Intelligent logistics vehicle monitoring system based on GPS positioning

Abstract

The present invention discloses an intelligent logistics vehicle monitoring system based on GPS positioning, relates to the field of logistics vehicle monitoring, and is used to solve the problem that transportation logistics that are sensitive to temperature and humidity are prone to lack of safety monitoring, resulting in reduced attention to cargo monitoring and reduced transportation quality of logistics vehicles. By collecting the number of vehicles in a region and the total length of communication signal transmission delay, it is determined whether the current vehicle monitoring range is adjusted, and then a logistic regression formula is used to calculate the adjustment ratio based on the added value of vehicle specificity scores within the current range and the regional utilization rate within the current range. The product of the base station signal coverage radius obtained by a free space path loss model and the adjustment ratio is used as the adjustment range value. Different adjustment rules are determined according to the adjusted vehicle monitoring range and its adjustment range value, so as to improve the overall monitoring accuracy and efficiency and reduce resource waste and communication delay.

Description

Technical Field

[0001] The present invention relates to the field of logistics vehicle monitoring, and more specifically, to an intelligent logistics vehicle monitoring system based on GPS positioning. Background Art

[0002] In the modern logistics and transportation industry, transportation route optimization, real-time positioning and tracking, cargo safety monitoring and transportation cost savings have become key factors in improving logistics efficiency and competitiveness. GPS is a global satellite navigation system that uses satellites and ground control systems to provide positioning, navigation and timing services. Specifically, the intelligent logistics vehicle monitoring system is a comprehensive platform that integrates multiple technologies, including the global satellite positioning system (GPS), wireless communication technology, on-board sensor networks, big data analysis and artificial intelligence algorithms, etc. It has multiple functions such as vehicle positioning, operating status monitoring, and environmental data collection.

[0003] The prior art has the following deficiencies:

[0004] At present, in the vehicle monitoring system, the vehicle monitoring range refers to the geographical area where the system can effectively monitor the location, status and activities of the vehicle. However, in actual application, the communication signal coverage range is usually used as the vehicle monitoring range, which is easy to cause the lack of safety monitoring for some transportation logistics that are sensitive to temperature and humidity (such as fresh food, medicine, etc.), resulting in a decrease in the attention paid to cargo monitoring and the reduction of the transportation quality of logistics vehicles. Therefore, an intelligent logistics vehicle monitoring system based on GPS positioning is proposed.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent logistics vehicle monitoring system based on GPS positioning, which solves the problems raised in the above-mentioned background technology by applying different product inspection methods.

[0007] To achieve the above object, the present invention provides the following technical solution: an intelligent logistics vehicle monitoring system based on GPS positioning, comprising an adjustment evaluation module, a collection adjustment module, an adjustment analysis module and a supplementary rule module; signal connections between the modules;

[0008] The adjustment and evaluation module is used to collect the number of vehicles in the area and the total length of the communication signal transmission delay, and establish a data analysis model to obtain the determined adjustment coefficient and compare it with the determined threshold, obtain the marking result of the current vehicle monitoring range, and send it to the collection and adjustment module;

[0009] The collection and adjustment module is used to receive the marking results of the current vehicle monitoring range, and based on the marking results of the current vehicle monitoring range, collect the added value of the vehicle specificity scores and the area utilization rate within the current range, substitute them into the logistic regression formula to calculate the adjustment ratio, and send it to the adjustment analysis module;

[0010] The adjustment analysis module is used to receive the adjustment ratio, and use the product of the output result obtained by the free space path loss model and the adjustment ratio as the adjustment range value, and adjust the current vehicle monitoring range according to the adjustment range value, and send the adjusted vehicle monitoring range and its adjustment range value to the supplementary rule module;

[0011] The supplementary rule module is used to obtain the adjusted vehicle monitoring range and its adjustment range value, compare the adjustment range value with the adjustment threshold, determine the necessity of the adjustment range, analyze the vehicles with significant temperature differences within the adjustment range value marked as necessary adjustment, obtain the heat value of heat sources emitted by the vehicle and the vehicle refrigeration attenuation efficiency, and substitute the fuzzy logic to determine the re-adjustment range plan.

[0012] In a preferred embodiment, the real-time geographic coordinates of each vehicle are obtained, and the coordinates of all vehicles are compared with the coordinates of the monitoring center through a coordinate judgment formula, and the vehicles falling within the monitoring boundary are screened out to obtain the number of vehicles in the area;

[0013] By recording the sending timestamp of the vehicle and the receiving timestamp of the monitoring center, and subtracting the sending time of each vehicle from the receiving time of the monitoring center, the total delay length of the communication signal transmission is obtained.

[0014] A weighted calculation is established between the number of vehicles in the area and the total length of the communication signal transmission delay to obtain a determined adjustment coefficient;

[0015] The determined adjustment coefficient is compared and analyzed with the determined adjustment threshold. If it is greater than or equal to the determined adjustment threshold, the current vehicle monitoring range is marked as requiring adjustment.

[0016] In a preferred embodiment, the number of functional sensors installed on the vehicle, the absolute difference between the current temperature of the cargo and the outside temperature, and the absolute difference between the average speed of the current vehicle and the surrounding vehicles are obtained, and weighted average calculation is performed to obtain the specificity score of each vehicle in the current range, and then the sum of the specificity scores of the vehicles in the current range is calculated to obtain the sum z;

[0017] The area utilization rate s within the current monitoring range is calculated by calculating the ratio of the area actually occupied by the monitored vehicles within the current monitoring range to the area of ​​the current monitoring range;

[0018] Substitute the sum of the vehicle specificity scores within the current range and the area utilization rate within the current range into the logistic regression formula to calculate the adjustment ratio. The specific formula is as follows:

[0019] ;

[0020] In the formula, L is the result of logistic regression calculation, e is the natural base, and y is the linear combination term of the logistic regression model. Specifically, y can be set as:

[0021] ;

[0022] In the formula, is the bias term, is the regression coefficient of the sum of the vehicle specificity scores within the current range, is the regression coefficient of regional utilization within the current range.

[0023] In a preferred embodiment, the output result of the free space path loss model is the base station signal coverage radius, which is specifically expressed as follows:

[0024] ;

[0025] In the formula, R is the base station signal coverage radius, c is the speed of light, and f is the signal frequency. is the base station transmission frequency, is the receiving sensitivity, and L is the allowed path loss.

[0026] In a preferred embodiment, the base station signal coverage radius is used as the output result of the free space path loss model, and is multiplied by the adjustment ratio to obtain the adjustment range value;

[0027] The current vehicle monitoring range is adjusted according to the adjustment range value to obtain an adjusted vehicle monitoring range.

[0028] In a preferred embodiment, the adjustment range value is obtained and compared with the preset adjustment threshold value for analysis, specifically:

[0029] If the adjustment range value is greater than or equal to the adjustment threshold, the adjustment range value is marked as necessary adjustment;

[0030] If the adjustment range value is less than the adjustment threshold, the adjustment range is marked as unnecessary adjustment;

[0031] Filter out the adjustment range values ​​marked as unnecessary adjustment results;

[0032] Collect the adjustment range values ​​marked as necessary adjustment results and analyze the vehicles with significant temperature differences within the range.

[0033] In a preferred embodiment, the temperature difference is calculated by subtracting the internal temperature of the cargo box collected by a temperature sensor installed inside the vehicle cargo box from the external temperature collected by a temperature sensor installed outside the cargo box, and the temperature difference is compared with a preset temperature threshold. Vehicles with a temperature greater than or equal to the temperature threshold are marked as vehicles with significant temperature differences.

[0034] In a preferred embodiment, a heat source sensing device is installed around the vehicle to collect heat radiation data around the vehicle, and the effective heat conduction with the vehicle surface is calculated to obtain the heat value emitted by the heat source around the vehicle;

[0035] The vehicle refrigeration attenuation efficiency is obtained by recording the refrigeration capacity of the equipment under standard environmental conditions as the benchmark refrigeration efficiency, monitoring the temperature change rate in the cargo box, calculating the actual refrigeration efficiency, subtracting the benchmark refrigeration efficiency from the actual refrigeration efficiency, and calculating the ratio with the benchmark refrigeration efficiency.

[0036] In a preferred embodiment, the heat value of the heat source emitted from the vehicle surroundings and the vehicle refrigeration attenuation efficiency are defined as input variables and divided into different fuzzy sets respectively;

[0037] Define the readjustment range result as the output variable and divide it into fuzzy sets;

[0038] Formulate fuzzy rules to describe the impact of the heat value of heat sources emitted around the vehicle and the vehicle refrigeration decay efficiency on the readjustment range results;

[0039] Perform fuzzy reasoning based on fuzzy rules to determine the readjustment range plan.

[0040] Technical effects and advantages of the present invention:

[0041] 1. The present invention determines whether the current vehicle monitoring range should be adjusted by collecting the number of vehicles in the area and the total length of the communication signal transmission delay, and then calculates the adjustment ratio based on the logistic regression formula according to the added value of the vehicle specificity scores in the current range and the area utilization rate in the current range, and uses the product of the base station signal coverage radius obtained by the free space path loss model and the adjustment ratio as the adjustment range value to adjust the current vehicle monitoring range, thereby improving the overall monitoring accuracy and efficiency and reducing resource waste and communication delays.

[0042] 2. The present invention obtains the adjusted vehicle monitoring range and its adjustment range value, compares the adjustment range value with the adjustment threshold, determines the necessity of the adjustment range, analyzes vehicles with significant temperature differences within the adjustment range value marked as necessary adjustment, obtains the heat value of heat sources emitted around the vehicle and the vehicle refrigeration attenuation efficiency, and substitutes them into fuzzy logic to determine the adjustment range plan, thereby improving resource utilization, setting different adjustment rules to limit the adjustment of the vehicle monitoring range, and improving monitoring accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of the functions of the intelligent logistics vehicle monitoring system based on GPS positioning of the present invention.

[0044] Figure 2 This is a module schematic diagram of the intelligent logistics vehicle monitoring system based on GPS positioning of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] The present disclosure is based on the adjustment of the vehicle monitoring range, the number of vehicles in the collection area and the total length of the communication signal transmission delay are weighted to obtain the determined adjustment coefficient, the threshold is used to evaluate whether the current vehicle monitoring range is adjusted, and then the adjustment ratio is calculated by a logistic regression formula based on the sum of the vehicle specificity scores in the current range and the area utilization rate in the current range, and the product of the output result obtained by the free space path loss model and the adjustment ratio is used as the adjustment range value; different adjustment rules are determined according to the adjusted vehicle monitoring range and its adjustment range value;

[0047] Example 1

[0048] The present invention discloses a wireless security system based on the Internet of Things, such as Figure 1-Figure 2 As shown, it includes an adjustment evaluation module, a collection adjustment module, an adjustment analysis module and a supplementary rule module; and the modules are connected by signals;

[0049] The adjustment and evaluation module is used to collect the number of vehicles in the area and the total length of the communication signal transmission delay, and establish a data analysis model to obtain the determined adjustment coefficient and compare it with the determined threshold, obtain the marking result of the current vehicle monitoring range, and send it to the collection and adjustment module;

[0050] The number of regional vehicles refers to the vehicles being monitored in the intelligent logistics vehicle monitoring system within the current vehicle monitoring range. Specifically, each vehicle is equipped with a GPS and regularly sends location information to the monitoring system. The acquisition logic is to obtain the real-time geographic coordinates of each vehicle, compare the coordinates of all vehicles with the coordinates of the monitoring center through the coordinate judgment formula, screen out the vehicles that fall within the monitoring boundary, and obtain the number of regional vehicles;

[0051] Specifically, the coordinate judgment formula is:

[0052] ;

[0053] In the formula, is the distance between the vehicle and the monitoring center, are the vehicle coordinates, is the monitoring center coordinate, if If it is less than or equal to the monitoring range radius, the vehicle is considered to be within the current monitoring range, and the number of vehicles in the area is counted;

[0054] It should be noted that the real-time geographic coordinates refer to the specific coordinate information of the latitude and longitude or geographic location of the current logistics vehicle, which is obtained by the experimenter based on GPS and is not limited here;

[0055] It should be noted that the monitoring center refers to the core management platform of the logistics vehicle monitoring system, which is responsible for receiving, processing, storing and displaying the real-time data of each logistics vehicle. Specifically, the monitoring center is the command and dispatch hub of the entire system, usually including data servers, monitoring software, display screens, alarm systems and other hardware and software facilities, which will not be elaborated here;

[0056] The total length of communication signal transmission delay refers to the time difference between signal sending and receiving during the data transmission between the regional logistics total vehicle and the monitoring center. Its acquisition logic is to record the sending timestamp when the vehicle sends and the receiving timestamp of the monitoring center respectively, and subtract the sending time of each vehicle from the receiving time of the monitoring center to add up the total length of communication signal transmission delay;

[0057] It should be noted that the experimenters can understand that the sending timestamp is the data sending time automatically generated and attached by the communication module on each logistics vehicle when sending a data packet (such as positioning information or status update), and the receiving timestamp is the data arrival time mark automatically generated and recorded by the monitoring center when receiving the data packet sent by the vehicle. The specific settings of the sending timestamp and the receiving timestamp are not limited and will not be elaborated here;

[0058] A weighted calculation is established between the number of vehicles in the area and the total length of the communication signal transmission delay to obtain a determined adjustment coefficient;

[0059] Compare and analyze the determined adjustment coefficient with the determined adjustment threshold. If it is greater than or equal to the determined adjustment threshold, the current vehicle monitoring range is marked as requiring adjustment. Otherwise, if it is less than the determined adjustment threshold, the current vehicle monitoring range is marked as not requiring adjustment and returns to the beginning.

[0060] Among them, returning to the beginning means returning to the module where the system starts calculating and waiting for the next round of calculation. Specifically, the collection interval of the number of vehicles in the area and the total length of the communication signal transmission delay can be real-time or have different time intervals. It can be understood that the collection interval is obtained by the experimenter based on historical data and historical monitoring accuracy, and is not limited here;

[0061] It should be noted that the adjustment threshold is determined by combining the historical adjustment interval and the historically determined adjustment coefficient, which will not be elaborated here;

[0062] Send the marking result of the current vehicle monitoring range to the acquisition adjustment module;

[0063] The collection and adjustment module is used to receive the marking results of the current vehicle monitoring range, and based on the marking results of the current vehicle monitoring range, collect the added value of the vehicle specificity scores and the area utilization rate within the current range, substitute them into the logistic regression formula to calculate the adjustment ratio, and send it to the adjustment analysis module;

[0064] The marking results of the vehicle monitoring range are respectively required to be adjusted and not required to be adjusted. If the marking result is not required to be adjusted, the preset information in the current range will not be collected. If the marking result is required to be adjusted, the preset information in the current range will be collected.

[0065] The sum of the vehicle specificity scores in the current range refers to a comprehensive indicator obtained through quantitative analysis based on the number of sensors of each vehicle, the temperature difference of the transported goods, and the relative speed difference between the current vehicle and the surrounding vehicles. It is used to evaluate the vehicle specificity. The acquisition logic is to obtain the number of functional sensors installed on the vehicle, the absolute difference between the current temperature of the goods and the outside temperature, and the absolute difference between the average speed of the current vehicle and the surrounding vehicles, and perform weighted average calculation to obtain the specificity scores of each vehicle in the current range, and then perform addition calculation to obtain the sum of the vehicle specificity scores in the current range z;

[0066] Among them, the functional sensors installed on the vehicle include but are not limited to GPS modules, temperature and humidity sensors, collision detection sensors, etc., and the number of functional sensors installed on the vehicle is obtained by statistical calculation;

[0067] The absolute difference between the current temperature of the cargo and the outside temperature is calculated by subtracting the absolute difference between the current temperature of the cargo obtained by the temperature and humidity sensor installed in the cargo loading environment and the outside temperature obtained by the temperature and humidity sensor installed on the vehicle surface;

[0068] The absolute difference of the average speed of surrounding vehicles is obtained by using the speed sensor to obtain the current vehicle speed, and then subtracting it from the average speed of surrounding vehicles.

[0069] It should be noted that the range limitation of surrounding vehicles was obtained by the experimenter based on the historical vehicle status and the narrowing of the historical vehicle monitoring range, which will not be elaborated here;

[0070] The logic for obtaining the area utilization rate within the current range is to calculate the area utilization rate s within the current range by comparing the area actually occupied by the monitored vehicles within the current monitoring range with the area of ​​the current monitoring range;

[0071] It should be noted that the vehicles actually monitored within the current monitoring range are the floor space of all vehicles within the range monitored by the intelligent logistics vehicle monitoring system. Specifically, the floor space refers to the vehicle area displayed by the size model of the vehicle when it leaves the factory, which will not be elaborated here;

[0072] The area utilization rate within the current range refers to the proportion of monitored vehicles within the current monitoring range. The higher the area utilization rate within the current range, the smaller the monitoring range should be. On the contrary, the lower the area utilization rate within the current range, the larger the monitoring range should be to ensure stable monitoring efficiency.

[0073] Substitute the sum of the vehicle specificity scores within the current range and the area utilization rate within the current range into the logistic regression formula to calculate the adjustment ratio. The specific formula is as follows:

[0074] ;

[0075] In the formula, L is the result of logistic regression calculation, e is the natural base, and y is the linear combination term of the logistic regression model. Specifically, y can be set as:

[0076] ;

[0077] In the formula, is the bias term, is the regression coefficient of the sum of the vehicle specificity scores within the current range, is the regression coefficient of regional utilization within the current range;

[0078] The logistic regression calculation results are recorded as adjustment ratios and sent to the adjustment analysis module;

[0079] The adjustment analysis module is used to receive the adjustment ratio, and use the product of the output result obtained by the free space path loss model and the adjustment ratio as the adjustment range value, and adjust the current vehicle monitoring range according to the adjustment range value, and send the adjusted vehicle monitoring range and its adjustment range value to the supplementary rule module;

[0080] The coverage range of the communication base station determines the real-time monitoring capability of the vehicle in a specific area. The size of the coverage range depends on the antenna height, transmission power, communication frequency and propagation environment of the base station. The base station signal coverage radius is obtained through the free space path loss model.

[0081] Specifically, the free space path loss model is a theoretical model used to describe the attenuation of signal strength as the propagation distance increases when the radio signal propagates in free space. The specific calculation formula for obtaining the base station signal coverage radius is as follows:

[0082] ;

[0083] In the formula, R is the base station signal coverage radius, c is the speed of light, and f is the signal frequency. is the base station transmission frequency, is the receiving sensitivity, L is the allowed path loss;

[0084] The base station signal coverage radius is taken as the output result of the free space path loss model, and is multiplied by the adjustment ratio to obtain the adjustment range value;

[0085] Adjust the current vehicle monitoring range according to the adjustment range value to obtain an adjusted vehicle monitoring range, and send it to the supplementary rule module;

[0086] The present invention determines whether the current vehicle monitoring range should be adjusted by collecting the number of vehicles in the area and the total length of the communication signal transmission delay, and then calculates the adjustment ratio according to the logistic regression formula based on the added value of the vehicle specificity scores in the current range and the area utilization rate in the current range, and takes the product of the base station signal coverage radius obtained by the free space path loss model and the adjustment ratio as the adjustment range value, adjusts the current vehicle monitoring range, improves the overall monitoring accuracy and efficiency, and reduces resource waste and communication delay.

[0087] Example 2

[0088] In Example 1 of the present invention, an example is given to determine whether the current vehicle monitoring range is adjusted by collecting the number of vehicles in the area and the total length of the communication signal transmission delay, and then the adjustment ratio is calculated by a logistic regression formula based on the sum of the vehicle specificity scores in the current range and the area utilization rate in the current range, and the product of the base station signal coverage radius obtained by the free space path loss model and the adjustment ratio is used as the adjustment range value to adjust the current vehicle monitoring range. The operation strategy; however, in Example 1, only the adjustment range value is used as the starting point, and the adjustment accuracy and the adjustment rules of the subsequent system are not analyzed in detail. Obviously, although the vehicle monitoring range can be adjusted according to the adjustment range value, the adjustment rules are not divided in detail, and real-time adjustment is likely to lead to waste of resources; in view of the above problems, Example 2 of the present invention is further refined;

[0089] The supplementary rule module is used to obtain the adjusted vehicle monitoring range and its adjustment range value, compare the adjustment range value with the adjustment threshold, determine the necessity of the adjustment range, analyze the vehicles with significant temperature differences within the adjustment range value marked as necessary adjustment, obtain the heat value of the heat source emission around the vehicle and the vehicle refrigeration attenuation efficiency, and substitute the fuzzy logic to determine the re-adjustment range plan;

[0090] Get the adjustment range value and compare it with the preset adjustment threshold value. Specifically:

[0091] If the adjustment range value is greater than or equal to the adjustment threshold, the adjustment range value is marked as necessary adjustment;

[0092] If the adjustment range value is less than the adjustment threshold, the adjustment range is marked as unnecessary adjustment;

[0093] The adjustment range values ​​marked as non-essential adjustment results are screened out of the adjustment rules and are not used as reference ranges for historical adjustment ranges;

[0094] It should be noted that the adjustment threshold is obtained by the fluctuation frequency of the historical adjustment range value, which will not be described in detail here;

[0095] Specifically, the experimenter can also set different screening adjustment rules according to the adjustment range value marked as unnecessary adjustment results to reduce the pressure of real-time calculation of the system and reduce the waste of computing resources. The operation based on the adjustment range value marked as unnecessary adjustment results is not limited, but is set by those skilled in the art according to the specific historical adjustment range value and the adjustment rules of historical unnecessary adjustment results, which is not limited here;

[0096] Collect the adjustment range values ​​marked as necessary adjustment results, generate necessary adjustment rules, and analyze vehicles with significant temperature differences within the range. Specifically, the temperature difference is calculated by subtracting the internal temperature of the cargo box obtained by a temperature sensor installed inside the cargo box of the vehicle from the external temperature obtained by a temperature sensor installed outside the cargo box;

[0097] It should be noted that the experimenter can also set different necessary adjustment rules according to the adjustment range value marked as the necessary adjustment result, for example, the adjustment range value of the necessary adjustment result is used as the reference range of the historical adjustment range value, etc., to ensure the scientificity, pertinence and efficiency of the monitoring range adjustment;

[0098] The temperature difference is compared with a preset temperature threshold, and vehicles with a temperature greater than or equal to the temperature threshold are marked as vehicles with significant temperature difference, otherwise no mark is made;

[0099] It should be noted that the temperature threshold is set based on the storage and transportation conditions of fresh food and medicine, so it will not be elaborated here;

[0100] Collect corresponding information of vehicles marked as having significant temperature differences, including the heat value of heat sources emitted by the vehicle and the vehicle refrigeration attenuation efficiency;

[0101] The logic for obtaining the heat value of heat sources emitted by the vehicle is to install heat source sensing equipment around the vehicle, collect the heat radiation data around the vehicle, and calculate the effective heat conduction with the vehicle surface to obtain the heat value of heat sources emitted by the vehicle.

[0102] Specifically, the solar radiation heat received by the vehicle is calculated by the sunlight intensity and ambient temperature, as well as the vehicle surface area and color reflectivity. The specific formula is as follows:

[0103] ;

[0104] In the formula, The heat from solar radiation, is the solar radiation intensity, is the vehicle surface area, is the vehicle surface reflectivity;

[0105] The radiated heat is calculated by the heat emission power of the surrounding heat source and the distance from the vehicle. The specific formula is as follows:

[0106] ;

[0107] In the formula, is the radiant heat of the i-th heat source to the vehicle, where i is the i-th heat source, is the heat source emission power, is the distance between the heat source and the vehicle;

[0108] Add the solar radiation heat and the radiation heat of all heat sources to the vehicle to obtain the heat value emitted by the heat sources around the vehicle;

[0109] It should be noted that the evaluation of the surrounding heat source range is a range set by the experimenter based on the specific heat source distance and heat source amount, and is not limited here;

[0110] The logic for obtaining the vehicle refrigeration attenuation efficiency is to record the refrigeration capacity of the equipment under standard environmental conditions as the benchmark refrigeration efficiency, then monitor the temperature change rate in the cargo box, calculate the actual refrigeration efficiency, subtract the benchmark refrigeration efficiency from the actual refrigeration efficiency, and calculate the ratio with the benchmark refrigeration efficiency to obtain the vehicle refrigeration attenuation efficiency;

[0111] Specifically, the benchmark refrigeration efficiency is determined by obtaining the design parameters of the refrigeration equipment, including refrigeration power, target temperature maintenance capability, and ambient temperature adaptability range, under standard ambient conditions. The actual refrigeration efficiency is obtained by a temperature sensor installed inside the vehicle cargo box, which will not be described in detail here.

[0112] Substitute the heat value of the heat source around the vehicle and the vehicle refrigeration attenuation efficiency into the fuzzy logic to determine the adjustment range plan, specifically:

[0113] For example, "High", "Low", "Medium" for the heat emission value of the heat source around the vehicle, and "Excellent", "Inefficient", "Moderate" for the vehicle refrigeration attenuation efficiency;

[0114] Formulate a set of fuzzy rules to describe the impact of different input variables on output variables. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0115] The heat value of the heat source emitted from the vehicle surrounding is marked as X, the vehicle refrigeration attenuation efficiency is marked as U, and the readjustment range result is marked as C_results;

[0116] Then we can define:

[0117] Rule 1: IF (X is High) AND (U is Excellent) THEN (C_results is High)

[0118] Rule 2: IF (U is Low) AND (U is Inefficient) THEN (C_results is Low) ...

[0119] Perform fuzzy reasoning based on fuzzy rules to determine the readjustment range plan;

[0120] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although this embodiment takes three fuzzy sets as an example, it can actually be divided into more than three sets to facilitate better precise adjustment according to different situations.

[0121] Furthermore, for the determination of the heat value of the heat source emitted from the vehicle and the high, medium and low refrigeration attenuation efficiency of the vehicle, thresholds can be set according to the actual situation for determination. For example, when the heat value of the heat source emitted from the vehicle exceeds 62%, it is marked as "High", and when the refrigeration attenuation efficiency of the vehicle is higher than 51%, it is marked as "Excellent", etc., which will not be elaborated here;

[0122] The present invention obtains the adjusted vehicle monitoring range and its adjustment range value, compares the adjustment range value with the adjustment threshold, determines the necessity of the adjustment range, analyzes vehicles with significant temperature differences within the adjustment range value marked as necessary adjustment, obtains the heat value of heat sources emitted around the vehicle and the vehicle refrigeration attenuation efficiency, and substitutes them into fuzzy logic to determine the adjustment range plan, thereby improving resource utilization, setting different adjustment rules to limit the adjustment of the vehicle monitoring range, and improving monitoring accuracy.

[0123] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0124] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0125] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0126] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0128] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, 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.

[0129] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0130] 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.

[0131] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0132] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Intelligent logistics vehicle monitoring system based on GPS positioning, characterized by: It includes adjustment evaluation module, acquisition adjustment module, adjustment analysis module and supplementary rule module; signal connection between each module; The adjustment and evaluation module is used to collect the number of vehicles in the area and the total length of the communication signal transmission delay, and establish a data analysis model to obtain the determined adjustment coefficient and compare it with the determined threshold, obtain the marking result of the current vehicle monitoring range, and send it to the collection and adjustment module; The collection and adjustment module is used to receive the marking results of the current vehicle monitoring range, and based on the marking results of the current vehicle monitoring range, collect the added value of the vehicle specificity scores and the area utilization rate within the current range, substitute them into the logistic regression formula to calculate the adjustment ratio, and send it to the adjustment analysis module; The specificity score of each vehicle in the current range is obtained by obtaining the number of functional sensors installed on the vehicle, the absolute difference between the current temperature of the cargo and the outside temperature, and the absolute difference between the average speed of the current vehicle and the surrounding vehicles, and performing weighted average calculation; The adjustment analysis module is used to receive the adjustment ratio, and use the product of the output result obtained by the free space path loss model and the adjustment ratio as the adjustment range value, and adjust the current vehicle monitoring range according to the adjustment range value, and send the adjusted vehicle monitoring range and its adjustment range value to the supplementary rule module; The supplementary rule module is used to obtain the adjusted vehicle monitoring range and its adjustment range value, compare the adjustment range value with the adjustment threshold, determine the necessity of the adjustment range, and if the adjustment range value is greater than or equal to the adjustment threshold, mark the adjustment range value as necessary adjustment; analyze the vehicles with significant temperature differences within the adjustment range marked as necessary adjustment and obtain the heat value of the heat source emitted by the vehicle and the vehicle refrigeration attenuation efficiency, and substitute the fuzzy logic to determine the re-adjustment range plan; Get the real-time geographic coordinates of each vehicle, compare the coordinates of all vehicles with the coordinates of the monitoring center through the coordinate judgment formula, filter out the vehicles that fall within the monitoring boundary, and get the number of vehicles in the area; By recording the sending timestamp of the vehicle and the receiving timestamp of the monitoring center, and subtracting the sending time of each vehicle from the receiving time of the monitoring center, the total delay length of the communication signal transmission is obtained. A weighted calculation is established between the number of vehicles in the area and the total length of the communication signal transmission delay to obtain a determined adjustment coefficient; The determined adjustment coefficient is compared and analyzed with the determined threshold. If it is greater than or equal to the determined adjustment threshold, the current vehicle monitoring range is marked as requiring adjustment.

2. According to claim 1, the intelligent logistics vehicle monitoring system based on GPS positioning is characterized in that: Then perform addition calculation to obtain the added value z of the vehicle specificity scores within the current range; The area utilization rate s within the current monitoring range is calculated by calculating the ratio of the area actually occupied by the monitored vehicles within the current monitoring range to the area of ​​the current monitoring range; Substitute the sum of the vehicle specificity scores within the current range and the area utilization rate within the current range into the logistic regression formula to calculate the adjustment ratio. The specific formula is as follows: ； In the formula, L is the result of logistic regression calculation, e is the natural base, and y is the linear combination term of the logistic regression model. The specific setting of y is: ； In the formula, is the bias term, is the regression coefficient of the sum of the vehicle specificity scores within the current range, is the regression coefficient of regional utilization within the current range.

3. The intelligent logistics vehicle monitoring system based on GPS positioning according to claim 2 is characterized by: The output of the free space path loss model is the base station signal coverage radius, which is expressed as follows: ； In the formula, R is the base station signal coverage radius, c is the speed of light, and f is the signal frequency. is the base station transmission frequency, is the receiving sensitivity, and L is the allowed path loss.

4. The intelligent logistics vehicle monitoring system based on GPS positioning according to claim 3 is characterized by: The base station signal coverage radius is taken as the output result of the free space path loss model, and is multiplied by the adjustment ratio to obtain the adjustment range value; The current vehicle monitoring range is adjusted according to the adjustment range value to obtain an adjusted vehicle monitoring range.

5. According to claim 4, the intelligent logistics vehicle monitoring system based on GPS positioning is characterized in that: Get the adjustment range value and compare it with the preset adjustment threshold value. Specifically: If the adjustment range value is less than the adjustment threshold, the adjustment range is marked as unnecessary adjustment; Filter out the adjustment range values ​​marked as unnecessary adjustment results; Collect adjustment range values ​​marked as necessary adjustment results and analyze vehicles with significant temperature differences within the range.

6. The intelligent logistics vehicle monitoring system based on GPS positioning according to claim 5 is characterized by: The temperature difference is calculated by subtracting the internal temperature of the cargo box collected by the temperature sensor installed inside the vehicle cargo box from the external temperature collected by the temperature sensor installed outside the cargo box, and then compared with the preset temperature threshold. Vehicles with a temperature greater than or equal to the threshold will be marked as vehicles with significant temperature differences.

7. The intelligent logistics vehicle monitoring system based on GPS positioning according to claim 6 is characterized by: By installing heat source sensing equipment around the vehicle, the heat radiation data around the vehicle is collected, and the effective heat conduction with the vehicle surface is calculated to obtain the heat value emitted by the heat source around the vehicle; The vehicle refrigeration attenuation efficiency is obtained by recording the refrigeration capacity of the equipment under standard environmental conditions as the benchmark refrigeration efficiency, monitoring the temperature change rate in the cargo box, calculating the actual refrigeration efficiency, subtracting the benchmark refrigeration efficiency from the actual refrigeration efficiency, and calculating the ratio with the benchmark refrigeration efficiency.

8. The intelligent logistics vehicle monitoring system based on GPS positioning according to claim 7 is characterized by: The heat value of heat sources around the vehicle and the vehicle refrigeration attenuation efficiency are defined as input variables and divided into different fuzzy sets respectively; Define the readjustment range result as the output variable and divide it into fuzzy sets; Formulate fuzzy rules to describe the impact of the heat value of heat sources emitted around the vehicle and the vehicle refrigeration decay efficiency on the readjustment range results; Perform fuzzy reasoning based on fuzzy rules and determine the readjustment range plan.

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