulated; When the management parameter is a physiological health value, it means that the transportation personnel need to be controlled to stop and rest, and a stop and rest instruction is formulated.

[0036] After the interactive management instructions are formulated, they need to be executed in an orderly manner to ensure that the transport personnel can not only ensure the safety of their own transportation process, but also achieve the efficiency of the transportation process. At the same time, the interactive management effect between the management background and the transport personnel is improved, ensuring that the transport personnel can be effectively and safely managed, and greatly improving the efficiency of transportation operations; When executing the interactive management instructions, and when there are more than one interactive management instructions, it is necessary to arrange the execution priority of each specific interactive management instruction to ensure that each interactive management instruction can be executed in order; Since the stop and rest instruction is an instruction for the transport personnel's own physical health status, when the stop and rest instruction is formulated, it means that the transport personnel's physical condition is not good. If the transport operation continues, the transport personnel may suffer physical damage. Therefore, it is necessary to give priority to the physical safety of the transport personnel. At this time, the stop and rest instruction has the highest priority. The speed reduction and slowing down instruction is also aimed at the transport speed of the transport personnel during the transport process. When the speed reduction and slowing down instruction is formulated, it means that the transport speed of the transport personnel is too fast and the transport personnel are prone to injury. Therefore, the speed reduction and slowing down instruction has the second highest priority. In summary, the execution priority is: the priority of the stop and rest instruction is higher than the priority of the speed reduction and slow down instruction, and the priority of the speed reduction and slow down instruction is higher than the priority of the position correction instruction.

[0037] When the interactive management instructions are formulated, the formulated interactive management mode can be executed in order according to the execution priority to ensure the interactive management effect between the management background and the transportation personnel; Specifically, when the formulated interactive management instructions are a position correction instruction, a speed reduction and slowing instruction, and a stop and rest instruction, it is necessary to execute the stop and rest instruction first, then execute the speed reduction and slowing instruction, and finally execute the position correction instruction.

[0038] In this embodiment, by collecting the basic operating parameters of the wearable device, generating operating events of the wearable device, identifying abnormalities in the operating events, and determining whether the wearable device meets the interactive management requirements, the basic operating status of the wearable device can be analyzed from a multi-dimensional data level, and it can be accurately and comprehensively determined whether the wearable device can meet the needs of subsequent interactive management operations, thereby avoiding data calculation and analysis operations that do not meet subsequent needs in advance and accurately, reducing the computing burden of the data interaction system. At the same time, the wearable device collects the interaction parameters of the transport personnel at the interaction time, compares the interaction parameters with the corresponding safety values ​​to identify abnormal moments, and determines whether to trigger the interactive management mode based on the interactive trigger criteria. Therefore, the relevant data of the transport personnel in the transportation process can be comprehensively collected and analyzed, and the transport personnel can be accurately determined at the time of the interaction. The operation stability during the transportation process is ensured, and data support is provided for the subsequent interactive management between the management background and the transportation personnel, so as to improve the data interactive flow between the management background and the transportation personnel, avoid the problems of limitation or singularity in the data interactive management, and combine the management parameters identified from the abnormal moments to formulate interactive management instructions. Based on the execution priority, the interactive management instructions are controlled to be executed in an orderly manner. It can help the management background to formulate correct and reasonable interactive management measures for the transportation personnel according to their actual transportation status and performance, and provide safe transportation guidance to the transportation personnel remotely, thereby further deepening the data interaction effect between the management background and the transportation personnel, and promoting the management background to conduct more accurate, more timely and safer interactive management operations on the transportation personnel, thereby providing safety protection for the entire transportation process of the transportation personnel.

[0039] Example 2: Please refer to Figure 3 As shown, the part not described in detail in this embodiment is described in the first embodiment, and a wearable device data interaction method based on 5GRedCap is provided, which is applied to a cloud service platform and implemented based on a wearable device data interaction system based on 5GRedCap, including: S1: Collect basic operating parameters of the wearable device and generate operating events of the wearable device according to the basic operating parameters. The basic operating parameters include battery power remaining, unit attenuation value and unit failure rate; S2: Identify abnormalities in operation events, identify abnormal parameters in operation events, and determine whether the wearable device meets the interaction management requirements; S3: If the interaction management requirements are met, non-adjacent interaction moments are marked in the interaction management cycle, and the interaction parameters of the transport personnel at the interaction moments are collected through wearable devices. The interaction parameters include position offset value, speed peak value and physiological health value; S4: Compare the interaction parameters with the corresponding safety values, identify the abnormal moments, and determine whether to trigger the interaction management mode based on the interaction triggering criteria; S5: If the interactive management mode is triggered, management parameters are identified from the abnormal moment, interactive management instructions are formulated, and based on the execution priority, the interactive management instructions are controlled to be executed in an orderly manner.

[0040] Example 3: Please refer to Figure 4 As shown, this embodiment discloses an electronic device, including a processor and a memory; Wherein, the memory stores a computer program that can be called by the processor; The processor executes the wearable device data interaction method based on 5GRedCap by calling the computer program stored in the memory.

[0041] Since the electronic device introduced in this embodiment is an electronic device used to implement a wearable device data interaction method based on 5GRedCap in Example 1 of this application, based on the wearable device data interaction method based on 5GRedCap introduced in the embodiment of this application, the technical personnel in this field can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of this application will not be described in detail here. As long as the technical personnel in this field implement the electronic device used in the wearable device data interaction method based on 5GRedCap in the embodiment of this application, it belongs to the scope of protection of this application.

[0042] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A wearable device data interaction system based on 5GRedCap, applied to a cloud service platform, characterized in that: include: The first data collection module is used to collect basic operating parameters of the wearable device and generate operating events of the wearable device according to the basic operating parameters, where the basic operating parameters include battery power remaining, unit attenuation value and unit failure rate; The demand determination module is used to identify abnormalities in operation events, identify abnormal parameters in operation events, and determine whether the wearable device meets the interactive management requirements; The second data collection module is used to mark non-adjacent interaction moments in the interaction management cycle, and collect the interaction parameters of the transport personnel at the interaction moments through wearable devices. The interaction parameters include position offset value, speed peak value and physiological health value; The abnormality determination module is used to compare the interaction parameters with the corresponding safety values, identify the abnormal moment, and determine whether to trigger the interaction management mode based on the interaction triggering criteria. The management instruction module is used to identify management parameters from abnormal moments, formulate interactive management instructions, and control the orderly execution of interactive management instructions based on execution priorities.

2. A wearable device data interaction system based on 5GRedCap according to claim 1, characterized in that: The method to obtain the unit attenuation value is: The battery management system is used to query the time when the power supply battery is discharged for the first time on the day, which is recorded as the starting time, and the period from the starting time to the current time is recorded as the discharge period; According to the preset discharge time, A non-adjacent discharge moments are marked in the discharge period, and the remaining power of the power supply battery at the A discharge moments is queried one by one to obtain A remaining power values; Subtract the residual value at the last discharge moment from the residual value at the next discharge moment in sequence to obtain A-1 residual attenuation values; Eliminate the maximum and minimum values ​​of the residual attenuation value, and The residual attenuation values ​​are accumulated and averaged, and compared with the preset discharge time to obtain the unit attenuation value; The expression for unit attenuation value is: ； In the formula, is the unit attenuation value, For the The margin attenuation value, The preset discharge time.

3. A wearable device data interaction system based on 5GRedCap according to claim 2, characterized in that: The method to obtain the unit failure rate is: During the discharge period, all security logs in the security detection system are identified, and the security values ​​in the security logs are marked one by one; The security logs with security values ​​of "0-1", "1-0" and "0-0" are regarded as abnormal logs, and the number of abnormal logs is counted to obtain the fault quantity value; After comparing the fault value with the duration corresponding to the discharge period, the unit fault rate is obtained; The expression of unit failure rate is: ； In the formula, is the unit failure rate, is the fault value, is the duration corresponding to the discharge period.

4. A wearable device data interaction system based on 5GRedCap according to claim 3, characterized in that: The method for generating the run event is: Constructing a basic event with three event bits, and recording the three event bits as a first event bit, a second event bit, and a third event bit; Importing the remaining battery power, the unit attenuation value, and the unit failure rate into the first event bit, the second event bit, and the third event bit, respectively, to generate the first event bit, the second event bit, and the third event bit after importing; The first event bit, the second event bit and the third event bit after import are numbered in ascending order to generate a running event.

5. A wearable device data interaction system based on 5GRedCap according to claim 4, characterized in that: The method for identifying abnormal parameters is: According to the order from small to large, the battery power remaining, unit attenuation value and unit failure rate in the first event bit, the second event bit and the third event bit are sequentially identified for abnormality; When the battery power remaining is less than the lower limit of the remaining power, the battery power remaining is recorded as an abnormal parameter; When the unit attenuation value is greater than the unit attenuation upper limit value, the unit attenuation value is recorded as an abnormal parameter; When the unit failure rate is greater than the unit failure upper limit, the unit failure rate is recorded as an abnormal parameter; The method for determining whether the interactive management requirements are met is: When there are no abnormal parameters in the running event, it is determined that the interactive management requirements are met; When there are abnormal parameters in the running event, it is determined that the interactive management requirements are not met.

6. A wearable device data interaction system based on 5GRedCap according to claim 5, characterized in that: The method for obtaining the position offset value is: In chronological order, the locations of the transport personnel at B interaction moments are queried one by one through the built-in positioning system of the wearable device to obtain B real-time locations; The pre-planned standard operation route is searched through the map database, and the points corresponding to B interaction moments are marked one by one in the standard operation route to obtain B standard positions; The B real-time positions and the B standard positions are transferred to an electronic map, and the distances between the B real-time positions and the corresponding B standard positions are measured one by one by a scale to obtain B position offset values.

7. A wearable device data interaction system based on 5GRedCap according to claim 6, characterized in that: The method for obtaining physiological health values ​​is: At B interaction moments, the heart rate data, blood oxygen data and blood pressure data of the transport personnel are monitored respectively through the heart rate sensor, blood oxygen sensor and blood pressure sensor built into the wearable device to obtain B heart rate values, B blood oxygen values ​​and B blood pressure values; The heart rate values, blood oxygen values ​​and blood pressure values ​​that are not within the safe heart rate level, safe blood oxygen level and safe blood pressure level are recorded as healthy abnormal values, and the number of healthy abnormal values ​​is counted to obtain B abnormal values; At B interaction moments, B physiological health values ​​are calculated based on the sum of the number of abnormal values ​​and the heart rate value, blood oxygen value and blood pressure value; The expression of physiological health value is: ； In the formula, For the The physiological health value of each interaction moment, =1,2...B, For the The outliers at the interaction moment.

8. A wearable device data interaction system based on 5GRedCap according to claim 7, characterized in that: The method for identifying abnormal moments is: According to the order of acquisition time, the position offset value, velocity peak value and physiological health value of B interaction moments are compared with the displacement safety value, velocity safety value and health safety value respectively; When the position offset value at the Cth interaction moment is greater than the displacement safety value, the Cth interaction moment is recorded as an abnormal moment; When the speed peak value at the Cth interaction moment is greater than the speed safety value, the Cth interaction moment is recorded as an abnormal moment; When the physical health value at the Cth interaction moment is greater than the health safety value, the Cth interaction moment is recorded as an abnormal moment.

9. A wearable device data interaction system based on 5GRedCap according to claim 8, characterized in that: The interaction triggering criteria are: when there is a number continuous value greater than or equal to 3 or a number abnormal value greater than or equal to the number abnormal threshold, the interaction management mode is determined to be triggered; The method for determining whether to trigger the interactive management mode is: According to the chronological order, the B interaction moments are numbered and arranged in ascending order to generate a moment queue; Mark the numbers corresponding to the abnormal moments in the time queue one by one, record them as abnormal numbers, and count the number of numbers in the abnormal numbers that are in a continuous state, record them as number continuity values; When the serial number value is greater than or equal to 3, the interactive management mode is triggered; When the number continuous value is less than 3, the number of all abnormal numbers is counted and recorded as the number abnormal value; When the number abnormality value is greater than or equal to the number abnormality threshold, it is determined that the interactive management mode is triggered.

10. A wearable device data interaction system based on 5GRedCap according to claim 9, characterized in that: Interactive management instructions include position correction instructions, speed reduction instructions, and stop and rest instructions; The method for formulating the corrected position command, the speed reduction command and the stop and rest command is as follows: When the management parameter is a position offset value, a correction position instruction is formulated; When the management parameter reaches the speed peak, a speed reduction instruction is issued; When the management parameter reaches the physiological health value, a shutdown and rest instruction is issued; The execution priorities are: the priority of the stop and rest command is higher than the priority of the speed reduction and slow down command, and the priority of the speed reduction and slow down command is higher than the priority of the position correction command.

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