CN117217651A - Monitoring platform for truck transportation process - Google Patents
Monitoring platform for truck transportation process Download PDFInfo
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- CN117217651A CN117217651A CN202311482211.9A CN202311482211A CN117217651A CN 117217651 A CN117217651 A CN 117217651A CN 202311482211 A CN202311482211 A CN 202311482211A CN 117217651 A CN117217651 A CN 117217651A
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- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000012544 monitoring process Methods 0.000 title claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 42
- 230000002159 abnormal effect Effects 0.000 claims abstract description 15
- 238000012545 processing Methods 0.000 claims abstract description 15
- 238000011161 development Methods 0.000 claims abstract description 7
- 238000012800 visualization Methods 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 32
- 239000000446 fuel Substances 0.000 claims description 26
- 238000004891 communication Methods 0.000 claims description 10
- 238000011217 control strategy Methods 0.000 claims description 4
- 238000013480 data collection Methods 0.000 claims description 4
- 238000000926 separation method Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 abstract description 2
- 230000005856 abnormality Effects 0.000 description 6
- 230000035945 sensitivity Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a monitoring platform for a truck transportation process, which relates to the technical field of freight monitoring and comprises the following components: the data acquisition module of the truck transportation site is integrated in the vehicle-mounted terminal by adopting an embedded development method and is used for acquiring data of the truck transportation site; the freight transportation data processing module is used for carrying out abnormal analysis on the data acquired by the freight transportation site data acquisition module and alarming the freight transportation site according to the analysis result; and the trucking process visualization module is used for visualizing the data acquired by the trucking field data acquisition module and the alarm record of the trucking data processing module. The position of the truck is tracked in real time, the safety and on-time delivery of the truck are ensured, suspicious activities are found in time, and an alarm is sent to related personnel.
Description
Technical Field
The invention relates to the technical field of freight monitoring, in particular to a monitoring platform for a freight transportation process.
Background
Along with the rapid development of electronic commerce, the traditional logistics industry also has rapid development, and a plurality of problems are caused while the rapid development of the logistics industry brings about economic growth. How to realize safety, high-efficient, scientific dispatch and management to enterprise logistics vehicles improves the competitiveness of enterprise in commodity circulation market, ensures driver and goods's safety, saves logistics cost, is all logistics enterprises all face and the urgent problem that needs to solve.
Disclosure of Invention
The invention provides a monitoring platform for a truck transportation process, which comprises the following components: the system comprises a trucking site data acquisition module, a trucking data processing module and a trucking process visualization module;
the data acquisition module of the truck transportation site is integrated in the vehicle-mounted terminal by adopting an embedded development method and is used for acquiring data of the truck transportation site;
the freight transportation data processing module is used for carrying out abnormal analysis on the data acquired by the freight transportation site data acquisition module and alarming the freight transportation site according to the analysis result;
the trucking process visualization module is used for visualizing data acquired by the trucking field data acquisition module and alarm records of the trucking data processing module.
The monitoring platform for the truck transportation process is characterized in that the truck-mounted terminal is both acquisition equipment and control equipment, the platform initiates a control instruction to the truck-mounted terminal through network communication, and the truck-mounted terminal forwards the instruction to the control equipment.
The monitoring platform for the freight transportation process, as described above, performs exception analysis on data collected by the freight transportation site data collection module, and alarms the freight transportation site according to analysis results, specifically includes the following sub-steps:
the collected data are arranged to form a feature set required by anomaly analysis;
inputting the feature set into an anomaly analysis model, and outputting anomaly types;
and alarming the freight site according to the output result of the anomaly analysis model.
A monitoring platform for a trucking process as described above wherein the anomaly analysis model comprises: overspeed detection, abnormal fuel detection, fatigue driving detection, box door detection and route deviation detection.
A monitoring platform for a trucking process as described above, wherein the freight site is alerted based on the output of an anomaly analysis model, comprising the sub-steps of:
intercepting an abnormal analysis model output result S by taking "+" as a separation;
alarming according to the intercepted abnormal type expression value, and setting a safety control strategy;
recording the alarm time and the alarm information.
The monitoring platform for the trucking process, as described above, wherein the data collected by the trucking field data collection module and the alarm record of the trucking data processing module are visualized, specifically comprises the following sub-steps:
displaying the real-time position of the vehicle according to the GPS data acquired in real time by using a map API, and providing track playback;
generating a historical period oil quantity curve graph in real time according to the change of the fuel quantity of the truck;
and when an alarm occurs, carrying out popup window display, and displaying alarm records in a list mode.
The invention also provides a monitoring method of the truck transportation process, which comprises the following steps:
step1, acquiring data of a truck transportation site through a vehicle-mounted terminal;
step2, carrying out anomaly analysis on the collected site data, and alarming a freight site according to an analysis result;
step3, visualizing the acquired data and the abnormal alarm information.
The beneficial effects achieved by the invention are as follows: the position of the truck is tracked in real time, the safety and on-time delivery of the truck are ensured, suspicious activities are found in time, and an alarm is sent to related personnel.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
Fig. 1 is a view showing a monitoring platform for a trucking process according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, a first embodiment of the present invention provides a monitoring platform for a trucking process, including: the system comprises a trucking site data acquisition module, a trucking data analysis module and a trucking process visualization module;
(1) The data acquisition module of the truck transportation site is integrated in the vehicle-mounted terminal by adopting an embedded development method and is used for acquiring data of the truck transportation site;
the vehicle-mounted terminal collects real-time positioning of a truck through GPS equipment; collecting monitoring images in the transportation process by connecting a small high-definition camera installed on a truck; collecting real-time data of a vehicle through an OBD (On-Board Diagnostics) interface connected with a truck comprises: vehicle speed, fuel amount, etc.; the carriage door electronic lock is connected through wireless communication to acquire the state of the electronic lock.
The vehicle-mounted terminal is not only the acquisition equipment but also the control equipment, the platform initiates a control instruction to the vehicle-mounted terminal through network communication, and the vehicle-mounted terminal forwards the instruction to the control equipment.
(2) The freight transportation data processing module is used for carrying out abnormal analysis on the data acquired by the freight transportation site data acquisition module and alarming the freight transportation site according to the analysis result;
the trucking data processing module is provided with a timer, and the data acquired by the trucking site data acquisition module is pulled out at fixed time through network communication, so that the interval time of the timer can be set; the box door electronic lock is set to be in a closed state when transportation starts, and can be opened only when the delivery place is reached by the platform to send a control instruction;
I. the collected data are arranged to form a feature set required by anomaly analysis;
feature setWherein v is the vehicle speed, fu is the fuel quantity, t is the running time, lo is the state of the electronic lock of the box door, cp is the current position of the truck, and tp is the target position.
Inputting the feature set into an anomaly analysis model, and outputting anomaly types;
the anomaly analysis model is:wherein CS (v) is an overspeed detection function, a parameter is a vehicle speed v, YH (fu) is a fuel abnormality detection function, a parameter is a fuel quantity fu, PJ (t) is a fatigue driving detection function, a parameter is a travel time t, XM (lo) is a door detection function, a parameter is a door electronic lock state lo, PL (cp, tp) is a route deviation detection function, a parameter is a wagon current position cp, a target position tp, "+" is character string splicing;
overspeed detection functionWhere v is the current vehicle speed, minv is the lowest speed limit, maxv is the highest speed limit, =>For output, minv and maxv are variables, and the speed limit of the road section obtained in the map plug-in according to the current position is obtained and assigned;
fuel abnormality detection functionWhere fu is the current fuel quantity fu -1 For the last fuel quantity obtained +.>For the historical collection period of the truckAverage value of fuel amount, θ is detection sensitivity set, =>Is output;
fatigue driving detection functionWhere t is the time of continued travel, =>Is output;
box door detection functionWherein, lo is the state value of the box door, +.>For the normal and locked state of communication, +.>Whether to give instruction identification to platform, =>Is output;
route deviation detection functionWhere cp.a is the latitude of the truck current location, tp.a is the latitude of the target location, cp.b is the longitude of the current location, tp.b is the longitude of the target location, k is the set deviation threshold, =>Is output.
Inputting the feature set into an anomaly analysis model, outputting anomaly types, wherein the output S is expressed as a+b+c+d+e, and a-e respectively represent the expression values of different anomaly types.
Thirdly, alarming the freight site according to the output result of the anomaly analysis model;
intercepting an output result S of the anomaly analysis model by taking "+" as a separation, alarming according to the intercepted anomaly type expression value, and setting a safety control strategy, wherein the method comprises the following steps: remotely closing an engine, capturing by a camera, performing voice broadcasting and other controls; if the type of the intercepted abnormality is 3, indicating fatigue driving, sending alarm information to the vehicle-mounted terminal through 4G/5G network communication, broadcasting and displaying by the vehicle-mounted terminal, and recording the alarm time and the alarm information by the platform.
(3) The trucking process visualization module is used for visualizing the data acquired by the trucking site data acquisition module and the alarm record of the trucking data processing module;
I. displaying the real-time position of the vehicle according to the GPS data acquired in real time by using a map API, and providing track playback;
II, generating a historical period oil quantity curve graph in real time according to the change of the fuel quantity of the truck;
the historical period is selected as an abscissa by the time selector, the fuel quantity of the truck collected in the history is taken as an ordinate, a fuel quantity curve chart is generated, the normal part is represented by green, and the alarm part is represented by yellow.
III, when an alarm occurs, popup window display is carried out, and alarm records are displayed in a list mode;
setting content displayed by the popup window according to the alarm information and the corresponding abnormal type; clicking on record viewing details of the alarm record list, or performing remote processing.
Example two
The second embodiment of the invention provides a method for monitoring a truck transportation process, which comprises the following steps:
step S10: collecting data of a truck transportation site through a vehicle-mounted terminal;
the vehicle-mounted terminal collects real-time positioning of a truck through GPS equipment; collecting monitoring images in the transportation process by connecting a small high-definition camera installed on a truck; collecting real-time data of a vehicle through an OBD (On-Board Diagnostics) interface connected with a truck comprises: vehicle speed, fuel amount, etc.; the carriage door electronic lock is connected through wireless communication to collect and control the state of the electronic lock.
Step S20: carrying out anomaly analysis on the collected field data, and alarming a freight site according to an analysis result;
acquiring data acquired by a vehicle-mounted terminal in real time; the box door electronic lock is set to be in a closed state when transportation starts, and can be opened only when the delivery place is reached by the platform to send a control instruction;
I. the collected data are arranged to form a feature set required by anomaly analysis;
feature setWherein v is the vehicle speed, fu is the fuel quantity, t is the running time, lo is the state of the electronic lock of the box door, cp is the current position of the truck, and tp is the target position.
Inputting the feature set into an anomaly analysis model, and outputting anomaly types;
the anomaly analysis model is:wherein CS (v) is an overspeed detection function, a parameter is a vehicle speed v, YH (fu) is a fuel abnormality detection function, a parameter is a fuel quantity fu, PJ (t) is a fatigue driving detection function, a parameter is a travel time t, XM (lo) is a door detection function, a parameter is a door electronic lock state lo, PL (cp, tp) is a route deviation detection function, a parameter is a wagon current position cp, a target position tp, "+" is character string splicing;
overspeed detection functionWhere v is the current vehicle speed, minv is the lowest speed limit, maxv is the highest speed limit, =>For output, minv and maxv are variables, and the speed limit of the road section obtained in the map plug-in according to the current position is obtained and assigned;
fuel abnormality detection functionWhere fu is the current fuel quantity fu -1 For the last fuel quantity obtained +.>For the average value of the fuel quantity in the truck history acquisition period, θ is the set detection sensitivity, =>Is output;
fatigue driving detection functionWhere t is the time of continued travel, =>Is output;
box door detection functionWhich is provided withWherein lo is the door state value, +.>For the normal and locked state of communication, +.>Whether to give instruction identification to platform, =>Is output;
route deviation detection functionWhere cp.a is the latitude of the truck current location, tp.a is the latitude of the target location, cp.b is the longitude of the current location, tp.b is the longitude of the target location, k is the set deviation threshold, =>Is output.
Inputting the feature set into an anomaly analysis model, outputting anomaly types, wherein the output S is expressed as a+b+c+d+e, and a-e respectively represent the expression values of different anomaly types.
Thirdly, alarming the freight site according to the output result of the anomaly analysis model;
intercepting an output result S of the anomaly analysis model by taking "+" as a separation, alarming according to the intercepted anomaly type expression value, and setting a safety control strategy, wherein the method comprises the following steps: remotely closing an engine, capturing by a camera, performing voice broadcasting and other controls; if the type of the intercepted abnormality is 3, indicating fatigue driving, sending alarm information to the vehicle-mounted terminal through 4G/5G network communication, broadcasting and displaying by the vehicle-mounted terminal, and recording the alarm time and the alarm information by the platform.
Step S30: visualizing the acquired data and the abnormal alarm information;
I. displaying the real-time position of the vehicle according to the GPS data acquired in real time by using a map API, and providing track playback;
II, generating a historical period oil quantity curve graph in real time according to the change of the fuel quantity of the truck;
the historical period is selected as an abscissa by the time selector, the fuel quantity of the truck collected in the history is taken as an ordinate, a fuel quantity curve chart is generated, the normal part is represented by green, and the alarm part is represented by yellow.
III, when an alarm occurs, popup window display is carried out, and alarm records are displayed in a list mode;
setting content displayed by the popup window according to the alarm information and the corresponding abnormal type; clicking on record viewing details of the alarm record list, or performing remote processing.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention in further detail, and are not to be construed as limiting the scope of the invention, but are merely intended to cover any modifications, equivalents, improvements, etc. based on the teachings of the invention.
Claims (7)
1. A monitoring platform for a trucking process, comprising: the system comprises a trucking site data acquisition module, a trucking data processing module and a trucking process visualization module;
the data acquisition module of the truck transportation site is integrated in the vehicle-mounted terminal by adopting an embedded development method and is used for acquiring data of the truck transportation site;
the freight transportation data processing module is used for carrying out abnormal analysis on the data acquired by the freight transportation site data acquisition module and alarming the freight transportation site according to the analysis result;
the trucking process visualization module is used for visualizing the data acquired by the trucking field data acquisition module and the alarm record of the trucking data processing module.
2. The monitoring platform for a trucking process according to claim 1 wherein the vehicle-mounted terminal is both the acquisition device and the control device, the platform initiates control commands to the vehicle-mounted terminal via network communication, and the vehicle-mounted terminal forwards the commands to the control device.
3. The platform for monitoring a trucking process according to claim 1, wherein the data collected by the data collection module of the trucking site is subjected to anomaly analysis, and the freight site is alerted according to the analysis result, specifically comprising the following sub-steps:
the collected data are arranged to form a feature set required by anomaly analysis;
inputting the feature set into an anomaly analysis model, and outputting anomaly types;
and alarming the freight site according to the output result of the anomaly analysis model.
4. A monitoring platform for a trucking process according to claim 3 wherein the anomaly analysis model comprises: overspeed detection, abnormal fuel detection, fatigue driving detection, box door detection and route deviation detection.
5. A platform for monitoring a trucking process according to claim 3 wherein alerting the freight site based on the output of the anomaly analysis model comprises the sub-steps of:
intercepting an abnormal analysis model output result S by taking "+" as a separation;
alarming according to the intercepted abnormal type expression value, and setting a safety control strategy;
recording the alarm time and the alarm information.
6. The platform for monitoring a trucking process according to claim 1, wherein the data collected by the trucking field data collection module and the alarm records of the trucking data processing module are visualized, comprising the following sub-steps:
displaying the real-time position of the vehicle according to the GPS data acquired in real time by using a map API, and providing track playback;
generating a historical period oil quantity curve graph in real time according to the change of the fuel quantity of the truck;
and when an alarm occurs, carrying out popup window display, and displaying alarm records in a list mode.
7. A method of monitoring a trucking process comprising:
step1, acquiring data of a truck transportation site through a vehicle-mounted terminal;
step2, carrying out anomaly analysis on the collected site data, and alarming a freight site according to an analysis result;
step3, visualizing the acquired data and the abnormal alarm information.
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