Intelligent logistics monitoring method, system and device for long-distance transportation and storage medium

Abstract

The invention discloses an intelligent logistics monitoring method and system for long-distance transportation, and the method comprises the steps: collecting the real-time pressure values of m tires in a vehicle driving process, and obtaining the pressure value P < adjacent > of a tire adjacent to the ith tire when the pressure change gradient between Pi and the monitoring time point of the last round is greater than a preset pressure change gradient threshold value; comparing the Pi with the P adjacent, and obtaining the average pressure value Pave of the tires of the whole vehicle at the same time; the Pi is compared with the Pave, and at the moment, the real-time temperature Ti of the ith tire is obtained and compared with a preset safe temperature threshold value; and when Ti exceeds a preset safe temperature threshold value, an alarm is started. The safety risk of the large vehicle in the driving process is captured by monitoring and analyzing the numerical value change of the tire pressure, and the progressive verification logic of temperature value analysis is combined, so that hidden dangers are warned in advance, tire faults are effectively prevented, major accidents are avoided, and dual optimization of safety protection and cost control is realized.

Description

Technical Field

[0001] This invention relates to the field of transportation safety technology, and in particular to a smart logistics monitoring method, system, device, and storage medium for long-distance transportation. Background Technology

[0002] Large transport vehicles have heavy tire loads, with a single tire carrying up to several tons. Abnormal tire pressure at high speeds is a major cause of tire blowouts and vehicle rollovers. According to industry data, 40% of high-speed accidents involving heavy-duty vehicles are directly related to abnormal tire pressure. Long-distance driving exposes tires to harsh conditions, and abnormal tire pressure poses numerous risks. For example, low tire pressure leads to greater tire deformation and increased friction, resulting in higher tire temperatures; conversely, high tire pressure results in greater tire rigidity and poor heat dissipation, also causing abnormal temperatures. These risks not only impact transportation safety but also affect tire lifespan, increase replacement costs, and cause transportation delays and cargo losses due to tire failure, significantly affecting the rights and interests of transport companies and cargo owners. Summary of the Invention

[0003] To address the technical problems existing in the background art, the present invention proposes a smart logistics monitoring method, system, device, and storage medium for long-distance transportation.

[0004] This invention proposes a smart logistics monitoring method for long-distance transportation, comprising: Set the tire pressure monitoring time points according to the preset time intervals, and start the tire pressure monitoring mode according to the tire pressure monitoring time points; After the tire pressure monitoring mode is activated, the real-time pressure values ​​of m tires are collected during vehicle operation and denoted as P1, P2...P m ; When P i When the pressure change gradient from the previous monitoring time point exceeds a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 ; Comparison P i With P 邻 ,when At that time, obtain the real-time pressure values ​​of the m-1 tires of the entire vehicle excluding the i-th tire and calculate the average pressure value P. ave ; Comparison P i With P ave ,when At that time, obtain the real-time temperature T of the i-th tire. i And compare it with the preset safe temperature threshold; When T i An alarm will be triggered if the preset safe temperature threshold is exceeded. in, , 1≤i≤m, a and b are both preset values.

[0005] Optionally, a warning pressure value P is also preset. 警 ; When P i >P 警 When this occurs, a Level 1 alarm is activated; When P is detected i >cP 警 When this occurs, a level two alarm will be activated; Where c is a preset value and c>1, the first-level alarm is to alert the driver, and the second-level alarm is to alert both the driver and the monitoring platform simultaneously.

[0006] Optionally, a maximum threshold for pressure change gradient is also preset; When P i When the pressure change gradient at the previous monitoring time point exceeds the maximum threshold of the pressure change gradient, a level two alarm is activated.

[0007] Optionally, it also includes a risk observation mode that operates when an alarm is activated; The risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the abnormal situation is resolved; n is a preset value.

[0008] This invention proposes a smart logistics monitoring system for long-distance transportation, comprising: The real-time tire pressure monitoring unit is used to collect the real-time pressure values ​​of m tires at preset tire pressure monitoring time points during vehicle operation, denoted as P1, P2...P... m ; The gradient analysis unit is used to analyze P. i Compared with the pressure change gradient at the previous monitoring time point, when the pressure change gradient is greater than a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 ; The first differential pressure comparison unit is used to compare P. i With P 邻 ,when At that time, obtain the real-time pressure values ​​of the m-1 tires of the entire vehicle excluding the i-th tire and calculate the average pressure value P. ave ; The second differential pressure comparison unit compares P. i With P ave ,when At that time, obtain the real-time temperature T of the i-th tire. i ; Anomaly analysis and early warning unit, used to compare T i Compared with the preset safe temperature threshold, when Ti An alarm will be triggered if the preset safe temperature threshold is exceeded. in, , 1≤i≤m, a and b are both preset values.

[0009] Optionally, the anomaly analysis and early warning unit is further preset with a warning pressure value P. 警 ; When P i >P 警 When this occurs, a Level 1 alarm is activated; When P is detected i >cP 警 When this occurs, a level two alarm will be activated; Where c is a preset value and c>1, the first-level alarm is to alert the driver, and the second-level alarm is to alert both the driver and the monitoring platform simultaneously.

[0010] Optionally, the gradient change analysis unit is further preset with a maximum threshold for pressure change gradient; When P i When the pressure change gradient at the previous monitoring time point exceeds the maximum threshold of the pressure change gradient, the anomaly analysis and early warning unit activates a level two alarm.

[0011] Optionally, the anomaly analysis and early warning unit is also preset with a risk observation mode, which runs when an alarm is activated; The risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the abnormal situation is resolved; n is a preset value.

[0012] The present invention proposes a smart logistics monitoring device for long-distance transportation, comprising: a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the smart logistics monitoring method for long-distance transportation is implemented.

[0013] The present invention proposes a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the intelligent logistics monitoring method for long-distance transportation as described above.

[0014] As can be seen from the above solutions, the intelligent logistics monitoring method and system for long-distance transportation provided in this application has at least the following advantages compared with the prior art: This application first analyzes the pressure change gradients of two tires collected at two adjacent tire pressure detection time points to initially determine whether there is an abnormal risk in the target tire. If so, the first step of the judgment logic is initiated, which compares the real-time pressure values ​​of the target tire with those of adjacent tires. If there is a significant difference in the pressure values ​​of the two tires, the second step of the judgment is initiated, which compares the real-time pressure values ​​of the target tire with those of all tires in the vehicle. If the pressure value of the target tire is still significantly higher / lower than the average pressure value, a temperature comparison strategy is immediately introduced, which involves collecting the temperature of the target tire in real time. If the temperature deviates from a preset safe temperature threshold, an alarm is triggered to notify the driver and / or the monitoring platform to respond quickly and take targeted remedial measures to minimize danger and loss. This application not only adopts an interlocking risk judgment logic, but also introduces temperature for multi-dimensional verification when tire pressure is significantly abnormal. The judgment strategy combining pressure and temperature effectively improves the validity of the judgment results, providing reliable support for long-distance transportation of heavy-duty vehicles. Furthermore, this application also includes a tire pressure change monitoring mode. When a significant change in tire pressure is detected between two adjacent monitoring points, an alarm is immediately triggered to the driver and the monitoring platform, ensuring rapid notification and timely response to guarantee the safety of the vehicle, cargo, and personnel. This application captures safety risks during driving by monitoring and analyzing tire pressure data, and combines this with a progressive verification logic based on temperature value analysis to provide early warnings of potential hazards, effectively preventing tire failures, avoiding major accidents, and achieving a dual optimization of safety protection and cost control. Attached Figure Description

[0015] Figure 1 A flowchart of a smart logistics monitoring method for long-distance transportation; Figure 2 This is a module diagram of a smart logistics monitoring system for long-distance transportation. Detailed Implementation

[0016] like Figure 1 As shown, Figure 1 This is a flowchart of a smart logistics monitoring method for long-distance transportation proposed in this invention.

[0017] Reference Figure 1 The present invention proposes a smart logistics monitoring method for long-distance transportation, comprising: The tire pressure monitoring time points are set according to preset time intervals, and the tire pressure monitoring mode is activated at the specified time points. Abnormal tire pressure (too high / too low) will accelerate tire wear, and monitoring tire pressure can extend tire life. Too low tire pressure will increase the rolling resistance between the tire and the ground, thereby increasing vehicle fuel consumption. Monitoring tire pressure can effectively reduce fuel consumption. Abnormal tire pressure leading to tire failure will cause transportation interruption and generate additional costs such as towing fees and cargo demurrage fees. Monitoring tire pressure can effectively reduce failure delays. Therefore, this application monitors changes in tire pressure to achieve safety supervision of heavy-duty vehicles in long-distance transportation. It can not only predict vehicle failures in advance and achieve proactive prevention and control, but also optimize operation management and improve transportation control efficiency.

[0018] After the tire pressure monitoring mode is activated, the real-time pressure values ​​of m tires are collected during vehicle operation and denoted as P1, P2...P m ; When P i When the pressure change gradient from the previous monitoring time point exceeds a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 By monitoring the changes in tire pressure at two adjacent time points, it is possible to predict whether there is a dynamic risk to the tire. This application further compares the pressure values ​​of the target tire and adjacent tires to verify the rationality of the above prediction. Comparison P i With P 邻 ,when When there is a significant difference in pressure between the target tire and its adjacent tires, to verify whether this difference lies with the target tire, the next step is initiated: obtaining the real-time pressure values ​​of the m-1 tires (excluding the i-th tire) of the entire vehicle and calculating the average pressure value P. ave ; Comparison P i With P ave The rationality of the previous judgment is verified by analyzing the difference between the target tire temperature and the average tire temperature of the entire vehicle. When this occurs, it indicates that the target tire does indeed have an anomaly, and the real-time temperature T of the i-th tire is immediately obtained. i It is compared with a preset safe temperature threshold; temperature is introduced for multi-dimensional comparison, which further improves the effectiveness of the judgment results. When T i An alarm will be triggered if the preset safe temperature threshold is exceeded. in, , 1≤i≤m, a and b are both preset values.

[0019] This application employs a three-tiered comparison logic: comparing the temperature of the target tire itself at two adjacent time points, comparing the temperature of the target tire with that of adjacent tires, and comparing the temperature of the target tire with that of all tires on the vehicle. This comprehensive approach enhances the accuracy of the comparison results. Finally, temperature parameters are introduced as another dimension to assist in the judgment, further improving the rationality of the overall judgment results, reducing the risk of misjudgment, and providing safe and reliable support for long-distance transportation of heavy-duty trucks.

[0020] In a further embodiment, a warning pressure value P is preset. 警 When P i >P 警 When P is detected, a Level 1 alarm is activated; the Level 1 alarm is to alert the driver; when P is detected... i >cP 警 When a level 2 alarm is triggered, the level 2 alarm is simultaneously sent to both the driver and the monitoring platform. Here, c is a preset value and c > 1. By quantifying the risk level through differentiated alarm modes, resources can be saved on the one hand, and interference with the daily operation of the monitoring platform can be avoided when the risk is low. On the other hand, the monitoring platform can be notified in advance to take targeted countermeasures when the potential risk is high, which helps to greatly reduce risks and costs.

[0021] In a further embodiment, a maximum threshold for the pressure change gradient is preset; when P i A level two alarm is triggered when the pressure change gradient from the previous monitoring point exceeds the maximum threshold. A sudden increase in tire pressure within a short period is often caused by tire friction heat (such as prolonged braking or high-speed driving) or a broken tire cord. Without timely intervention, this can lead to a tire blowout within minutes. A rapid decrease in tire pressure indicates a possible puncture (such as a nail or sharp stone embedded in the tire), a valve leak, or sidewall damage. Continuing to drive in this situation can lead to complete tire depressurization and loss of vehicle control. Immediately triggering an alarm when tire pressure suddenly rises or falls notifies the driver and the monitoring platform to be aware of the abnormality and address it promptly, effectively preventing major accidents.

[0022] In a further embodiment, a risk observation mode is also included, which operates when an alarm is activated; the risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the anomaly is resolved; n is a preset value. This mode achieves collaboration between the system and human intervention through cyclical alarms. The system continuously transmits risk signals, and the driver and / or monitoring platform select the processing time and method according to the actual situation, ensuring both the effectiveness of risk monitoring and the flexibility of risk handling.

[0023] Reference Figure 2 The present invention proposes a smart logistics monitoring system for long-distance transportation, comprising: The real-time tire pressure monitoring unit is used to collect the real-time pressure values ​​of m tires at preset tire pressure monitoring time points during vehicle operation, denoted as P1, P2...P... m ; The gradient analysis unit is used to analyze P. i Compared with the pressure change gradient at the previous monitoring time point, when the pressure change gradient is greater than a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 ; The first differential pressure comparison unit is used to compare P. i With P 邻 ,when At that time, obtain the real-time pressure values ​​of the m-1 tires of the entire vehicle excluding the i-th tire and calculate the average pressure value P. ave ; The second differential pressure comparison unit compares P. i With P ave ,when At that time, obtain the real-time temperature T of the i-th tire. i ; Anomaly analysis and early warning unit, used to compare T i Compared with the preset safe temperature threshold, when T i An alarm will be triggered if the preset safe temperature threshold is exceeded. in, 1≤i≤m, where a and b are preset values. By comparing the tire pressure of the target tire with adjacent tires and with all tires on the vehicle, combined with the temperature analysis of the target tire, a progressive verification logic significantly reduces false alarm rates and avoids ineffective operational interference. Simultaneously, it accurately identifies the root cause of risks, improves the efficiency of risk management, and provides data support for optimizing enterprise operating costs and compliance management.

[0024] In a further embodiment, the anomaly analysis and early warning unit is also preset with a warning pressure value P. 警 When P i >P 警 When P is detected, a Level 1 alarm is activated, which is a warning to the driver; i >cP 警 When a level 2 alarm is triggered, it simultaneously alerts both the driver and the monitoring platform; where c is a preset value and c > 1. Setting up a tiered alarm mode ensures that the alarm mechanism precisely matches the actual severity of the risk, reducing driver interference, ensuring driving safety, and improving the accuracy and timeliness of risk handling, thereby optimizing transportation operation efficiency and improving regulatory efficiency.

[0025] In a further embodiment, the gradient change analysis unit is further preset with a maximum threshold for the pressure change gradient; when P iWhen the pressure change gradient from the previous monitoring time point exceeds the maximum threshold of the pressure change gradient, the anomaly analysis and early warning unit activates a level two alarm. For large transport vehicles during long-distance transport, a sudden increase or decrease in tire pressure is an extremely high-risk signal for tire safety. In such cases, an immediate high-level alarm is triggered to seize the golden opportunity for response, prevent serious accidents, minimize property damage, reduce the risk of operational interruption, and further mitigate secondary safety risks, thus protecting the road environment.

[0026] In a further embodiment, the anomaly analysis and early warning unit is also preset with a risk observation mode, which operates when an alarm is activated; the risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the abnormal situation is resolved; n is a preset value. Repeated reminders reinforce the risk awareness of drivers and / or the monitoring platform, improving driving safety while ensuring effective risk control. The interval n seconds can be dynamically adjusted according to the actual risk level; the higher the risk level, the higher the reminder frequency, dynamically adapting to various applicable scenarios to reduce the accident rate and minimize economic losses.

[0027] The present invention proposes a smart logistics monitoring device for long-distance transportation, comprising: a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions. When the program instructions are loaded and executed by the processor, the smart logistics monitoring method for long-distance transportation is implemented.

[0028] The present invention proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the intelligent logistics monitoring method for long-distance transportation.

[0029] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart logistics monitoring method for long-distance transportation, characterized in that, include: Set the tire pressure monitoring time points according to the preset time intervals, and start the tire pressure monitoring mode according to the tire pressure monitoring time points; After the tire pressure monitoring mode is activated, the real-time pressure values ​​of m tires are collected during vehicle operation and denoted as P1, P2...P m ; When P i When the pressure change gradient from the previous monitoring time point exceeds a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 ; Compare P i With P 邻 ,when At that time, obtain the real-time pressure values ​​of the m-1 tires of the entire vehicle excluding the i-th tire and calculate the average pressure value P. ave ; Compare P i With P ave ,when At that time, obtain the real-time temperature T of the i-th tire. i And compare it with the preset safe temperature threshold; When T i An alarm will be triggered if the preset safe temperature threshold is exceeded. in, , 1≤i≤m, a and b are both preset values.

2. The intelligent logistics monitoring method for long-distance transportation according to claim 1, characterized in that, It also has a preset warning pressure value P. 警 ; When P i >P 警 When this occurs, a Level 1 alarm is activated; When P is detected i >cP 警 When this occurs, a level two alarm will be activated; Where c is a preset value and c>1, the first-level alarm is to alert the driver, and the second-level alarm is to alert both the driver and the monitoring platform simultaneously.

3. The intelligent logistics monitoring method for long-distance transportation according to claim 2, characterized in that, It also has a preset maximum threshold for pressure change gradient; When P i When the pressure change gradient at the previous monitoring time point exceeds the maximum threshold of the pressure change gradient, a level two alarm is activated.

4. The intelligent logistics monitoring method for long-distance transportation according to claim 1, characterized in that, It also includes a risk observation mode, which runs when an alarm is activated; The risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the abnormal situation is resolved; n is a preset value.

5. A smart logistics monitoring system for long-distance transportation, characterized in that, include: The real-time tire pressure monitoring unit is used to collect the real-time pressure values ​​of m tires at preset tire pressure monitoring time points during vehicle operation, denoted as P1, P2...P... m ; The gradient analysis unit is used to analyze P. i Compared with the pressure change gradient at the previous monitoring time point, when the pressure change gradient is greater than a preset pressure change gradient threshold, the pressure value P of the tire adjacent to the i-th tire is obtained. 邻 ; The first differential pressure comparison unit is used to compare P. i With P 邻 ,when At that time, obtain the real-time pressure values ​​of the m-1 tires of the entire vehicle excluding the i-th tire and calculate the average pressure value P. ave ; The second differential pressure comparison unit compares P. i With P ave ,when At that time, obtain the real-time temperature T of the i-th tire. i ; Anomaly analysis and early warning unit, used to compare T i Compared with the preset safe temperature threshold, when T i An alarm will be triggered if the preset safe temperature threshold is exceeded. in, , 1≤i≤m, a and b are both preset values.

6. The intelligent logistics monitoring system for long-distance transportation according to claim 5, characterized in that, The anomaly analysis and early warning unit is also preset with a warning pressure value P. 警 ; When P i >P 警 When this occurs, a Level 1 alarm is activated; When P is detected i >cP 警 When this occurs, a level two alarm will be activated; Where c is a preset value and c>1, the first-level alarm is to alert the driver, and the second-level alarm is to alert both the driver and the monitoring platform simultaneously.

7. The intelligent logistics monitoring system for long-distance transportation according to claim 6, characterized in that, The gradient analysis unit is also preset with a maximum threshold for pressure change gradient; When P i When the pressure change gradient at the previous monitoring time point exceeds the maximum threshold of the pressure change gradient, the anomaly analysis and early warning unit activates a level two alarm.

8. The intelligent logistics monitoring system for long-distance transportation according to claim 5, characterized in that, The anomaly analysis and early warning unit is also preset with a risk observation mode, which runs when the alarm is activated. The risk observation mode specifically includes: continuously monitoring P after the alarm is activated. i An alarm will sound every n seconds until the abnormal situation is resolved; n is a preset value.

9. A smart logistics monitoring device for long-distance transportation, comprising: A memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, characterized in that: when the program instructions are loaded and executed by the processor, they implement the intelligent logistics monitoring method for long-distance transportation as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the intelligent logistics monitoring method for long-distance transportation as described in any one of claims 1 to 4.

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