CN114170704A - Digital intelligent vehicle monitoring system - Google Patents
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- CN114170704A CN114170704A CN202111298925.5A CN202111298925A CN114170704A CN 114170704 A CN114170704 A CN 114170704A CN 202111298925 A CN202111298925 A CN 202111298925A CN 114170704 A CN114170704 A CN 114170704A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B3/00—Audible signalling systems; Audible personal calling systems
- G08B3/10—Audible signalling systems; Audible personal calling systems using electric transmission; using electromagnetic transmission
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Abstract
The invention discloses a digital intelligent vehicle monitoring system, which comprises: the vehicle monitoring system comprises a vehicle acquisition feedback module, a vehicle monitoring management module and a warning module. The system carries out preprocessing operation on data after importing the data, wherein invalid data are filtered out firstly, then valid data are transmitted into corresponding modules according to different types, real-time anomaly detection, analysis and prediction and the like are carried out on the data, and finally the data are displayed or exported according to the requirements of management personnel. The invention has the following advantages: the method simplifies the manual operation of the vehicle-related data, flexibly manages and monitors the vehicle, can effectively avoid the condition that a manager cannot control the vehicle journey and the reason of data abnormity in real time, the driving process of a driver deviating from a specified route and the like, also improves the accuracy of the enterprise in real-time control of the vehicle journey information, and enables the enterprise to efficiently manage the vehicle-related data.
Description
Technical Field
The invention relates to the field of vehicle management, in particular to a digital intelligent vehicle monitoring system.
Background
During the driving process of the vehicle, the vehicle generates a large amount of data related to the vehicle, and the driving condition of the vehicle and the driving condition of the driver can be reflected by analyzing the data related to the vehicle. In order to comprehensively analyze the data to achieve the purpose of monitoring the vehicle, the most original method is that after the vehicle runs for a period of time, a data analyzer collects the data related to the vehicle for the period of time to perform manual analysis and prediction, and judges whether the vehicle is in an abnormal state, however, the time required for taking proper measures to enable the vehicle to reach a normal state is greatly reduced. In the following, a vehicle data analysis device for analyzing vehicle data showing a time-series change in a vehicle state, such as the invention patent named "vehicle data analysis device, vehicle data analysis method, and failure diagnosis device" (publication number CN 103443608A), has appeared, in which an operation unit of the device generates an operation result, and a recognition unit of the device uses the result as a criterion for judging the vehicle state, thereby specifying a portion where abnormal data is generated and clarifying a cause of an abnormality in the vehicle state. However, this method needs to prepare an effective and reliable model, and the model also needs to acquire a plurality of vehicle data as model data in advance, and a large amount of data is not always suitable for the model, and the calculation result of the model data generates a lot of unavoidable errors, so that the range of normal data is expanded, and the detection effect of abnormal data is not good.
At present, an iOBD (iOn-Board Diagnostics, i-th generation vehicle-mounted automatic diagnosis system) system is also available, which is a system for monitoring the running condition of a vehicle, can monitor whether the tail gas of the vehicle exceeds the standard or not at any time according to the running condition of an engine, and can give out a warning when the tail gas exceeds the standard, and can realize the warning and detection of automobile faults. For example, in an invention patent named "vehicle management system based on iOBD and a vehicle management method thereof" (publication number CN 102881057A), when a system fails, an iOBD system failure lamp or a check engine warning lamp is turned on, and a Powertrain Control Module (PCM) stores failure information in a memory, and a failure code can be read out from the PCM by a certain program. According to the prompt of the fault code, professional maintenance personnel can quickly and accurately determine the nature and the position of the fault. However, the system can only diagnose the fault of a single vehicle, and how to apply the system to a vehicle management system of a large enterprise is not involved, so that the enterprise cannot monitor the vehicle in real time.
In the patent document, a method for automatically and intelligently detecting the entering and exiting vehicles is provided aiming at the problem that enterprises cannot realize real-time monitoring of vehicles, for example, in an invention patent named as an intelligent vehicle management system (with the publication number being CN 111915784A), real-time vehicle data required by relevant vehicle information, geographic position information, departure personnel information and the like is acquired through a flagship version light supplement snapshot all-in-one machine, an employee mobile phone easy-to-believe APP, a vehicle-mounted GPS and other data acquisition devices, and aiming at the defects of the existing RFID (radio frequency identification) technology, OCR (optical character recognition) technology, vehicle positioning and vehicle dispatching process and the butt joint function of an enterprise OA (office automation) system, automatic data transmission and real-time processing feedback among all systems are realized, so that the purpose of intelligently managing the vehicles is achieved. However, the system is only beneficial to the management of the personnel entering and exiting the vehicle, and the intelligent vehicle management function is single, so that the system is not practical for most enterprises on the market.
Disclosure of Invention
The invention aims to provide a digital intelligent vehicle monitoring system which has the functions of data preprocessing, automatic exception handling and the like, and performs special processing on data generated in the vehicle driving process by using various algorithms, Beidou positioning and other methods on the premise of not manually counting various numerical values so as to achieve the purposes of managing and monitoring the vehicle driving, refueling conditions and driver states in real time.
The purpose of the invention is realized as follows:
a digital intelligent vehicle monitoring system is characterized in that: including vehicle acquisition feedback module, vehicle supervision management module and warning module, wherein:
A. the vehicle acquisition feedback module comprises: the system comprises a journey data acquisition submodule, a refueling data acquisition submodule and a front-end and rear-end information interaction submodule;
a. the driving data acquisition submodule comprises: the system is used for acquiring vehicle related data of a vehicle in the driving process;
b. the refueling data acquisition submodule comprises: the system is used for collecting vehicle-related data when a vehicle is refueled;
c. the front-end and back-end information interaction submodule: the system comprises a vehicle monitoring management module, a driving data acquisition submodule and a refueling data acquisition submodule, wherein the vehicle monitoring management module is used for transmitting data acquired by the driving data acquisition submodule or the refueling data acquisition submodule to the vehicle monitoring management module, receiving data and abnormal value signals processed and sent by the vehicle monitoring management module, and transmitting the abnormal value signals to a warning module for voice warning to remind a driver of driving reasonably;
B. the vehicle monitoring management module comprises: the system comprises a vehicle journey data preprocessing submodule, a vehicle data statistics submodule, a real-time journey tracking data submodule, an abnormal data processing submodule, a data analysis and prediction submodule and an import and export submodule;
a. the vehicle travel data preprocessing submodule comprises: the data acquisition submodule is used for preprocessing the data acquired by the data acquisition submodule, and comprises data duplication removal, wrong value cleaning, missing value filling and the like;
b. the vehicle data statistics submodule is: the data preprocessing submodule is used for carrying out statistics on the data processed by the vehicle travel data preprocessing submodule, and the data which can be counted comprises daily, monthly, quarterly and annual oil consumption data, various expense data, hundred kilometer oil consumption data and the like;
c. the real-time tracking journey data submodule: the data processing sub-module is used for comparing the data counted by the vehicle data counting sub-module with the data stored in the data table in real time, screening abnormal data and transmitting the abnormal data to the abnormal data processing sub-module for corresponding processing;
d. the abnormal data processing submodule is used for: the method is used for vehicle oil consumption exception handling, vehicle cost exception handling and vehicle running longitude and latitude exception handling;
e. the data analysis predictor module: the method is used for abnormal data analysis and normal data analysis;
f. the import/export submodule: the system is used for importing vehicle dispatching information, vehicle specific travel information, vehicle fuel consumption information of the year, the month, the quarter and the year, vehicle cost information of the year, and the like;
C. the warning module is connected with the vehicle acquisition feedback module and used for receiving abnormal value signals of the front-end and rear-end information interaction sub-modules in the vehicle acquisition feedback module and converting radio signals into sound signals to be played;
a. the outlier signal includes: an abnormal signal that the vehicle running track deviates from a specified track, an abnormal signal that the vehicle refuels at an unspecified gas station, and an abnormal signal that the vehicle has a rest in an unspecified area.
The invention has the advantages that:
1. the vehicle-related data can be automatically and intelligently processed and fed back in real time, and the acquired information is subjected to data analysis, threshold judgment, import and export as required and the like, so that the pressure of manual processing of huge data is effectively reduced, and the error rate of calculation results during statistics and analysis is reduced;
2. the method simplifies the manual operation of the vehicle-related data, flexibly manages and monitors the vehicle, can effectively avoid the condition that a manager cannot control the vehicle journey and the reason of data abnormity in real time, the driving process of a driver deviating from a specified route and the like, also improves the accuracy of the enterprise in real-time control of the vehicle journey information, and enables the enterprise to efficiently manage the vehicle-related data.
Drawings
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic diagram of a real-time trip data tracking sub-module;
fig. 3 is a flow chart of the present invention for processing a rest area.
The specific implementation mode is as follows:
in order to make the objects, embodiments and advantages of the present invention more apparent, the technical solutions in the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings in the embodiments of the present invention. It should be noted that the specific embodiments described herein are merely exemplary to illustrate the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a schematic structural diagram of a digital intelligent vehicle monitoring system 111 according to an embodiment of the present invention includes a vehicle acquisition feedback module 100, a vehicle monitoring management module 200, and an alert module 300, where:
A. the vehicle acquisition feedback module 100 includes: a driving data acquisition submodule 101, a refueling data acquisition submodule 102 and a front-end and rear-end information interaction submodule 103;
further, the driving data collection sub-module 101: the system is used for realizing the real-time collection of vehicle information data, wherein the vehicle information data comprises basic vehicle factory basic information data, vehicle mileage information data, vehicle oil consumption information data, vehicle running track information data and the like;
further, the fueling data acquisition sub-module 102: the system is used for acquiring the current vehicle oil quantity information data, the refueling time, the refueling amount, the vehicle position in the refueling time period and the like in real time;
further, the front-end and back-end information interaction sub-module 103: the system is used for transmitting data acquired by the driving data acquisition submodule 101 or the refueling data acquisition submodule 102 to the vehicle monitoring management module 200, and meanwhile, the system can receive data processed by the vehicle monitoring management module 200, such as vehicle route travel information, vehicle route deviation warning information and designated area parking information, and can also receive abnormal value signals transmitted by the vehicle monitoring management module 200, and transmit the abnormal value signals to the warning module 300 to perform voice alarm to remind a driver of driving reasonably.
B. The vehicle monitoring management module 200 includes: the system comprises a vehicle journey data preprocessing submodule 201, a vehicle data statistics submodule 202, a real-time journey tracking data submodule 203, an abnormal data processing submodule 204, a data analysis and prediction submodule 205 and an import and export submodule 206;
further, the vehicle travel data preprocessing sub-module 201: and the data processing module is configured to receive data acquired by the driving data acquisition submodule 101 or the refueling data acquisition submodule 102, and perform data deduplication, wrong value cleaning, and missing value filling operations on the received data. For example: during the running process of the vehicle, certain data are repeatedly recorded for a plurality of times within fifteen seconds, and the data need to be filtered; in the Beidou positioning use process, when the latitude and longitude values of a certain time point are greatly different from the latitude and longitude values in the adjacent time period, the latitude and longitude value of the time point is judged to be an error value, and the error value is removed by using a K-MEANS clustering algorithm; the missing values can be filled by using a mean-value half-variance method;
the K-MEANS clustering algorithm used in the above example is a common statistical data analysis technique, which is referred to as "optimized K-MEANS clustering algorithm for data including abnormal values", jean, west ampere electronics science and technology university, 2009;
the mean-half-variance method employed in the above examples is a method derived from the mean-half-variance model, see "A novel analog based on a harmonic search and intellectual property bean color for solving a recursive approximation a mean-variance approach", a second Mohammad Seyhossei, a hammad Javaesfahai, a Mehdi Ghaffari, Journal of Central South University,2016,23(01): 181-188;
further, the vehicle data statistics sub-module 202: the vehicle-related data processed by the vehicle journey data preprocessing submodule 201 are used for counting. The data counted by the vehicle data counting sub-module 202 specifically includes: daily, monthly, quarterly and annual oil consumption data statistics, daily, monthly, quarterly and annual generated expense statistics of each item, daily, monthly, quarterly and annual hundred kilometer oil consumption data statistics and the like. For example: the vehicle travel data obtained by the vehicle travel data preprocessing submodule 201 includes mileage, oil consumption, travel track, maintenance and repair information, and the vehicle data statistics submodule 202 can count the total oil consumption, total oil cost, total maintenance cost, total mileage, oil consumption per hundred kilometers, and oil cost per hundred kilometers of the vehicle in days, months, quarters, and years;
further, the real-time tracking trip data sub-module 203: the system is used for monitoring the vehicle travel track information in real time, giving a specified route according to the starting place and the destination of the imported vehicle dispatching list, and simultaneously dividing the area range of an oil filling point and a rest point on the specified route;
further, the exception data processing sub-module 204: and the data processing module is used for processing the abnormal data screened out by the real-time tracking journey data submodule, classifying the data beyond the normal range into corresponding abnormal data according to various numerical value ranges preset by an enterprise, and storing the data into corresponding database tables. The processing types of the method can specifically comprise vehicle oil consumption exception processing, vehicle cost exception processing and vehicle running longitude and latitude exception processing. For example: the abnormal processing of the vehicle oil consumption is judged according to the initially given maximum value and minimum value of the oil consumption of the system, and when the oil consumption value is not in a normal range, the data is classified to be abnormal in oil consumption and isolated from other normal data;
further, the data analysis prediction sub-module 205: the vehicle data statistics sub-module 202 and the abnormal data processing sub-module 204 are used for performing subsequent analysis and prediction on the vehicle related data, specifically including abnormal data analysis and normal data analysis. For example, oil consumption values in abnormal data are sorted according to time, a trend graph is displayed in the background, an enterprise can properly adjust a normal maximum threshold value and a normal minimum threshold value of oil consumption according to a line graph, and for example, all cost values in normal data are sorted according to time, a data line graph in recent years is displayed in the background, and the enterprise can visually reflect the development trend of the enterprise according to the trend graph;
further, the import-export submodule 206: for collecting data that cannot be collected by the vehicle collection feedback module 100, for example: vehicle maintenance information data, vehicle dispatch information data, and the like. In the import/export sub-module 206, various excel table data are imported into the corresponding database through the vehicle data statistics sub-module 202, so that other modules can call the required data conveniently. The import/export sub-module 206 may also invoke and export the corresponding excel table data from the vehicle data statistics sub-module 202 according to the statistical data required by the enterprise, and may query the data information in various reports.
Now, a specific design manner of the real-time tracking journey data sub-module 203 is illustrated, and the function implementation of the real-time tracking journey data sub-module 203 needs to be completed by cooperation of the journey data acquisition sub-module 101, the refueling data acquisition sub-module 102, the front-end and back-end information interaction sub-module 103, the vehicle journey data preprocessing sub-module 201, the vehicle data statistics sub-module 202, the abnormal data processing sub-module 204 and the warning module 300, and the structure of the real-time tracking journey data sub-module is shown in fig. 2.
The vehicle collection feedback module 100 collects vehicle related data generated during vehicle driving through the frequency that the driving data collection submodule 101 and the refueling data collection submodule 102 are once every fifteen seconds, after a certain amount of data is collected, the front-end and back-end information interaction submodule 103 sends corresponding instructions to the driving data collection submodule 101 and the refueling data collection submodule 102, after receiving the corresponding instructions, the driving data collection submodule 101 and the refueling data collection submodule 102 send all vehicle related data collected from the previous received instructions to the current received instructions to the vehicle travel data preprocessing submodule 201 of the vehicle monitoring management module 200, the vehicle travel data preprocessing submodule 201 preprocesses the received vehicle related data, and sends the processed vehicle related data to the vehicle data statistics submodule 202 for statistics, the vehicle data statistics sub-module 202 transmits the counted vehicle-related data to the real-time tracking travel data sub-module 203 in real time, the real-time tracking travel data sub-module 203 compares the received vehicle-related data with a threshold corresponding to each index of the vehicle-related data in a database table, if the data is larger than the threshold, the data is abnormal, the real-time tracking travel data sub-module 203 transmits abnormal data to the abnormal data processing sub-module 204 for data optimization, and meanwhile, the abnormal data processing sub-module 204 transmits abnormal value signals to the warning module 300 through the vehicle data statistics sub-module 202 and the front-back end information interaction sub-module 103 of the vehicle acquisition feedback module 100 in sequence to perform voice warning to remind a driver of reasonable driving.
Three specific examples of the real-time tracking trip data sub-module 203 are given below in conjunction with fig. 2.
The real-time operation for monitoring the vehicle track comprises the following specific steps: in the vehicle running process, the vehicle acquisition feedback module 100 transmits the acquired vehicle trajectory data to the vehicle running data preprocessing submodule 201 of the vehicle monitoring background management module 200 every fifteen seconds, and the vehicle running data preprocessing submodule 201 performs data preprocessing on the received vehicle trajectory data and sends the processed vehicle trajectory data to the vehicle data statistics submodule 202 for statistics. The vehicle data statistics submodule 202 transmits the counted vehicle track data to the real-time tracking travel data submodule 203 in real time, the real-time tracking travel data submodule 203 compares the longitude and the latitude of the received vehicle track data with a route preset by a system, judges whether a driver runs according to a specified route according to a difference threshold value given by the system, if the running route of the driver deviates from the specified route, marks the deviated track data as abnormal and uploads the abnormal track data to the abnormal data processing submodule 204, meanwhile, the abnormal data processing submodule 204 transmits an abnormal value signal to the warning module 300 through the vehicle data statistics submodule 202 and the front-end and back-end information interaction submodule 103 of the vehicle acquisition feedback module 100, and the warning module 300 immediately sends a voice alarm to the driver after receiving the abnormal value signal, meanwhile, the current deviation route map and the specified route map can be displayed to the driver through a mobile phone APP or special equipment.
The method comprises the following specific steps of monitoring refueling of a vehicle within a specified range in real time: starting from the starting point of the vehicle, timing is started, if the insufficient fuel quantity of the vehicle is detected, the front-end and rear-end information interaction submodule 103 of the vehicle acquisition feedback module 100 transmits an abnormal value signal to the warning module 300, and the warning module 300 immediately sends a voice alarm to the driver after receiving the abnormal value signal, displays the abnormal value signal to a nearest refueling area near the driver through a mobile phone APP or special equipment, and guides the driver to refuel in the area designated by the system. During this period, the fuel quantity of the fuel tank rises to trigger the vehicle collection feedback module 100 to upload the vehicle position data to the vehicle driving data preprocessing submodule 201 of the vehicle monitoring management module 200, the vehicle travel data preprocessing sub-module 201 performs data preprocessing on the received vehicle position data, and sends the processed vehicle position data to the vehicle data statistics sub-module 202 for statistics, the vehicle data statistics submodule 202 transmits the counted vehicle position data to the real-time follow-up trip data submodule 203 in real time, the real-time tracking journey data submodule 203 compares the received vehicle position data with the longitude and latitude within the refueling range specified by the system, and judges whether the driver refuels within the specified range, the refueling time difference is not more than 15 minutes, and the refueling range difference is not more than 100 meters.
The real-time operation of the vehicle for monitoring the rest within the specified range comprises the following specific steps: starting from the starting point of the vehicle, timing is started, if the time for the driver to drive the vehicle reaches four hours, the front-end and rear-end information interaction sub-module 103 of the vehicle acquisition feedback module 100 transmits an abnormal value signal to the warning module 300, and when the warning module 300 receives the abnormal value signal, a voice alarm is immediately sent to the driver, and the abnormal value signal is displayed to the nearest rest area near the driver through a mobile phone APP or special equipment and guides the driver to rest in the designated area. In this period, the vehicle collection feedback module 100 transmits the collected vehicle trajectory data to the vehicle driving data preprocessing submodule 201 of the vehicle monitoring management module 200 every fifteen seconds, the vehicle driving data preprocessing submodule 201 performs data preprocessing on the received vehicle trajectory data and sends the processed vehicle trajectory data to the vehicle data statistics submodule 202 for statistics, the vehicle data statistics submodule 202 transmits the counted vehicle trajectory data to the real-time tracking stroke data submodule 203 in real time, the real-time tracking stroke data submodule 203 compares the received vehicle trajectory data with the longitude and latitude within the rest range specified by the system, and judges whether the driver has a rest within the specified range, and the rest time is not less than one hour.
Fig. 3 schematically shows a flowchart of the processing of the rest area by the digital intelligent vehicle monitoring system 111 according to the present invention, which includes the following steps:
in step S301, the driving data collecting submodule 101 of the vehicle collecting and feedback module 100 collects driving time data of a vehicle, and sends the driving time data to the vehicle journey data preprocessing submodule 201 of the vehicle monitoring and managing module 200 through the front-end and back-end information interaction submodule 103 every fifteen seconds.
In step S302, the vehicle journey data preprocessing submodule 201 performs data preprocessing on the received travel time data, and transmits the processed travel time data to the vehicle data statistics submodule 202 for statistics.
In step S303, the vehicle data statistics sub-module 202 compares the received travel time data with the threshold stored in the database, determines whether the travel time data exceeds the threshold, and if so, goes to steps S304 and S305; otherwise, the process goes to step S301.
In step S304, when the driving time data exceeds the threshold, the abnormal value signal transmitted from the vehicle data statistics sub-module 202 is transmitted to the warning module 300 through the front-end and back-end information interaction sub-module 103 of the vehicle acquisition feedback module 100, and the warning module 300 receives the abnormal value signal, converts the electrical signal into an acoustic signal, and performs a voice alarm.
In step S305, when the travel time data exceeds the threshold, the vehicle data statistics sub-module 202 sends the abnormal data to the abnormal data processing sub-module 204 for performing corresponding abnormal optimization processing.
In step S306, when the travel time data is abnormal, the vehicle data statistics sub-module 202 compares the longitude and latitude in the vehicle trajectory data with the longitude and latitude of a rest area specified by the system, and determines whether the driver has a rest in the specified rest area, if not, the driver continues to go to step S305 to perform determination and step S304 to perform voice alarm reminding; otherwise, the process goes to step S307.
In step S307, when the driver takes a rest in a predetermined rest area, the vehicle data statistics submodule 202 transmits a signal indicating that the rest is started to the vehicle collection feedback module 100, when the driver takes a rest, the trip data collection submodule 101 and the fueling data collection submodule 102 of the vehicle collection feedback module 100 should keep a stable value, and the driver should take a rest for at least one hour after fatigue driving according to the specification, so that it should be determined whether the data of the vehicle collection feedback module is changed, if so, it indicates that the driver is still in fatigue driving, and it should turn to the step S305 to determine whether the driver is in the rest area and perform the voice alarm prompt in step S304; otherwise, the driver is indicated to rest in the designated rest area according to the regulations without any treatment.
Claims (4)
1. The utility model provides a digital intelligent vehicle monitored control system which characterized in that: including vehicle acquisition feedback module, vehicle supervision management module and warning module, wherein:
A. the vehicle acquisition feedback module comprises: the system comprises a journey data acquisition submodule, a refueling data acquisition submodule and a front-end and rear-end information interaction submodule;
B. the vehicle monitoring management module comprises: the system comprises a vehicle journey data preprocessing submodule, a vehicle data statistics submodule, a real-time journey tracking data submodule, an abnormal data processing submodule, a data analysis and prediction submodule and an import and export submodule;
C. the warning module is connected with the vehicle acquisition feedback module and used for receiving abnormal value signals of the front-end and rear-end information interaction sub-modules in the vehicle acquisition feedback module and converting radio signals into sound signals to be played.
2. The digital intelligent vehicle monitoring system of claim 1, wherein: the vehicle acquisition feedback module comprises:
a. the driving data acquisition submodule comprises: the system is used for acquiring vehicle related data of a vehicle in the driving process;
b. the refueling data acquisition submodule comprises: the system is used for collecting vehicle-related data when a vehicle is refueled;
c. the front-end and back-end information interaction submodule: the system comprises a driving data acquisition submodule and a refueling data acquisition submodule, wherein the driving data acquisition submodule or the refueling data acquisition submodule is used for transmitting data acquired by the driving data acquisition submodule or the refueling data acquisition submodule to the vehicle monitoring management module, meanwhile, the system can also receive data and abnormal value signals processed and sent by the vehicle monitoring management module, and transmits the abnormal value signals to the warning module to perform voice warning to remind a driver of driving reasonably.
3. The digital intelligent vehicle monitoring system of claim 1, wherein: the vehicle monitoring management module comprises:
a. the vehicle travel data preprocessing submodule comprises: the data acquisition submodule is used for preprocessing the data acquired by the data acquisition submodule, and comprises data duplication removal, wrong value cleaning and missing value filling;
b. the vehicle data statistics submodule is: the data preprocessing submodule is used for carrying out statistics on the data processed by the vehicle travel data preprocessing submodule, and the data which can be counted comprises daily, monthly, quarterly and annual oil consumption data, various expense data and hundred kilometer oil consumption data;
c. the real-time tracking journey data submodule: the data processing sub-module is used for comparing the data counted by the vehicle data counting sub-module with the data stored in the data table in real time, screening abnormal data and transmitting the abnormal data to the abnormal data processing sub-module for corresponding processing;
d. the abnormal data processing submodule is used for: the method is used for vehicle oil consumption exception handling, vehicle cost exception handling and vehicle running longitude and latitude exception handling;
e. the data analysis predictor module: the method is used for abnormal data analysis and normal data analysis;
f. the import/export submodule: the system is used for importing vehicle dispatching information, vehicle specific travel information, vehicle fuel consumption information of the year, the month, the quarter and the year, vehicle cost information of the year, month, quarter and the like.
4. The digital intelligent vehicle monitoring system of claim 1, wherein: the outlier signal of the alert module comprises: an abnormal signal that the vehicle running track deviates from a specified track, an abnormal signal that the vehicle refuels at an unspecified gas station, and an abnormal signal that the vehicle has a rest in an unspecified area.
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| CN116342008A (en) * | 2023-03-26 | 2023-06-27 | 广州智卡物流科技有限公司 | Logistics road transportation management method and system |
| CN117912133A (en) * | 2024-03-19 | 2024-04-19 | 杭州三一谦成科技有限公司 | Vehicle information coefficient acquisition system based on measured data |
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