Dotting record optimization method and device and electronic equipment

Abstract

The invention relates to a dotting record optimization method and device and electronic equipment, and relates to the technical field of data processing, and the method comprises the steps: obtaining the real-time position information of mobile equipment according to a preset access time interval and a preset continuous access frequency; determining the driving state of the mobile equipment according to the real-time position information; and adjusting the preset access time interval and the preset number of continuous access times based on the driving state of the mobile equipment. According to the embodiment of the invention, the preset access time interval and the preset number of continuous access times are adjusted based on the driving state of the mobile equipment, so that the position of the logistics transportation vehicle can be accurately positioned in a complex terrain such as an overpass group.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a dot record optimization method, device and electronic equipment. Background Art

[0002] With the rapid development of modern logistics industry, the monitoring and management of transport vehicles in the process of logistics transportation is particularly important. The traditional logistics transportation monitoring and management system mainly records the logistics transportation vehicles at fixed time intervals and fixed number of times. This method cannot accurately locate the location of logistics transportation vehicles in complex terrain such as overpasses. Summary of the invention

[0003] In view of this, the present application provides a method, device and electronic device for optimizing point recording, the main purpose of which is to solve the technical problem that the current traditional logistics and transportation monitoring and management system mainly records the points of logistics and transportation vehicles according to fixed time intervals and fixed number of points, and this method cannot accurately locate the location of logistics and transportation vehicles in complex terrains such as overpasses.

[0004] According to a first aspect of the present disclosure, a dot record optimization method is provided, the method comprising:

[0005] Acquire the real-time location information of the mobile device according to the preset data acquisition time interval and the preset number of continuous data acquisitions;

[0006] Determining the driving status of the mobile device according to the real-time location information;

[0007] The preset data acquisition time interval and the preset number of consecutive data acquisition times are adjusted based on the driving state of the mobile device.

[0008] According to a second aspect of the present disclosure, a dot record optimization device is provided, the device comprising:

[0009] An acquisition module, used to acquire real-time location information of a mobile device according to a preset data acquisition time interval and a preset number of continuous data acquisitions;

[0010] A determination module, used to determine the driving state of the mobile device according to the real-time location information;

[0011] The adjustment module is used to adjust the preset data acquisition time interval and the preset number of consecutive data acquisition times based on the driving state of the mobile device.

[0012] According to the third aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method of the aforementioned first aspect.

[0013] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable a computer to execute the method of the aforementioned first aspect.

[0014] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program implements the method of the aforementioned first aspect when executed by a processor.

[0015] Compared with the prior art, the dot record optimization method, device and electronic device provided by the present disclosure obtain the real-time location information of the mobile device according to the preset data acquisition time interval and the preset continuous data acquisition number; determine the driving state of the mobile device according to the real-time location information; and adjust the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device. For the embodiment of the present disclosure, by adjusting the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device, the location of the logistics transportation vehicle can be accurately located in complex terrain such as a group of overpasses.

[0016] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical application in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 A flowchart of a dot record optimization method provided by an embodiment of the present disclosure;

[0020] Figure 2A flowchart of a dot record optimization system provided by an embodiment of the present disclosure;

[0021] Figure 3 A flowchart of a dot record optimization method provided by an embodiment of the present disclosure;

[0022] Figure 4 A schematic diagram of the structure of a dot record optimization device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0023] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description. It should be noted that, in the absence of conflict, the embodiments of the present disclosure and the features in the embodiments may be combined with each other.

[0024] The dot record optimization method, device and electronic device of the embodiments of the present disclosure are described below with reference to the accompanying drawings.

[0025] The present disclosure provides a method, device and electronic device for optimizing point recording, the main purpose of which is to solve the technical problem that the current traditional logistics and transportation monitoring and management system mainly records the points of logistics and transportation vehicles according to fixed time intervals and fixed number of points, and this method cannot accurately locate the location of logistics and transportation vehicles in complex terrains such as overpasses.

[0026] like Figure 1 As shown, an embodiment of the present disclosure provides a method for optimizing dot recording, wherein the method may include:

[0027] Step 101: Acquire real-time location information of a mobile device according to a preset data acquisition time interval and a preset number of consecutive data acquisition times.

[0028] Among them, mobile devices may include vehicles, smart phones, tablets, wearable devices, portable computers, drones, robots and other movable devices with positioning technology.

[0029] The real-time location information may be the latitude and longitude coordinate information of the real-time location of the mobile device determined by satellite positioning technology or the like.

[0030] Specifically, the real-time location information of the interval time point can be obtained from the mobile device (such as a transport vehicle) regularly through the GPS receiving unit according to the pre-configured data acquisition time interval and the number of continuous data acquisitions in the model parameters of the preset recording model, that is:

[0031] p1(x1,y1,z1),p2(x2,y2,z2)...pn(xn,yn,zn)

[0032] Wherein, pn may represent the position information obtained for the nth time, and xn, yn, and zn may represent the coordinate values ​​of the position in the longitude, latitude, and height (or altitude) directions, respectively. Figure 2 shown.

[0033] In specific application scenarios, there are three main factors that affect the preset recording model, namely environmental factors, vehicle factors, and model configuration information factors.

[0034] Environmental factors mainly involve geographical and climatic conditions, such as topography, road conditions, water systems, climate and soil. Different environmental conditions have a certain impact on the construction, use and safety of transportation. For example, complex mountainous terrain increases the difficulty of transportation; rising water levels in the rainy season threaten the safety of transportation. These factors need to be fully considered and incorporated when constructing and using preset record models.

[0035] Vehicle factors are mainly divided into vehicle condition factors and vehicle driver factors. Vehicle condition factors may include the conditions of multiple systems such as the engine, chassis, body and electronic equipment, as well as specific details such as tire wear, brake pad replacement time, battery condition, oil level and replacement time; vehicle driver factors may mainly include their driving status, driving age, driving experience, etc. These factors directly affect the performance of the vehicle during operation, and thus affect the recording of position change information.

[0036] Model configuration information factors can be model data parameters pre-configured by enterprise administrators according to material transportation management requirements, which may include distance change threshold, height threshold, normal speed value, data acquisition time interval, number of consecutive data acquisitions, etc. These parameters form the rules for intelligent recording of location changes and affect the final recorded location information change data.

[0037] Step 102: Determine the driving status of the mobile device according to the real-time location information.

[0038] For the embodiment of the present disclosure, as a possible implementation method, the position change value between the current position and the previous position of the mobile device can be determined based on the real-time position information of the mobile device, and the position change value can be compared with a preset position change threshold to determine the driving state of the mobile device. The driving state may include normal driving state, acceleration state, deceleration state, parking state, uphill state, downhill state, interchange maze state, and interchange bridge group state.

[0039] Step 103: adjusting the preset data acquisition time interval and the preset number of consecutive data acquisition times based on the driving state of the mobile device.

[0040] For the embodiments of the present disclosure, the driving status of the mobile device can be continuously analyzed to adjust the pre-configured data acquisition time interval and the number of continuous data acquisitions in the model parameters of the preset recording model based on the driving status of the mobile device, so that the location of the mobile device can be accurately located under different driving conditions.

[0041] For example, if the driving state of the mobile device is a driving state in a complex terrain such as an interchange maze or a group of interchange bridges, the AI ​​intelligent adjustment unit can be used to shorten the data acquisition time interval and increase the number of continuous data acquisitions, thereby increasing the accuracy and reliability of the positioning of the mobile device by increasing the amount of data;

[0042] If the driving state of the mobile device is normal, the adjusted data acquisition time interval and the number of consecutive data acquisitions can be automatically restored to the original preset data acquisition time interval and the preset number of consecutive data acquisitions to prevent wasting computing resources.

[0043] In summary, compared with the prior art, the dot record optimization method provided by the present disclosure obtains the real-time location information of the mobile device according to the preset data acquisition time interval and the preset continuous data acquisition number; determines the driving state of the mobile device according to the real-time location information; and adjusts the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device. For the embodiment of the present disclosure, by adjusting the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device, the location of the logistics transportation vehicle can be accurately located in complex terrain such as a group of overpasses.

[0044] Further, as a refinement and expansion of the above embodiment, in order to fully illustrate the specific implementation process of the disclosed method, the present disclosure provides the following Figure 3 The specific method shown includes:

[0045] Step 201: Determine a location change value between a current location and a previous location of a mobile device according to real-time location information.

[0046] The position change value may include a distance change value and a height change value.

[0047] For the embodiments of the present disclosure, Figure 2 As shown, the position calculation unit can be used to calculate the position change value between the current position and the last position of the mobile device. Specifically, the first longitude coordinate value and the first latitude coordinate value of the current position of the mobile device, and the second longitude coordinate value and the second latitude coordinate value of the last position of the mobile device can be substituted into the preset distance change value calculation formula to determine the distance change value between the current position and the last position of the mobile device.

[0048] The calculation formula for the preset distance change value is as follows:

[0049]

[0050] In the formula, S_i may represent the distance change value, x1 may represent the first longitude coordinate value, x2 may represent the second longitude coordinate value, y1 may represent the first latitude coordinate value, and y2 may represent the second latitude coordinate value.

[0051] For the embodiment of the present disclosure, the first height coordinate value of the current position of the mobile device and the second height coordinate value of the previous position of the mobile device may be substituted into a preset height change value calculation formula to determine the height change value between the current position and the previous position of the mobile device, wherein the preset height change value calculation formula is as follows:

[0052] H_i=|z 1-z 2|

[0053] Wherein, H_i may represent a height change value, z1 may represent a first height coordinate value, and z2 may represent a second height coordinate value.

[0054] Step 202: Determine the temporary driving state of the mobile device according to the position change value and a preset position change threshold.

[0055] The preset position change threshold may include a preset distance change threshold and a preset height change threshold.

[0056] For the embodiments of the present disclosure, the normal distance value and the normal height value between the current position and the previous position of the mobile device can be calculated first, and the temporary driving state of the mobile device can be determined according to the distance change value, the normal distance value, the preset distance change threshold, the height change value, the normal height value and / or the preset height change threshold.

[0057] For the embodiment of the present disclosure, as a possible implementation method, the normal distance value between the current position and the previous position of the mobile device may be calculated according to a preset normal distance value calculation formula, wherein the preset normal distance value calculation formula is as follows:

[0058] S_a=V×T

[0059] Wherein, S_a may represent the normal distance value, V may represent the normal driving speed, and T may represent the time interval between the current position and the previous position.

[0060] For the embodiment of the present disclosure, as a possible implementation method, the normal height value between the current position and the previous position of the mobile device may be calculated according to a preset normal height value calculation formula, wherein the preset normal height value calculation formula is as follows:

[0061] S_z=V_z×T

[0062] Wherein, S_z may represent the normal height value, V_z may represent the normal vertical moving speed, and T may represent the time interval between the current position and the previous position.

[0063] For the disclosed embodiment, the distance change value can be compared with the normal distance value and the preset distance change threshold of the model configuration. According to the comparison result, the temporary driving state of the vehicle (such as parking, acceleration, deceleration, etc.) can be determined and the distance change factor S_x can be calculated.

[0064] Specifically, if the distance change value is 0, the temporary driving state of the mobile device is determined and saved as a parked state, and the distance change factor is 0;

[0065] If the distance change value is greater than the normal distance value, and the difference between the distance change value and the normal distance value is greater than the preset distance change threshold, the temporary driving state of the mobile device is determined and saved as the acceleration state, and the distance change factor S_x=S_i-S_a-S, where S_i can represent the distance change value, S_a can represent the normal distance value, and S can represent the preset distance change threshold;

[0066] If the distance change value is smaller than the normal distance value, and the difference between the normal distance value and the distance change value is greater than the preset distance change threshold, it is determined that the temporary driving state of the mobile device is a deceleration state, and the distance change factor S_x=S_a-S_i-S.

[0067] For the disclosed embodiment, the height change value can be compared with the normal height value and the preset height change threshold of the model configuration. Based on the comparison result, the temporary driving state of the vehicle (such as uphill, downhill, etc.) can be determined and the height change factor H_x can be calculated.

[0068] Specifically, if the height change value is greater than the normal height value, and the difference between the height change value and the normal height value is greater than the preset height change threshold, the temporary driving state of the mobile device is determined and saved as an uphill state, and the height change factor H_x=H_i-H_a-H, where H_a can represent the normal height value, H_i can represent the height change value, and H can represent the preset height change threshold;

[0069] If the height change value is less than the normal height value, and the difference between the normal height value and the height change value is greater than the preset height change threshold, the temporary driving state of the mobile device is determined and saved as a downhill state, and the height change factor H_x=H_a-H_i-H.

[0070] After completing the above calculation, the current calculation process ends and the next round of GPS receiving unit process can be entered to reacquire new position information (such as p3) and repeat the calculation between points P3 and P2 to continuously monitor and record the vehicle's driving status and position changes.

[0071] For the embodiment of the present disclosure, the trigger recording unit can be used to continuously obtain N times according to the model configuration parameters, and obtain the position information Pn, Pn-1, Pn-2, ... P1 recorded for the first N, N-1, N-2... times respectively, obtain relevant calculation information and trigger the calculation process of the AI ​​intelligent adjustment unit.

[0072] The AI ​​intelligent adjustment unit can be used to calculate and record position change information based on the calculation information recorded by the trigger recording unit and combined with the model configuration parameters, which may include position coordinates, time, distance change value, height change value, current vehicle speed, driving status, etc., for statistical analysis and display.

[0073] When the record triggering condition is not met, the current calculation process ends, the value of the current position information can be saved to the previous position information, and the next round of calculation is entered to obtain new position information.

[0074] Step 203: Determine the driving state of the mobile device based on the temporary driving state.

[0075] For the embodiments of the present disclosure, as a possible implementation method, the straight-line distance value, normal straight-line distance value, vector cosine value between the current position and the previous position of the mobile device can be calculated, and the current speed of the current position of the mobile device and the historical speed of the previous position of the mobile device can be calculated, and the driving state of the mobile device can be determined based on the temporary driving state, straight-line distance value, normal straight-line distance value, vector cosine value, current speed and / or historical speed.

[0076] Specifically, as a possible implementation method, the straight-line distance value between the current position and the previous position of the mobile device may be calculated according to a preset straight-line distance value calculation formula, wherein the preset straight-line distance value calculation formula is as follows:

[0077]

[0078] In the formula, S_pn can represent the straight-line distance value, x1 can represent the first longitude coordinate value, x2 can represent the second longitude coordinate value, y1 can represent the first latitude coordinate value, y2 can represent the second latitude coordinate value, z1 can represent the first height coordinate value, and z2 can represent the second height coordinate value.

[0079] As a possible implementation method for the embodiment of the present disclosure, the vector cosine value between the current position and the previous position of the mobile device may be calculated according to a preset vector cosine value calculation formula, wherein the preset vector cosine value calculation formula is as follows:

[0080] cosθ=(a·b) / (|a|·|b|)

[0081] Wherein, cosθ may represent the cosine value of a vector, a may represent the vector from position point P1 to position point P2, and b may represent the vector from position point P1 to position point P3.

[0082] For the embodiment of the present disclosure, as a possible implementation method, the current speed of the current position of the mobile device may be calculated according to a preset current speed calculation formula, wherein the preset current speed calculation formula is as follows:

[0083] V_i=S_i / T

[0084] Wherein, V_i may represent the current speed, S_i may represent the distance change between the current position and the previous position, and T may represent the time interval between the current position and the previous position.

[0085] For the embodiment of the present disclosure, as a possible implementation method, the historical speed of the last position of the mobile device may be calculated according to a preset historical speed calculation formula, wherein the preset historical speed calculation formula is as follows:

[0086] V_i-1=S_i-1 / T

[0087] Wherein, V_i-1 may represent the historical speed of the previous position, S_i-1 may represent the distance change between the previous position and the position before the previous position, and T may represent the time interval between the previous position and the position before the previous position.

[0088] According to the embodiment of the present disclosure, the driving state of the mobile device may be determined according to the temporary driving state, the straight-line distance value, the normal straight-line distance value, the vector cosine value, the current speed and / or the historical speed.

[0089] Specifically, if the straight-line distance value is 0, it is determined that the driving state of the mobile device is a docked state;

[0090] If the temporary driving state is the same for a preset number of consecutive times, the temporary driving state is determined to be the driving state of the mobile device. For example, if the temporary driving state obtained by the threshold comparison unit for N consecutive times is an acceleration state, the driving state of the record point P1 is updated to an acceleration state; if the temporary driving state obtained by the threshold comparison unit for N consecutive times is a deceleration state, the driving state of the record point P1 is updated to a deceleration state; if the temporary driving state obtained by the threshold comparison unit for N consecutive times is an uphill state, the driving state of the record point P1 is updated to an uphill state; if the temporary driving state obtained by the threshold comparison unit for N consecutive times is a downhill state, the driving state of the record point P1 is updated to a downhill state.

[0091] If the temporary driving state is different for a preset number of consecutive times, such as N consecutive times, when the temporary driving state of the threshold comparison unit is both uphill and downhill, and the straight-line distance value is less than or equal to half of the normal straight-line distance value, then the driving state of the mobile device is determined and updated as the flyover maze state, wherein the normal straight-line distance value can be expressed as S_a×N;

[0092] If the temporary driving state is different for a preset number of consecutive times, the straight-line distance value is less than or equal to half of the normal straight-line distance value, and the vector cosine value is greater than the first preset threshold, it is determined that the direction is opposite and reverse driving, and the driving state of the recording point Pn of the mobile device is determined and updated as the overpass group state, wherein the first preset threshold may be 90 degrees;

[0093] In N consecutive cases, if the vector cosine value of the angle P1OP2 calculated according to the cosine formula is less than the second preset threshold, and the speed difference ratio between the current speed and the historical speed is less than the preset speed difference ratio, the driving state of the mobile device is determined and updated to a normal driving state, wherein the second preset threshold may be 15 degrees, and the preset speed difference ratio may be 10%.

[0094] Step 204: adjusting the preset data acquisition time interval and the preset number of consecutive data acquisition times based on the driving status of the mobile device.

[0095] For the embodiments of the present disclosure, the driving status of the mobile device can be continuously analyzed to adjust the pre-configured data acquisition time interval and the number of continuous data acquisitions in the model parameters of the preset recording model based on the driving status of the mobile device, so that the location of the mobile device can be accurately located under different driving conditions.

[0096] Specifically, if the driving state of the mobile device is an acceleration state, a downhill state, an interchange maze state and / or an interchange bridge group state, the AI ​​intelligent adjustment unit can be used to shorten the data acquisition time interval and increase the number of continuous data acquisitions, and the preset data acquisition time interval can be adjusted to the first data acquisition time interval, and the preset continuous data acquisition number can be adjusted to the first continuous data acquisition number;

[0097] If the driving state of the mobile device is a deceleration state and / or an uphill state, the AI ​​intelligent adjustment unit can be used to extend the data acquisition time interval and reduce the number of continuous data acquisitions. Correspondingly, the preset data acquisition time interval can be adjusted to the second data acquisition time interval, and the preset continuous data acquisition number can be adjusted to the second continuous data acquisition number;

[0098] If the driving state of the mobile device is a docked state, the AI ​​intelligent adjustment unit can be used to infinitely extend the data acquisition time interval and infinitely reduce the number of continuous data acquisitions until the driving state of the mobile device changes to another driving state. Accordingly, the preset data acquisition time interval can be adjusted to the third data acquisition time interval, and the preset continuous data acquisition number can be adjusted to the third continuous data acquisition number.

[0099] If the driving state of the mobile device is a normal driving state, the AI ​​intelligent adjustment unit can be used to automatically restore the adjusted data acquisition time interval and the number of continuous data acquisitions to the original preset data acquisition time interval and the preset number of continuous data acquisitions, and the corresponding adjustable data acquisition time interval is the preset data acquisition time interval, and the adjusted continuous data acquisition number is the preset continuous data acquisition number;

[0100] The first data acquisition time interval is smaller than the second data acquisition time interval, the second data acquisition time interval is smaller than the third data acquisition time interval, the first continuous data acquisition number is larger than the second continuous data acquisition number, and the second continuous data acquisition number is larger than the third continuous data acquisition number.

[0101] In summary, compared with the prior art, the dot record optimization method provided by the present disclosure obtains the real-time location information of the mobile device according to the preset data acquisition time interval and the preset continuous data acquisition number; determines the driving state of the mobile device according to the real-time location information; and adjusts the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device. For the embodiment of the present disclosure, by adjusting the preset data acquisition time interval and the preset continuous data acquisition number based on the driving state of the mobile device, the location of the logistics transportation vehicle can be accurately located in complex terrain such as a group of overpasses.

[0102] Based on the above Figure 1 and Figure 3 The specific implementation of the method shown in the embodiment provides a dot record optimization device, such as Figure 4 As shown, the device includes: an acquisition module 31, a determination module 32, and an adjustment module 33;

[0103] The acquisition module 31 is used for the acquisition module, and is used to acquire the real-time location information of the mobile device according to the preset data acquisition time interval and the preset continuous data acquisition times;

[0104] A determination module 32, configured to determine the driving state of the mobile device according to the real-time location information;

[0105] The adjustment module 33 is used to adjust the preset data acquisition time interval and the preset number of consecutive data acquisition times based on the driving state of the mobile device.

[0106] In a specific application scenario, the determination module 32 may be used to determine a position change value between a current position and a previous position of the mobile device according to the real-time position information;

[0107] Determining a temporary driving state of the mobile device according to the position change value and a preset position change threshold;

[0108] A driving state of the mobile device is determined based on the temporary driving state.

[0109] In a specific application scenario, the position change value includes a distance change value and a height change value, and the preset position change threshold includes a preset distance change threshold and a preset height change threshold; the determination module 32 can be used to calculate a normal distance value and a normal height value between the current position and the previous position of the mobile device;

[0110] The temporary driving state of the mobile device is determined according to the distance change value, the normal distance value, the preset distance change threshold, the height change value, the normal height value and / or the preset height change threshold.

[0111] In a specific application scenario, the determination module 32 may be used to determine that the temporary driving state of the mobile device is a docked state if the distance change value is 0;

[0112] If the distance change value is greater than the normal distance value, and the difference between the distance change value and the normal distance value is greater than the preset distance change threshold, determining that the temporary driving state of the mobile device is an acceleration state;

[0113] If the distance change value is less than the normal distance value, and the difference between the normal distance value and the distance change value is greater than the preset distance change threshold, determining that the temporary driving state of the mobile device is a deceleration state;

[0114] If the height change value is greater than the normal height value, and the difference between the height change value and the normal height value is greater than the preset height change threshold, determining that the temporary driving state of the mobile device is an uphill state;

[0115] If the height change value is smaller than the normal height value, and the difference between the normal height value and the height change value is greater than the preset height change threshold, it is determined that the temporary driving state of the mobile device is a downhill state.

[0116] In a specific application scenario, the determination module 32 may be used to calculate a straight-line distance value, a normal straight-line distance value, a vector cosine value between a current position and a previous position of the mobile device, and calculate a current speed of the current position of the mobile device and a historical speed of the previous position of the mobile device;

[0117] The driving state of the mobile device is determined according to the temporary driving state, the straight-line distance value, the normal straight-line distance value, the vector cosine value, the current speed and / or the historical speed.

[0118] In a specific application scenario, the determination module 32 may be used to determine that the driving state of the mobile device is a docked state if the straight-line distance value is 0;

[0119] If the temporary driving state is the same temporary driving state for a preset number of consecutive times, determining that the temporary driving state is the driving state of the mobile device;

[0120] If the temporary driving state is a different temporary driving state for a preset number of consecutive times, and the straight-line distance value is less than or equal to half of the normal straight-line distance value, then the driving state of the mobile device is determined to be an interchange maze state;

[0121] If the temporary driving state is a different temporary driving state for a preset number of consecutive times, the straight-line distance value is less than or equal to half of the normal straight-line distance value, and the vector cosine value is greater than a first preset threshold, then the driving state of the mobile device is determined to be an overpass group state;

[0122] If the vector cosine value is less than a second preset threshold value, and the speed difference ratio between the current speed and the historical speed is less than a preset speed difference ratio, it is determined that the driving state of the mobile device is a normal driving state, wherein the first preset threshold value is greater than the second preset threshold value.

[0123] In a specific application scenario, the adjustment module 33 may be used to adjust the preset data acquisition time interval to the first data acquisition time interval and the preset continuous data acquisition number to the first continuous data acquisition number if the driving state is an acceleration state, a downhill state, an interchange maze state and / or an interchange bridge group state;

[0124] If the driving state is a deceleration state and / or an uphill state, the preset data acquisition time interval is adjusted to a second data acquisition time interval, and the preset number of continuous data acquisitions is adjusted to a second number of continuous data acquisitions;

[0125] If the driving state is a parking state, adjusting the preset data acquisition time interval to a third data acquisition time interval, and adjusting the preset number of consecutive data acquisition times to a third number of consecutive data acquisition times;

[0126] If the driving state is a normal driving state, the data acquisition time interval is adjusted to the preset data acquisition time interval, and the number of continuous data acquisitions is adjusted to the preset number of continuous data acquisitions;

[0127] The first data acquisition time interval is smaller than the second data acquisition time interval, the second data acquisition time interval is smaller than the third data acquisition time interval, the first continuous data acquisition number is larger than the second continuous data acquisition number, and the second continuous data acquisition number is larger than the third continuous data acquisition number.

[0128] It should be noted that for other corresponding descriptions of the functional units involved in the dot record optimization device provided in this embodiment, please refer to Figure 1 and Figure 3 The corresponding description of the method in will not be repeated here.

[0129] Based on the above Figure 1 and Figure 3 The method shown in the present disclosure, accordingly, also provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned Figure 1 and Figure 3 The method shown.

[0130] Based on this understanding, the technical solution of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of various implementation scenarios of the present disclosure.

[0131] Based on the above Figure 1 and Figure 3 The method shown, and Figure 4 In order to achieve the above-mentioned purpose, the embodiment of the present disclosure also provides an electronic device that can be configured on the vehicle (such as an electric vehicle) side, and the device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 and Figure 3 The method shown.

[0132] Optionally, the above-mentioned physical device may also include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), etc.

[0133] Those skilled in the art will appreciate that the above-mentioned physical device structure provided by the present disclosure does not constitute a limitation on the physical device, and may include more or fewer components, or a combination of certain components, or different arrangements of components.

[0134] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the above-mentioned physical device, and supports the operation of the information processing program and other software and / or programs. The network communication module is used to realize the communication between the components inside the storage medium, and the communication with other hardware and software in the information processing physical device.

[0135] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present disclosure can be implemented by means of software plus a necessary general hardware platform, or by hardware. Compared with the prior art, the dot record optimization method, device, and electronic device provided by the present disclosure obtain the real-time location information of the mobile device according to a preset data acquisition time interval and a preset number of consecutive data acquisitions; determine the driving status of the mobile device according to the real-time location information; and adjust the preset data acquisition time interval and the preset number of consecutive data acquisitions based on the driving status of the mobile device. For the embodiments of the present disclosure, by adjusting the preset data acquisition time interval and the preset number of consecutive data acquisitions based on the driving status of the mobile device, the location of the logistics transportation vehicle can be accurately located in complex terrain such as a group of overpasses.

[0136] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0137] The above are only specific embodiments of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features applied herein.

Claims

1. A dot record optimization method, characterized in that: The method comprises: Acquire the real-time location information of the mobile device according to the preset data acquisition time interval and the preset number of continuous data acquisitions; Determining the driving status of the mobile device according to the real-time location information; The preset data acquisition time interval and the preset number of consecutive data acquisition times are adjusted based on the driving state of the mobile device.

2. The method according to claim 1, characterized in that Determining the driving state of the mobile device according to the real-time location information includes: Determining a position change value between a current position and a previous position of the mobile device according to the real-time position information; Determining a temporary driving state of the mobile device according to the position change value and a preset position change threshold; A driving state of the mobile device is determined based on the temporary driving state.

3. The method according to claim 2, characterized in that The position change value includes a distance change value and a height change value, and the preset position change threshold includes a preset distance change threshold and a preset height change threshold; The determining the temporary driving state of the mobile device according to the position change value and a preset position change threshold value includes: Calculating a normal distance value and a normal height value between a current position and a previous position of the mobile device; The temporary driving state of the mobile device is determined according to the distance change value, the normal distance value, the preset distance change threshold, the height change value, the normal height value and / or the preset height change threshold.

4. The method according to claim 3, characterized in that The determining the temporary driving state of the mobile device according to the distance change value, the normal distance value, the preset distance change threshold, the height change value, the normal height value and / or the preset height change threshold comprises: If the distance change value is 0, determining that the temporary driving state of the mobile device is a docked state; If the distance change value is greater than the normal distance value, and the difference between the distance change value and the normal distance value is greater than the preset distance change threshold, determining that the temporary driving state of the mobile device is an acceleration state; If the distance change value is less than the normal distance value, and the difference between the normal distance value and the distance change value is greater than the preset distance change threshold, determining that the temporary driving state of the mobile device is a deceleration state; If the height change value is greater than the normal height value, and the difference between the height change value and the normal height value is greater than the preset height change threshold, determining that the temporary driving state of the mobile device is an uphill state; If the height change value is smaller than the normal height value, and the difference between the normal height value and the height change value is greater than the preset height change threshold, it is determined that the temporary driving state of the mobile device is a downhill state.

5. The method according to claim 4, characterized in that The determining the driving state of the mobile device based on the temporary driving state includes: Calculating a straight-line distance value, a normal straight-line distance value, and a vector cosine value between a current position and a previous position of the mobile device, and calculating a current speed of the current position of the mobile device and a historical speed of the previous position of the mobile device; The driving state of the mobile device is determined according to the temporary driving state, the straight-line distance value, the normal straight-line distance value, the vector cosine value, the current speed and / or the historical speed.

6. The method according to claim 5, characterized in that The determining the driving state of the mobile device according to the temporary driving state, the straight-line distance value, the normal straight-line distance value, the vector cosine value, the current speed and / or the historical speed includes: If the straight-line distance value is 0, it is determined that the driving state of the mobile device is a docked state; If the temporary driving state is the same temporary driving state for a preset number of consecutive times, determining that the temporary driving state is the driving state of the mobile device; If the temporary driving state is a different temporary driving state for a preset number of consecutive times, and the straight-line distance value is less than or equal to half of the normal straight-line distance value, then the driving state of the mobile device is determined to be an interchange maze state; If the temporary driving state is a different temporary driving state for a preset number of consecutive times, the straight-line distance value is less than or equal to half of the normal straight-line distance value, and the vector cosine value is greater than a first preset threshold, then the driving state of the mobile device is determined to be an overpass group state; If the vector cosine value is less than a second preset threshold value, and the speed difference ratio between the current speed and the historical speed is less than a preset speed difference ratio, it is determined that the driving state of the mobile device is a normal driving state, wherein the first preset threshold value is greater than the second preset threshold value.

7. The method according to claim 6, characterized in that The adjusting the preset data acquisition time interval and the preset number of consecutive data acquisitions based on the driving state of the mobile device includes: If the driving state is an acceleration state, a downhill state, an interchange maze state and / or an interchange bridge group state, the preset data acquisition time interval is adjusted to a first data acquisition time interval, and the preset continuous data acquisition number is adjusted to a first continuous data acquisition number; If the driving state is a deceleration state and / or an uphill state, the preset data acquisition time interval is adjusted to a second data acquisition time interval, and the preset number of continuous data acquisitions is adjusted to a second number of continuous data acquisitions; If the driving state is a parking state, adjusting the preset data acquisition time interval to a third data acquisition time interval, and adjusting the preset number of consecutive data acquisition times to a third number of consecutive data acquisition times; If the driving state is a normal driving state, the data acquisition time interval is adjusted to the preset data acquisition time interval, and the number of continuous data acquisitions is adjusted to the preset number of continuous data acquisitions; The first data acquisition time interval is smaller than the second data acquisition time interval, the second data acquisition time interval is smaller than the third data acquisition time interval, the first continuous data acquisition number is larger than the second continuous data acquisition number, and the second continuous data acquisition number is larger than the third continuous data acquisition number.

8. A dot record optimization device, characterized in that: The device comprises: An acquisition module, used to acquire real-time location information of a mobile device according to a preset data acquisition time interval and a preset number of continuous data acquisitions; A determination module, used to determine the driving state of the mobile device according to the real-time location information; The adjustment module is used to adjust the preset data acquisition time interval and the preset number of consecutive data acquisition times based on the driving state of the mobile device.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

11. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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