Intelligent logistics monitoring system and method based on big data

Abstract

The present application provides an intelligent logistics monitoring method based on big data, which relates to the field of logistics and transportation technology, and is used to improve the problem that the risks in logistics strategies cannot be evaluated and quantified, and the logistics strategies cannot be monitored. The method includes: establishing a first mapping table of road sections, traffic information, and road section risk influencing factors. Obtaining the path information of the path selected by the logistics strategy, the path information includes road section information and traffic information. Obtaining the path risk influencing factor of the logistics strategy based on the road section information, traffic information, and the first mapping table, wherein the path risk influencing factor is used to indicate the risk of the path causing the goods to fail. Establishing a second mapping table of goods and failure parameters, and obtaining the failure parameters of the goods to be transported based on the goods to be transported and the second mapping table. Obtaining the risk assessment value of the logistics strategy based on the path risk influencing factor and the failure parameter. Monitoring the risk of the logistics strategy based on the risk assessment value.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of logistics and transportation, and in particular to an intelligent logistics monitoring system and method based on big data. Background Art

[0002] In the field of modern logistics and transportation, enterprises are faced with complex supply chain management challenges, including but not limited to transportation cost control, cargo safety, timeliness guarantee, environmental adaptability, etc. Although the logistics industry has adopted a variety of logistics strategies to optimize these challenges, the existing logistics and transportation system still has some key defects, especially in risk assessment and monitoring.

[0003] Existing logistics strategies usually focus on cost-benefit analysis and transportation efficiency, but lack a comprehensive assessment of potential risks. These risks include but are not limited to cargo loss, delays during transportation, the impact of environmental factors on transportation, and fluctuations in market demand. Due to the lack of effective risk assessment tools and methods, logistics companies often find it difficult to predict and mitigate these risks, resulting in supply chain fragility and reduced transportation efficiency.

[0004] In addition, existing logistics systems often rely on qualitative analysis and empirical judgment, lacking quantitative risk assessment methods to evaluate and monitor logistics strategies. This makes it difficult to make scientific and reasonable decisions in the face of complex and changing environments, increasing operating costs and potentially affecting customer satisfaction. In some cases, risk assessment of logistics strategies is even completely ignored, resulting in companies being unable to respond in a timely manner when unforeseen events occur, resulting in economic losses and reputation damage.

[0005] In summary, the existing technology has the problem of being unable to evaluate and quantify the risks in logistics strategies, and being unable to monitor logistics strategies. Summary of the invention

[0006] The embodiments of the present application provide an intelligent logistics monitoring system and method based on big data, which are used to improve the problems in the prior art that the risks in logistics strategies cannot be evaluated and quantified, and the logistics strategies cannot be monitored.

[0007] To achieve the above objectives, the embodiments of the present application adopt the following technical solutions:

[0008] In a first aspect, a smart logistics monitoring method based on big data is provided, which is used to evaluate and monitor a logistics strategy method. The method includes: establishing a first mapping table of road sections, traffic information, and road section risk influencing factors. Obtaining path information of the path selected by the logistics strategy, the path information includes road section information and traffic information. Obtaining the path risk influencing factor of the logistics strategy based on the road section information, traffic information, and the first mapping table, wherein the path risk influencing factor is used to indicate the risk of the path causing the goods to fail. Establishing a second mapping table of goods and failure parameters, and obtaining the failure parameters of the goods to be transported based on the goods to be transported and the second mapping table. Obtaining a risk assessment value of the logistics strategy based on the path risk influencing factor and the failure parameter. Monitoring the risk of the logistics strategy based on the risk assessment value.

[0009] In the case of existing data, a mapping relationship between the road section, traffic information and the road section risk factor can be obtained according to the acquired road section type, traffic information and road section risk factor, and a first mapping table related to the above parameters can be established.

[0010] Extract the path information of the path selected in the traffic flow strategy. The path information may include the road section information of the path and the current traffic information of the path. The road section information includes but is not limited to the road section type, the number of each road section type, etc.

[0011] After the first mapping table, the road section information and traffic information of the path in the logistics strategy are available, the road section risk factor of each road section in the path can be obtained according to the corresponding mapping relationship. According to the road section risk factor of each road section, the path risk impact factor of the logistics strategy can be obtained.

[0012] Each cargo has different resistance to damage due to different materials and structures. When the external impact reaches a certain level, the cargo may be damaged, unusable, or lose its original value. The critical value of the external impact when the cargo reaches the above state is used as its failure parameter. Through a large number of tests and big data statistics, the failure parameters corresponding to each type of cargo can be obtained, thereby establishing a second mapping table between cargo and failure parameters.

[0013] The failure parameters of the goods to be transported can be obtained according to the type of goods to be transported and the second mapping table. When evaluating the logistics strategy, the path risk impact factor of the logistics strategy and the failure parameters of the goods to be transported can be used to characterize the risk of the logistics strategy. Therefore, the risk assessment value of the logistics strategy can be obtained according to the path risk impact factor and the failure parameter.

[0014] During the logistics transportation process, the risks of executing logistics strategies can be monitored at all times. When the risk assessment value of the logistics strategy to be executed is high, the logistics strategy can be changed or the risk can be avoided in time.

[0015] In a possible implementation of the first aspect, traffic information may include a traffic level of a road section. At this time, the step of establishing a first mapping table of road sections, traffic information, and road section risk impact factors may include: obtaining a road section risk parameter of the road section. Obtaining a traffic risk parameter of the traffic level. Obtaining a road section risk impact factor of the road section at the corresponding traffic level based on the road section risk parameter and the traffic risk parameter. Establishing a first mapping table based on the road section, the traffic level, and the road section risk impact factor.

[0016] In a possible implementation of the first aspect, the road section includes a first road section, a second road section and a third road section, and the smooth travel level includes a first smooth travel level, a second smooth travel level and a third smooth travel level. The road section information includes the number of the first road section, the second road section and the third road section in the path; the traffic information includes the smooth travel levels corresponding to the first road section, the second road section and the third road section in the path. The path risk impact factor of the logistics strategy is obtained according to the road section information, the traffic information and the first mapping table, including: according to the number of the first road section, the second road section and the third road section in the path, and the smooth travel levels corresponding to the first road section, the second road section and the third road section in the path, the total risk impact factor of the first road section, the second road section and the third road section is obtained. The path risk impact factor of the logistics strategy is obtained according to the total risk impact factor of the first road section, the second road section and the third road section.

[0017] In a possible implementation of the first aspect, obtaining the traffic risk parameter of the free-travel level includes: obtaining the frequency of vehicle emergency braking and the intensity of vehicle emergency braking under the free-travel level. The traffic risk parameter is obtained according to the frequency of emergency braking, the intensity of emergency braking and a first formula, and the first formula is: Among them, F sg is the traffic risk parameter, F js is the frequency of emergency braking, I js is the intensity of emergency braking, a, b, c are constants.

[0018] In a possible implementation of the first aspect, the method further includes: obtaining a section loss parameter of the section. Obtaining a brake loss parameter of the smooth travel level. Obtaining a section loss influence factor of the vehicle on the section at the corresponding smooth travel level based on the section loss parameter and the brake loss parameter. Obtaining a total loss influence factor of the first section, the second section and the third section based on the number of the first section, the second section and the third section in the path and the smooth travel level corresponding to the first section, the second section and the third section in the path. Obtaining a path loss assessment value of the logistics strategy based on the total loss impact factor of the first section, the second section and the third section. Obtaining a recommendation degree of the logistics strategy based on the risk assessment value and the loss assessment value.

[0019] In a possible implementation of the first aspect, the method further includes: obtaining a section energy consumption parameter of the section. Obtaining a traffic energy consumption parameter of a smooth traffic level. Obtaining an energy consumption impact factor of a vehicle on a section at a corresponding smooth traffic level based on the section energy consumption parameter and the traffic energy consumption parameter. Obtaining a total energy consumption impact factor of the first section, the second section, and the third section based on the number of the first section, the second section, and the third section in the path and the smooth traffic level corresponding to the first section, the second section, and the third section in the path. Obtaining an energy consumption evaluation value of the logistics strategy based on the total energy consumption impact factor of the first section, the second section, and the third section. Obtaining a recommendation degree of the logistics strategy based on the risk evaluation value, the loss evaluation value, and the energy consumption evaluation value.

[0020] In a possible implementation of the first aspect, the method further includes: obtaining a section arrival time parameter of the section;

[0021] Obtain the traffic arrival time parameters of the smooth traffic level. Obtain the arrival time impact factor of the vehicle on the road section under the corresponding smooth traffic level according to the section arrival time parameter and the traffic arrival time parameter. Obtain the total arrival time impact factor of the first section, the second section and the third section according to the number of the first section, the second section and the third section in the path and the smooth traffic level corresponding to the first section, the second section and the third section in the path. Obtain the arrival time evaluation value of the logistics strategy according to the total arrival time impact factor of the first section, the second section and the third section. Obtain the recommendation degree of the logistics strategy according to the risk assessment value, the loss assessment value, the energy consumption assessment value, the arrival time assessment value and the second formula. The second formula is: Among them, T pg For recommendation, is the risk assessment value, is the loss assessment value, is the energy consumption assessment value, is the estimated arrival time, Z 1 , Z 2 , Z 3 and Z 4 is a constant, and Z 1 +Z 2 +Z 3 +Z 4 =1.

[0022] In a possible implementation of the first aspect, the goods to be transported include multiple goods, and obtaining the expiration parameters of the goods to be transported according to the goods to be transported and the second mapping table includes: obtaining the value of each of the goods and the total value of the goods to be transported. According to the multiple goods and the second mapping table, obtaining the expiration parameter of each of the goods. Obtaining the expiration parameter of the goods to be transported according to the value of each of the goods, the total value of the goods to be transported, and the expiration parameter of each of the goods.

[0023] In a possible implementation of the first aspect, the method further includes: obtaining a location of the goods to be transported, and determining a deviation value of the goods to be transported according to the location of the goods to be transported and path information of a path selected by the logistics strategy.

[0024] In a second aspect, an embodiment of the present application provides an intelligent logistics monitoring system based on big data, which is used to execute the method in any implementation of the first aspect. The system includes: an acquisition module, which is used to acquire the path information of the path selected by the logistics strategy, a data processing module, which is coupled to the acquisition module, and the data processing module is used to obtain the risk assessment value of the logistics strategy based on the path information and the failure parameters of the goods to be transported. A monitoring module, which is used to monitor the risk of the logistics strategy according to the risk assessment value. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flowchart of a monitoring method provided for some embodiments of the present application;

[0026] Figure 2 A flowchart of a monitoring method provided for other embodiments of the present application;

[0027] Figure 3 A flowchart of a monitoring method provided for other embodiments of the present application;

[0028] Figure 4 A flowchart of a monitoring method provided for other embodiments of the present application;

[0029] Figure 5 A flowchart of a monitoring method provided for other embodiments of the present application;

[0030] Figure 6 A flowchart of a monitoring method provided for other embodiments of the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0032] In the following, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0033] In addition, in the present application, directional terms such as "up", "down", "left" and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts, which are used for relative description and clarification, and may change accordingly according to the change in the orientation of the components in the drawings.

[0034] In this application, unless otherwise specified or limited, the term "connection" should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. In addition, the term "coupling" can be a way of achieving electrical connection for signal transmission.

[0035] As used herein, "about," "substantially," or "approximately" includes the stated value and an average value that is within an acceptable range of variation from the particular value as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0036] In the embodiments of the present application, the words "exemplarily" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present related concepts in a specific way.

[0037] Existing logistics strategies usually focus on cost-benefit analysis and transportation efficiency, but lack a comprehensive assessment of potential risks. These risks include but are not limited to cargo loss, delays during transportation, the impact of environmental factors on transportation, and fluctuations in market demand. Due to the lack of effective risk assessment tools and methods, logistics companies often find it difficult to predict and mitigate these risks, resulting in supply chain fragility and reduced transportation efficiency.

[0038] In addition, existing logistics systems often rely on qualitative analysis and empirical judgment, and lack quantitative risk assessment methods to evaluate and monitor logistics strategies. This makes it difficult to make scientific and reasonable decisions in the face of complex and changing environments, increases operating costs and may affect customer satisfaction. In some cases, the risk assessment of logistics strategies is even completely ignored, resulting in the inability of enterprises to respond in a timely manner when unforeseen events occur, resulting in economic losses and reputation damage. In summary, there are problems in the existing technology that cannot evaluate and quantify the risks in logistics strategies, as well as the inability to monitor logistics strategies.

[0039] The embodiments of the present application provide an intelligent logistics monitoring system and method based on big data, which are used to improve the problems in the prior art that the risks in logistics strategies cannot be evaluated and quantified, and the logistics strategies cannot be monitored.

[0040] This method is used to evaluate and monitor logistics strategies. Figures 1 to 6 , the method may include:

[0041] S100: Establish a first mapping table of road sections, traffic information and road section risk influencing factors.

[0042] In the case of existing data, a mapping relationship between the road section, traffic information and the road section risk factor can be obtained according to the acquired road section type, traffic information and road section risk factor, and a first mapping table related to the above parameters can be established.

[0043] In some embodiments, according to different types of road sections, the road section may include a first road section, a second road section and a third road section. For example, the first road section, the second road section and the third road section may represent one of an uphill road section, a flat road section and a downhill road section respectively. Based on the objective factors of each road section, the risk of a vehicle traveling on each road section is different. According to the data information of vehicle accidents on each road section, the road section risk parameters of different road sections can be obtained by statistically analyzing the big data. The road section risk parameters can be used to characterize the risk of a vehicle when running on the road section.

[0044] Traffic information may include the traffic smoothness level of a road section. The traffic smoothness level may indicate the smoothness of the transportation vehicles passing through the road section. It is understandable that when there are many vehicles in traffic congestion, the smoothness of the transportation vehicles passing through is less than when there are fewer vehicles. In relative terms, the lower the traffic smoothness level, the lower the smoothness of the vehicles passing through the road section, and thus, the higher the risk of vehicles driving on the road section. The higher the traffic smoothness level, the smoother the vehicles passing through the road section, and the lower the risk of vehicles driving on the road section. For the convenience of evaluation, the risks under different traffic smoothness levels are quantified using traffic risk parameters. The quantification process can be performed based on the big data of the traffic smoothness level and accident conditions of the corresponding road section.

[0045] In some embodiments, according to different traffic conditions, the traffic congestion level may include a first traffic congestion level, a second traffic congestion level, and a third traffic congestion level. For example, the first traffic congestion level, the second traffic congestion level, and the third traffic congestion level may respectively represent one of very congested, generally congested, and good traffic conditions.

[0046] Therefore, the step of establishing a first mapping table of road sections, traffic information and road section risk influencing factors may include:

[0047] S101. Obtain a road section risk parameter of a road section.

[0048] S102: Obtain traffic risk parameters of the smooth traffic level.

[0049] It should be noted that when acquiring the road section risk parameters, it is necessary to consider the impact of traffic factors. When acquiring the traffic risk parameters, it is necessary to consider the impact of excluding the road section, and only consider the risk brought by the level of free flow during analysis, such as conducting data tests of multiple levels of free flow on a flat road. Of course, the testing and acquisition methods of the above data are only examples, and those skilled in the art can set them as needed. The analysis method of the above data can also be selected as needed by those skilled in the art.

[0050] S103. Obtain a road section risk impact factor of the road section at a corresponding traffic level according to the road section risk parameter and the traffic risk parameter.

[0051] S104: Establish a first mapping table according to the road section, the traffic level, and the road section risk influencing factor.

[0052] In this way, a first mapping table of the road section risk factor, road section and traffic level can be obtained. The road section risk factor includes both the risk parameters caused by the road section and the risk factors caused by traffic, so that the road section risk factor can better characterize the risk of transport vehicles when traveling on the corresponding road section.

[0053] The frequency and intensity of emergency braking at the corresponding traffic level can be obtained through statistical analysis of big data. For example, the speed of the vehicle at different times can be calculated through the footage captured by the intersection camera, thereby obtaining the vehicle's braking acceleration. The greater the braking acceleration, the higher the braking intensity. The frequency of braking and the correlation between braking and accidents can also be obtained through the footage.

[0054] Then, S102, obtaining traffic risk parameters of the smooth traffic level may include:

[0055] S1021. Obtain the frequency and intensity of vehicle emergency braking under the smooth traffic level.

[0056] S1022. Obtain a traffic risk parameter according to the frequency of emergency braking, the intensity of emergency braking, and a first formula. The first formula is: Among them, F sg is the traffic risk parameter, F js is the frequency of emergency braking, I js is the intensity of emergency braking, a, b, c are constants.

[0057] It is understandable that the above traffic risk parameters do not take the impact of road sections into account when calculating the statistics. In this way, the traffic risks brought by the road section types can be ignored, and the risks of logistics strategies can be evaluated with pure traffic risk parameters.

[0058] In other embodiments, traffic risk parameters of a specific road section at a specific level of free travel may be counted to obtain accurate risk parameters suitable for the corresponding road section. For example, the frequency and intensity of sudden braking of vehicles at a specific level of free travel of the first road section, the second road section, and the third road section may be counted to obtain traffic risk parameters of the corresponding road section at the corresponding level of free travel.

[0059] S200: Obtain path information of the path selected by the logistics strategy, where the path information includes road section information and traffic information.

[0060] Extract the path information of the path selected in the traffic flow strategy. The path information may include the road section information of the path and the current traffic information of the path. The road section information includes but is not limited to the road section type, the number of each road section type, etc.

[0061] For example, the segment information may include the number of the first segment, the second segment, and the third segment in the path. The traffic information may include the traffic smoothness level corresponding to the first segment, the second segment, and the third segment in the path.

[0062] S300: Obtain a path risk impact factor of a logistics strategy according to the road section information, the traffic information and the first mapping table, wherein the path risk impact factor is used to indicate the risk of the path causing the goods to fail.

[0063] After the first mapping table, the road section information and traffic information of the path in the logistics strategy are available, the road section risk factor of each road section in the path can be obtained according to the corresponding mapping relationship. According to the road section risk factor of each road section, the path risk impact factor of the logistics strategy can be obtained.

[0064] Exemplarily, S300, obtaining the path risk influencing factor of the logistics strategy according to the road section information, the traffic information and the first mapping table, may include:

[0065] S301. Obtain the total risk impact factor of the first section, the second section and the third section according to the number of the first section, the second section and the third section in the path and the traffic smoothness levels corresponding to the first section, the second section and the third section in the path.

[0066] For example, the section risk parameters of the first section, the second section, and the third section are L 1 , L 2 and L 3 The traffic risk parameters of the first level of traffic flow, the second level of traffic flow, and the third level of traffic flow are J 1 , J 2 and J 3 The road section risk impact factor of the corresponding road section can be obtained according to the first mapping table.

[0067] For example, when the traffic level of the first road section is the first traffic level, the road section risk impact factor of the road section that can be obtained according to the first mapping table is:

[0068] If there are three first sections in the route, the corresponding traffic levels of the three first sections are the first traffic level, the second traffic level and the third traffic level. Then the total risk impact factor of the first section of the route is:

[0069] The total risk impact factor of the second section and the third section can refer to the calculation method of the total risk impact factor of the first section. The total risk factors of the first section, the second section and the third section are obtained in sequence, and the path risk impact factor of the path can be obtained.

[0070] The path risk impact factor of the logistics strategy is obtained according to the total risk impact factors of the first section, the second section and the third section. in, is the path risk influencing factor, is the total risk impact factor of the first section, is the total risk impact factor of the second section, is the total risk influencing factor of the third section.

[0071] S400: Establish a second mapping table between goods and expiration parameters, and obtain the expiration parameters of the goods to be transported according to the goods to be transported and the second mapping table.

[0072] Each cargo has different resistance to damage due to different materials and structures. When the external impact reaches a certain level, the cargo may be damaged, unusable, or lose its original value. The critical value of the external impact when the cargo reaches the above state can be used as its failure parameter. Through a large number of tests and big data statistics, the failure parameters corresponding to each type of cargo can be obtained, thereby establishing a second mapping table between cargo and failure parameters.

[0073] The failure parameter of the goods to be transported can be obtained according to the type of goods to be transported and the second mapping table. It can be understood that there may be multiple types of goods to be transported, so the failure parameter of the goods to be transported can be a comprehensive value. Exemplarily, the failure parameter of the goods to be transported can be the failure parameter of the goods with the highest total value among the goods to be transported, or the failure parameter of the goods to be transported can be the average value of the failure parameters of all types of goods to be transported, or the failure parameter of the goods to be transported can be the failure parameter of the goods that are most likely to fail among the goods to be transported.

[0074] S500: Obtain a risk assessment value of the logistics strategy according to the path risk influencing factor and the failure parameter.

[0075] When evaluating logistics strategies, the path risk impact factor of the logistics strategy and the failure parameter of the goods to be transported can be used to characterize the risk of the logistics strategy. Therefore, the risk assessment value of the logistics strategy can be obtained based on the path risk impact factor and the failure parameter.

[0076] For example, the failure parameter of the goods to be transported is , then the risk assessment value of the logistics strategy is Can be:

[0077] S600. Monitor the risk of the logistics strategy according to the risk assessment value.

[0078] During the logistics transportation process, the risk of the logistics strategy to be executed can be monitored at all times. When the risk assessment value of the logistics strategy to be executed is high, the logistics strategy can be changed in time or the risk can be avoided. Therefore, the intelligent logistics monitoring method provided by the present application can evaluate and quantify the risk of the logistics strategy, and improve the problem that the logistics strategy cannot be monitored in the prior art.

[0079] In some embodiments, the monitoring method may further include:

[0080] S710: Obtain the section loss parameter of the road section. The section loss parameter can be used to indicate the loss of the vehicle on the road section, such as the wear and tear of components, such as the engine, gearbox, suspension system, etc. The data can be obtained through a large number of tests, evaluations and analyses of the vehicle on the corresponding road section.

[0081] S720: Obtain brake loss parameters for the traffic flow level. Different levels of traffic conditions have different brake losses, and this data can also be obtained by analyzing the big data of the vehicle at the corresponding traffic flow level.

[0082] It should be noted that the influence of traffic factors needs to be considered when obtaining the road section loss parameters, such as testing on closed roads. The influence of road sections needs to be excluded when obtaining the traffic loss parameters, and only the influence of the brake loss caused by the level of free travel is considered during analysis, such as testing data of multiple levels of free travel on a flat road. Of course, the above data testing and acquisition methods are only examples, and those skilled in the art can set them as needed based on their needs.

[0083] S730. Obtain a road section loss influence factor for the vehicle on a road section at a corresponding traffic smoothness level according to the road section loss parameter and the brake loss parameter.

[0084] Exemplarily, the segment loss parameters of the first segment, the second segment, and the third segment are H 1 , H 2 and H 3 The brake loss parameters for the first level of smooth travel, the second level of smooth travel, and the third level of smooth travel are T1 、T 2 and T 3 .

[0085] When the traffic level of the first road section is the first traffic level, the road loss impact factor of the road section is: in, is the section loss influencing factor of the first section, is the section loss parameter of the first section, It is the brake loss parameter for the first level of smooth driving.

[0086] S740. Obtain the total loss impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the smooth travel levels corresponding to the first section, the second section, and the third section in the path.

[0087] If there are three first sections in the route, the corresponding traffic levels of the three first sections are the first traffic level, the second traffic level and the third traffic level. Then the total loss impact factor of the first section of the route is:

[0088] The total loss impact factors of the second and third sections can refer to the calculation method of the total loss impact factor of the first section. The total loss impact factors of the first section, the second section and the third section are obtained in sequence, and the loss evaluation value of the path can be obtained.

[0089] S750: Obtain a path loss evaluation value of the logistics strategy according to the total loss impact factors of the first road section, the second road section, and the third road section. in, is the loss assessment value of the logistics strategy, is the total loss influencing factor of the first section, is the total loss influencing factor of the second section, is the total loss influencing factor of the third section.

[0090] S760. Obtain a recommendation for a logistics strategy based on the risk assessment value and the loss assessment value.

[0091] When the risk assessment value of the logistics strategy is obtained and loss assessment of logistics strategies After that, the recommendation degree of the logistics strategy can be obtained based on the two data. It can be understood that there are many routes from the departure point to the destination, and the routes in each logistics strategy are different. It is necessary to reasonably evaluate the recommendation degree of each logistics strategy. The recommendation degree can be used as the basis for selecting a logistics strategy.

[0092] In some embodiments, the method further comprises:

[0093] S801, obtaining a road section energy consumption parameter of a road section. The road section energy consumption parameter is used to characterize the energy consumption of a vehicle when running on the road section. The data can be obtained through big data analysis of vehicles running on the corresponding road section.

[0094] S802: Obtain traffic energy consumption parameters of the smooth traffic level. Traffic energy consumption parameters are used to characterize the energy consumption of the vehicle when it is running at the smooth traffic level. The data can be obtained through big data analysis of the vehicle running at the corresponding smooth traffic level.

[0095] It should be noted that the influence of traffic factors needs to be considered when acquiring the energy consumption parameters of road sections, such as testing on closed roads. The influence of road sections needs to be excluded when acquiring traffic energy consumption parameters, and only the energy consumption influence caused by the level of free flow is considered during analysis, such as testing data of multiple levels of free flow on a flat road. Of course, the above data testing and acquisition methods are only examples, and those skilled in the art can set them as needed based on their needs.

[0096] S803: Obtain an energy consumption influencing factor of a vehicle on a road section at a corresponding traffic level according to the road section energy consumption parameter and the traffic energy consumption parameter.

[0097] For example, the energy consumption parameters of the first section, the second section, and the third section are N 1 、N 2 and N 3 The traffic energy consumption parameters of the first level of free flow, the second level of free flow, and the third level of free flow are U 1 , U 2 and U 3 .

[0098] When the traffic level of the first road section is the first traffic level, the energy consumption influencing factor of the road section is: in, is the energy consumption influencing factor of the first section, is the energy consumption parameter of the first section, It is the traffic energy consumption parameter of the first level of smooth traffic.

[0099] S804. Obtain a total energy consumption impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the traffic smoothness levels corresponding to the first section, the second section, and the third section in the path.

[0100] If there are three first sections in the route, the corresponding traffic levels of the three first sections are the first traffic level, the second traffic level and the third traffic level. Then the total loss impact factor of the first section of the route is:

[0101] The total energy consumption impact factors of the second and third sections can refer to the calculation method of the total energy consumption impact factor of the first section. The total energy consumption impact factors of the first section, the second section and the third section are obtained in sequence, and the energy consumption evaluation value of the path can be obtained.

[0102] S805 . Obtain an energy consumption evaluation value of the logistics strategy according to the total energy consumption influencing factors of the first road section, the second road section, and the third road section. in, is the energy consumption evaluation value of the logistics strategy, is the total energy consumption influencing factor of the first section, is the total energy consumption influencing factor of the second section, is the influencing factor of the total energy consumption of the third section.

[0103] S806. Obtain a recommendation for a logistics strategy based on the risk assessment value, the loss assessment value, and the energy consumption assessment value.

[0104] In some other embodiments, taking the first section as an upper wave section as an example, obtaining the section energy consumption parameter of the section may include:

[0105] The starting height and ending height of multiple first sections in the path are obtained. It should be noted that, for ease of calculation, the heights in the embodiments of the present application are all horizontal heights. It is understandable that the art can also define the height in other ways based on demand, as long as it is easy to calculate and can achieve the purpose of the present application.

[0106] Get the total climbing height of the path. Subtract the starting height from the ending height of each first section to get the height difference of each first section. Add the height differences of each first section to get the total climbing height of the path and get the climbing height of the path. Get the height of the starting point and the end point of the path, and subtract the height of the starting point from the height of the end point to get the climbing height of the path.

[0107] The energy consumption parameters of the road section are obtained according to the total climbing height and the required climbing height.

[0108] Exemplarily, the road section energy consumption parameter may be a ratio of the total climbing height to the required climbing height. It is understandable that the closer the ratio is to 1, the lower the energy consumption parameter.

[0109] In some other embodiments, the method further comprises:

[0110] S901, obtaining a section arrival time parameter of a section. The section arrival time parameter is used to characterize the impact of a vehicle running on the section on the arrival time.

[0111] S902: Obtaining a traffic arrival time parameter of a traffic smoothness level. The traffic arrival time parameter is used to characterize the impact of a vehicle on the arrival time when running at the traffic smoothness level.

[0112] It should be noted that the arrival time parameters of the road sections need to be obtained by excluding the impact of traffic factors, such as testing on closed roads. The arrival time parameters of traffic need to be obtained by excluding the impact of road sections, and only the impact of the traffic level on the arrival time is considered during analysis, such as testing data of multiple traffic levels on a flat road. Of course, the above data testing and acquisition methods are only examples, and those skilled in the art can set them as needed based on their needs.

[0113] S903. Obtain an arrival time influence factor of a vehicle on a road section at a corresponding traffic level according to a road section arrival time parameter and a traffic arrival time parameter.

[0114] For example, the arrival time parameters of the first section, the second section, and the third section are Y, 1 , Y 2 and Y 3 The traffic arrival time parameters for the first level of traffic flow, the second level of traffic flow, and the third level of traffic flow are M 1 、M 2 and M 3 .

[0115] When the traffic level of the first road section is the first traffic level, the arrival time influencing factor of the road section is: in, is the arrival time influencing factor of the first section, is the section arrival time parameter of the first section, It is the traffic arrival time parameter of the first level of smooth traffic.

[0116] S904. Obtain a total arrival time influence factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the traffic smoothness levels corresponding to the first section, the second section, and the third section in the path.

[0117] If there are three first sections in a route, the traffic levels corresponding to the three first sections are the first traffic level, the second traffic level, and the third traffic level. Then the total arrival time impact factor of the first section of the route is:

[0118] The total arrival time impact factor of the second section and the third section can refer to the calculation method of the total arrival time impact factor of the first section. The total arrival time impact factor of the first section, the second section and the third section is obtained in sequence, and the arrival time evaluation value of the path can be obtained.

[0119] S905 . Obtain an arrival time evaluation value of the logistics strategy according to the total arrival time impact factors of the first road section, the second road section, and the third road section. in, is the time evaluation value of the logistics strategy, is the influencing factor of the total arrival time of the first section, is the influencing factor of the total arrival time of the second section, is the influencing factor of the total arrival time of the third section.

[0120] S906. Obtain the recommendation degree of the logistics strategy according to the risk assessment value, the loss assessment value, the energy consumption assessment value, the arrival time assessment value and the second formula. The second formula is: Among them, T pg For recommendation, is the risk assessment value, is the loss assessment value, is the energy consumption assessment value, is the estimated arrival time, Z 1 , Z 2 , Z 3 and Z 4 is a constant, and Z 1 +Z 2 +Z 3 +Z 4 =1.

[0121] In the above embodiment, the recommendation degree of the logistics strategy based on some parameters can refer to the calculation method in this embodiment.

[0122] In some embodiments, the cargo to be transported includes multiple cargoes, and the failure parameters of the cargo to be transported are obtained according to the cargo to be transported and the second mapping table, including:

[0123] Get the value of each shipment and the total value of the shipment to be transported.

[0124] According to the multiple goods and the second mapping table, the expiration parameter of each of the goods is obtained.

[0125] The failure parameter of the goods to be transported is obtained according to the value of each of the goods, the total value of the goods to be transported and the failure parameter of each of the goods.

[0126] Exemplarily, when the total value of a certain cargo accounts for the highest proportion of the total value of the cargo to be transported and its failure parameter is the smallest (most likely to fail), the failure parameter of the cargo is used as the failure parameter of the cargo to be transported.

[0127] Exemplarily, the total value of the goods and the failure parameter may be weighted for analysis.

[0128] Of course, those skilled in the art can also perform various analyses based on the above parameters to obtain failure parameters of the goods to be transported. This application does not limit this.

[0129] In some embodiments, the method further comprises:

[0130] Get the location of the goods to be transported.

[0131] The deviation value of the goods to be transported is determined based on the location of the goods to be transported and the path information of the path selected by the logistics strategy.

[0132] Exemplarily, the above deviation value is obtained based on the current position of the goods to be transported and the position of the road section planned for the goods to be transported in the path information of the path selected by the logistics strategy. When the deviation value is large, an information reminder is issued.

[0133] It should be noted that the calculation of various data in the above embodiments of the present application may be to normalize the data first so that the data are in the same dimension. It is also possible to perform partial calculations and then perform normalization, which is not limited in the present application. Those skilled in the art can process the data to different degrees according to their needs.

[0134] The embodiment of the present application also provides an intelligent logistics monitoring system based on big data, which is used to execute an intelligent logistics monitoring method based on big data. The system includes: an acquisition module, a data processing module and a monitoring module. The acquisition module is used to acquire the path information of the path selected by the logistics strategy.

[0135] The data processing module is coupled to the acquisition module, and is used to obtain the risk assessment value of the logistics strategy according to the path information and the failure parameters of the goods to be transported. The monitoring module is used to monitor the risk of the logistics strategy according to the risk assessment value.

[0136] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0137] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0139] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated units may be implemented in the form of hardware.

[0140] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An intelligent logistics monitoring method based on big data, characterized in that: The method comprises: Establishing a first mapping table of road sections, traffic information and road section risk influencing factors; Obtaining path information of the path selected by the logistics strategy, wherein the path information includes road section information and traffic information; Obtaining a path risk impact factor of the logistics strategy according to the road section information, the traffic information and the first mapping table, wherein the path risk impact factor is used to indicate the risk of a path causing the goods to fail; Establishing a second mapping table between goods and expiration parameters; Obtaining the expiration parameter of the goods to be transported according to the goods to be transported and the second mapping table; Obtaining a risk assessment value of the logistics strategy according to the path risk impact factor and the failure parameter; monitoring the risk of the logistics strategy according to the risk assessment value; The traffic information includes the traffic level of the road section; the first mapping table of the road section, the traffic information and the road section risk influencing factor is established, including: Obtaining a road section risk parameter of the road section; Obtaining traffic risk parameters of the smooth traffic level; Obtaining a road section risk impact factor of the road section corresponding to the smooth traffic level according to the road section risk parameter and the traffic risk parameter; Establishing the first mapping table according to the road section, the traffic smoothness level and the road section risk influencing factor; The road section includes a first road section, a second road section and a third road section, the first road section, the second road section and the third road section respectively represent one of an uphill road section, a flat road section and a downhill road section, and the travel smoothness level includes a first travel smoothness level, a second travel smoothness level and a third travel smoothness level; The road segment information includes the number of the first road segment, the second road segment, and the third road segment in the path; the traffic information includes the traffic smoothness levels corresponding to the first road segment, the second road segment, and the third road segment in the path; The obtaining of the path risk influencing factor of the logistics strategy according to the road section information, the traffic information and the first mapping table includes: Obtaining a total risk impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the travel smoothness levels corresponding to the first section, the second section, and the third section in the path; Obtaining a path risk impact factor of the logistics strategy according to the total risk impact factor of the first road section, the second road section and the third road section; The traffic risk parameters for obtaining the smooth traffic level include: Obtaining the frequency and intensity of sudden braking of vehicles under the smooth traffic level; The traffic risk parameter is obtained according to the frequency of the emergency braking, the intensity of the emergency braking and a first formula, wherein the first formula is: Among them, F sg is the traffic risk parameter, F js is the frequency of emergency braking, I js is the intensity of emergency braking, a, b, c are constants.

2. The intelligent logistics monitoring method based on big data according to claim 1 is characterized in that: The method further comprises: Obtaining a section loss parameter of the section; Obtaining brake loss parameters of the smooth travel level; Obtaining a road section loss influence factor of the vehicle on the road section corresponding to the smooth travel level according to the road section loss parameter and the brake loss parameter; Obtaining a total loss impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the travel smoothness levels corresponding to the first section, the second section, and the third section in the path; Obtaining a loss evaluation value of the logistics strategy according to the total loss impact factor of the first road section, the second road section and the third road section; A recommendation degree of the logistics strategy is obtained according to the risk assessment value and the loss assessment value.

3. The intelligent logistics monitoring method based on big data according to claim 2 is characterized in that: The method further comprises: Obtaining a section energy consumption parameter of the section; Obtaining traffic energy consumption parameters of the smooth traffic level; Obtaining an energy consumption influencing factor of the vehicle on the road section corresponding to the smooth travel level according to the road section energy consumption parameter and the traffic energy consumption parameter; Obtaining a total energy consumption impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the traffic smoothness levels corresponding to the first section, the second section, and the third section in the path; Obtaining an energy consumption evaluation value of the logistics strategy according to the total energy consumption impact factor of the first road section, the second road section and the third road section; The recommendation degree of the logistics strategy is obtained according to the risk assessment value, the loss assessment value and the energy consumption assessment value.

4. The intelligent logistics monitoring method based on big data according to claim 3 is characterized in that: The method further comprises: Obtaining a section arrival time parameter of the section; Obtaining the traffic arrival time parameter of the traffic smoothness level; Obtaining an arrival time influence factor of a vehicle on the road section corresponding to the smooth traffic level according to the road section arrival time parameter and the traffic arrival time parameter; Obtaining a total arrival time impact factor of the first section, the second section, and the third section according to the number of the first section, the second section, and the third section in the path and the traffic smoothness levels corresponding to the first section, the second section, and the third section in the path; Obtaining an arrival time evaluation value of the logistics strategy according to the total arrival time impact factor of the first road section, the second road section, and the third road section; The recommendation degree of the logistics strategy is obtained according to the risk assessment value, the loss assessment value, the energy consumption assessment value, the arrival time assessment value and a second formula, wherein the second formula is: Among them, T pg For recommendation, is the risk assessment value, is the loss assessment value, is the energy consumption assessment value, is the estimated value of the arrival time, Z1, Z2, Z3 and Z4 are constants, and Z1+Z2+Z3+Z4=1.

5. The intelligent logistics monitoring method based on big data according to claim 1 is characterized in that: The goods to be transported include multiple types of goods, and obtaining the expiration parameters of the goods to be transported according to the goods to be transported and the second mapping table includes: Obtaining the value of each of the goods and the total value of the goods to be transported; According to the plurality of goods and the second mapping table, obtaining an expiration parameter of each of the goods; The expiration parameter of the goods to be transported is obtained according to the value of each of the goods, the total value of the goods to be transported and the expiration parameter of each of the goods.

6. The intelligent logistics monitoring method based on big data according to claim 1 is characterized in that: The method further comprises: Obtaining the location of the goods to be transported; The deviation value of the goods to be transported is determined according to the location of the goods to be transported and the path information of the path selected by the logistics strategy.

7. An intelligent logistics monitoring system based on big data, used to execute the method described in any one of claims 1 to 6, characterized in that: The system comprises: An acquisition module, the acquisition module is used to acquire path information of the path selected by the logistics strategy; A data processing module, coupled to the acquisition module, and configured to obtain a risk assessment value of the logistics strategy according to the path information and the failure parameters of the goods to be transported; A monitoring module is used to monitor the risk of the logistics strategy according to the risk assessment value.

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