CN114881561A - Commodity circulation industry-based remote online monitoring and management cloud platform for freight vehicles - Google Patents
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Abstract
The invention discloses a remote online monitoring and management cloud platform for freight vehicles based on the logistics industry, which comprises: the system comprises a goods transport company basic information acquisition module, a vehicle and personnel information acquisition module, a goods transport order distribution module, a goods transport vehicle entrance and exit monitoring module, a maintenance vehicle display and a storage database, wherein an optimal influence coefficient is obtained through two aspects of comprehensive analysis of driver driving experience and driver fatigue index, and a vehicle maintenance coefficient is obtained through two aspects of comprehensive analysis of vehicle body abrasion degree and vehicle body dent index.
Description
Technical Field
The invention relates to the technical field of cargo transportation, in particular to a remote online monitoring and management cloud platform for cargo transportation vehicles based on the logistics industry.
Background
The modern logistics industry, as a new composite industry, develops rapidly in the world and becomes a basic industry of the global people economy and a backbone industry of the service industry. At present, the logistics industry is still in the accumulation phase, and with the massive application of information technology and the rise of electronic commerce, more and more cargo transportation modes mainly based on trucks appear.
At present, the management of freight vehicles lacks intelligent control and management, so the current freight vehicle management platform has the following disadvantages:
current cargo vehicle management platform has certain defect in managing the distribution of freight train driver, not only lack and carry out the analysis to driver's experience, still lack and carry out the analysis to driver's fatigue index, lead to having the problem of considering incompleteness when distributing freight train driver, cause the irrational nature easily, simultaneously, it can lead to the increase of freight train driver potential safety hazard in the driving process more to ignore freight train driver's fatigue index, make accident rate promote greatly.
The current freight vehicle management platform has certain defect in the maintenance management of the freight vehicles, not only ignores the analysis of the abrasion degree of the bodies of the freight vehicles, but also ignores the analysis of the sinking indexes of the bodies of the freight vehicles, so that the vehicle maintenance coefficient can not be obtained as reliable reference data, and further the freight vehicles can not be maintained and adjusted in time, the service efficiency of the freight vehicles is reduced, certain economic loss is caused, and meanwhile, instability is caused when the freight vehicles run.
Disclosure of Invention
In order to overcome the defects in the background art, the embodiment of the invention provides a remote online monitoring and management cloud platform for freight vehicles based on the logistics industry, which can effectively solve the problems related to the background art.
The purpose of the invention can be realized by the following technical scheme:
a long-range on-line monitoring management cloud platform of freight vehicle based on commodity circulation trade includes:
the system comprises a basic information acquisition module of a freight carrier, a basic information acquisition module of the freight carrier, a basic information processing module of the freight carrier, and a basic information processing module of the freight carrier, wherein the basic information comprises the quantity of freight vehicles corresponding to each vehicle type and the number of the freight drivers corresponding to each vehicle type and the freight carrier;
the vehicle and personnel information acquisition module is used for monitoring the use state of each truck vehicle corresponding to each vehicle type and the working state of each truck driver corresponding to each vehicle type in real time through the intelligent camera, acquiring the rest duration of each free truck driver corresponding to each vehicle type, and further acquiring a set of free truck vehicles corresponding to each vehicle type and a set of free truck drivers corresponding to each vehicle type;
the system comprises a cargo transportation order information acquisition module, a cargo transportation order information acquisition module and a cargo transportation information processing module, wherein the cargo transportation order information acquisition module is used for acquiring current cargo transportation order information, and the cargo transportation order information comprises a cargo volume and a cargo transportation place;
the goods transportation order distribution module is used for acquiring a target transportation vehicle number and a target transportation truck driver number distributed by the current goods transportation order from a free truck set corresponding to each vehicle type and a free truck driver set corresponding to each vehicle type, and further carrying out goods transportation work notification on the target transportation truck driver;
the system comprises a truck vehicle entrance and exit monitoring module, a monitoring module and a monitoring module, wherein the truck vehicle entrance and exit monitoring module is used for counting the number of distributed truck vehicles in a set time period, acquiring an entrance image and an exit image of each distributed truck vehicle through an intelligent camera to obtain a body entrance image and a body exit image corresponding to each distributed truck vehicle, analyzing a vehicle maintenance coefficient corresponding to each distributed truck vehicle according to the body entrance image and the body exit image, counting the number of vehicles needing maintenance according to the vehicle maintenance coefficient, and extracting the number of each vehicle needing maintenance;
the maintenance vehicle display is used for displaying the number of vehicles needing to be maintained and the corresponding serial numbers;
the storage database is used for storing the corresponding ages and driving ages of truck drivers corresponding to the truck types, the corresponding nuclear cargo volumes of the truck types, the driving mileage and driving duration of the truck drivers corresponding to the truck types, the body surface areas of the truck vehicles corresponding to the truck types, the suggested rest duration corresponding to the ages of the truck drivers and the contact modes of the truck drivers corresponding to the truck types.
Preferably, the method for numbering the freight cars corresponding to the respective types of cars and the freight car drivers corresponding to the respective types of cars includes the following steps: marking the truck vehicles corresponding to all the vehicle types as A kc ，A kc The model is expressed as that the kth model corresponds to the c-th truck vehicle, c is 1,2, the kr ，B kr The model denoted as kth corresponds to the r-th truck driver, and r is 1, 2.
Preferably, the usage status of the truck vehicle includes use and leisure, and the working status of the truck driver includes delivery and leisure.
Preferably, the freight order distribution module includes a freight target transport vehicle distribution unit, a freight target transport truck driver distribution unit, and a target transport truck driver notification unit.
Preferably, the cargo target transportation vehicle allocation unit is configured to obtain a target transportation vehicle number allocated in the current cargo transportation order, and the specific analysis is as follows:
extracting the cargo volume from the current cargo transportation order information, comparing the cargo volume with the nuclear cargo volume corresponding to each vehicle type stored in the storage database, further analyzing the vehicle type with the matched cargo volume, and recording the vehicle type with the matched cargo volume as the specified vehicle type;
and acquiring an idle truck vehicle set corresponding to the specified vehicle type from the idle truck vehicle set corresponding to each vehicle type based on the specified vehicle type, recording the idle truck vehicle corresponding to the specified vehicle type as a target transport vehicle, and extracting a number corresponding to the target transport vehicle.
Preferably, the driver allocation unit of the target freight wagon is configured to obtain a driver number of the target freight wagon allocated in the current freight order, and the specific analysis is as follows:
based on the appointed vehicle type, acquiring the set of leisure truck drivers corresponding to the appointed vehicle type from the set of leisure truck drivers corresponding to each vehicle type, andthe method comprises the steps of calculating driving experience indexes of all leisure truck drivers in a set of leisure truck drivers corresponding to a specified vehicle type, wherein the specific calculation formula is
ηB′ r Representing driving experience index, B ', corresponding to the r-th leisure van driver for a specified vehicle type' r L、B′ r T is respectively expressed as the driving mileage and the driving time of the r-th leisure truck driver corresponding to the specified vehicle type, L ' and T ' are respectively expressed as the reference driving mileage and the reference driving time of the driver, and B ' r g is the driving age of the r-th leisure van driver corresponding to the specified vehicle type, and a1, a2 and a3 are respectively expressed as influence factors corresponding to the driving mileage, the driving duration and the driving age;
extracting the rest duration of each leisure van driver corresponding to the appointed vehicle type from the rest duration of each leisure van driver corresponding to each vehicle type, and calculating the fatigue index of each leisure van driver corresponding to the appointed vehicle type, wherein the specific calculation formula is
Representing fatigue index, B ', for the r-th leisure van driver for a given model' r t represents the rest time length of the r-th leisure truck driver corresponding to the specified vehicle type, b represents the correction coefficient corresponding to the rest time length, and rjt' represents the suggested rest time length corresponding to the age of the r-th truck driver;
based on the driving experience indexes of all leisure goods vehicle drivers corresponding to the appointed vehicle type and the fatigue indexes of all leisure goods vehicle drivers corresponding to the appointed vehicle type, the optimal influence coefficient of all leisure goods vehicle drivers corresponding to the appointed vehicle type is obtained through comprehensive analysis, and the specific calculation formula is
σB′ r Showing preferred images of the r-th leisure van driver for a given modelThe response coefficients e1 and e2 are respectively expressed as weight factors corresponding to driving experience indexes and fatigue indexes;
and sequencing the preferred influence coefficients of the designated vehicle type corresponding to the drivers of the leisure trucks from large to small, screening out the corresponding drivers of the leisure trucks with the highest preferred influence coefficients, recording the drivers as the drivers of the target transport trucks, and extracting the numbers of the drivers of the target transport trucks.
Preferably, the target transport wagon driver notification unit is configured to match the number of the target transport wagon driver corresponding to the specified vehicle type with the contact information of each wagon driver corresponding to each vehicle type in the storage database, so as to obtain the contact information of the target transport wagon driver, and further send the number of the target transport vehicle to the target transport wagon driver, so that the target transport wagon driver performs the transportation work of the current cargo transportation order.
Preferably, the analysis of the vehicle maintenance coefficients corresponding to the respective assigned trucks is as follows:
sequentially numbering the allocated truck vehicles according to allocation time, wherein the allocated truck vehicles are numbered as 1,2, a.
Comparing the vehicle body entrance image and the vehicle body exit image corresponding to each distributed wagon vehicle one by one, counting the wear quantity of each distributed vehicle body and the recess quantity of each distributed vehicle body, and acquiring the wear area corresponding to each wear part of each distributed vehicle body and the recess area and the recess depth corresponding to each recess part of each distributed vehicle body;
the degree of wear of the corresponding vehicle of each distributed truck vehicle is calculated by the specific calculation formula
γ f Expressed as the degree of body wear, f, of the f-th allocated wagon n m represents the corresponding wear area of the nth truck body in the f-th allocated truck vehicle, n represents the number of the truck body wear, and n is 1, 2.
Calculating the body depression index of each assigned truck vehicle by the specific calculation formula
μ f Expressed as the corresponding body depression index, f, of the f-th allocated van vehicle q m' is expressed as the body depression area corresponding to the qth depression in the f-th allocated wagon vehicle, f q h is the body depression depth of the q-th depression in the f-th assigned truck vehicle, q is the number of the depression, q is 1, 2.. the p, fH is the allowable body depression depth corresponding to the f-th assigned truck vehicle, and c1 and c2 are respectively the influence factors corresponding to the body depression area and the body depression depth;
calculating the vehicle maintenance coefficient corresponding to each distributed wagon vehicle according to the vehicle body abrasion degree and the vehicle body depression index of each distributed wagon vehicle, wherein the specific calculation formula is
ζ f The f-th assigned truck vehicle corresponds to the vehicle maintenance coefficient, and d1 and d2 respectively correspond to the vehicle body abrasion degree and the vehicle body depression index.
Preferably, the statistics of the vehicles to be maintained according to the vehicle maintenance coefficients includes:
and comparing the corresponding maintenance coefficient of each distributed truck vehicle with a preset vehicle maintenance threshold value, if the corresponding maintenance coefficient of a certain distributed truck vehicle is greater than the preset vehicle maintenance threshold value, recording the corresponding maintenance coefficient of the distributed truck vehicle as a vehicle needing maintenance, extracting the number of the vehicle needing maintenance, and further counting the number of the vehicles needing maintenance.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
the invention effectively solves the defect that the current freight vehicle management platform can not realize the analysis of the optimal influence coefficient, obtains the optimal influence coefficient from the comprehensive analysis of the driving experience index and the fatigue index of the driver, makes up the defect that the analysis of the driving experience and the fatigue index of the driver does not exist in the current technology, avoids the irrationality caused by the incomplete consideration when the truck drivers are distributed, ensures that the analysis of the fatigue index of the truck drivers has more rigor and scientific foundation and effectively reduces the potential safety hazard of the truck drivers in the driving process.
The invention effectively solves the defect that the current freight transport vehicle management platform can not analyze the vehicle maintenance coefficient, obtains the vehicle maintenance coefficient by comprehensively analyzing the two aspects of the vehicle body abrasion degree and the vehicle body depression index, overcomes the defect that the analysis of the vehicle body abrasion degree and the vehicle body depression index is not generated in the current technology, provides a powerful data base for vehicle maintenance, realizes the timely maintenance and adjustment of the freight transport vehicle, avoids the reduction of the utilization rate of the freight transport vehicle, reduces the economic loss to a great extent, and simultaneously ensures the running stability and safety of the freight transport vehicle.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a schematic diagram of the system module connection according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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, the invention provides a logistics industry-based remote online monitoring and management cloud platform for freight vehicles, which comprises a basic information acquisition module for a freight carrier, a vehicle and personnel information acquisition module, a freight order distribution module, a freight vehicle entrance and exit monitoring module, a maintenance vehicle display and a storage database.
The system comprises a goods transportation company basic information acquisition module, a vehicle and personnel information acquisition module, a goods transportation order distribution module, a goods vehicle access monitoring module, a maintenance vehicle display and a storage database, wherein the goods transportation company basic information acquisition module is connected with the vehicle and personnel information acquisition module, the vehicle and personnel information acquisition module is connected with the goods transportation order distribution module, the goods transportation order distribution module is connected with the goods vehicle access monitoring module, the goods vehicle access monitoring module is connected with the maintenance vehicle display, and the storage database is respectively connected with the goods transportation order distribution module and the goods vehicle access monitoring module.
The basic information acquisition module of the freight transport company is used for acquiring the basic information of the freight transport company, wherein the basic information comprises the quantity of the freight vehicles corresponding to all the vehicle types and the quantity of the freight drivers corresponding to all the vehicle types, and meanwhile, the freight vehicles corresponding to all the vehicle types and the freight drivers corresponding to all the vehicle types are numbered.
Preferably, the method for numbering the freight cars corresponding to the respective types of cars and the freight car drivers corresponding to the respective types of cars includes the following steps: marking the truck vehicles corresponding to all the vehicle types as A kc ，A kc The model is expressed as that the kth model corresponds to the c-th truck vehicle, c is 1,2, the kr ，B kr The kth model is shown to correspond to the r-th truck driver, and r is 1, 2.
The vehicle and personnel information acquisition module is used for monitoring the use state of each truck vehicle corresponding to each vehicle type and the working state of each truck driver corresponding to each vehicle type in real time through the intelligent camera, acquiring the rest duration of each vehicle type corresponding to each leisure truck driver from the use state, and further acquiring a set of free truck vehicles corresponding to each vehicle type and a set of leisure truck drivers corresponding to each vehicle type.
Preferably, the usage status of the truck vehicle includes use and leisure, and the working status of the truck driver includes delivery and leisure.
It should be noted that the obtaining of the rest duration of each leisure van driver corresponding to each vehicle type in the invention is a powerful data support for subsequently obtaining the fatigue index corresponding to each leisure van driver, so that the analysis result is clearer, more accurate and more reliable.
The goods transportation order information acquisition module is used for acquiring current goods transportation order information, and the goods transportation order information comprises a goods volume and a goods transportation place.
Preferably, the freight order distribution module includes a freight target transport vehicle distribution unit, a freight target transport truck driver distribution unit, and a target transport truck driver notification unit.
Preferably, the cargo target transportation vehicle allocation unit is configured to obtain a target transportation vehicle number allocated in the current cargo transportation order, and the specific analysis is as follows:
extracting the cargo volume from the current cargo transportation order information, comparing the cargo volume with the nuclear cargo volume corresponding to each vehicle type stored in the storage database, further analyzing the vehicle type with the matched cargo volume, and recording the vehicle type with the matched cargo volume as the specified vehicle type;
and acquiring an idle truck vehicle set corresponding to the specified vehicle type from the idle truck vehicle set corresponding to each vehicle type based on the specified vehicle type, recording the idle truck vehicle corresponding to the specified vehicle type as a target transport vehicle, and extracting a number corresponding to the target transport vehicle.
It should be noted that, in the embodiment of the present invention, the idle wagon vehicle corresponding to the specified vehicle type is regarded as the target transportation vehicle, and specifically, the idle wagon vehicle is: if the number of the idle wagon vehicles corresponding to the specified vehicle type is larger than 1, acquiring the residual oil quantity of the current oil tank of each idle wagon vehicle corresponding to the specified vehicle type, and screening the idle wagon vehicle corresponding to the specified vehicle type with the largest residual oil quantity in the current oil tank as a target transport vehicle; and if the number of the idle truck vehicles corresponding to the specified vehicle type is equal to 1, recording the idle truck vehicles corresponding to the specified vehicle type as target transport vehicles.
Preferably, the driver allocation unit of the target freight wagon is configured to obtain a driver number of the target freight wagon allocated in the current freight order, and the specific analysis is as follows:
based on the appointed vehicle type, acquiring the set of leisure truck drivers corresponding to the appointed vehicle type from the set of leisure truck drivers corresponding to each vehicle type, and calculating driving experience indexes of all the leisure truck drivers in the set of leisure truck drivers corresponding to the appointed vehicle type, wherein the specific calculation formula is
ηB′ r Representing driving experience index, B ', corresponding to the r-th leisure van driver for a specified vehicle type' r L、B′ r T is respectively expressed as the driving mileage and the driving time of the r-th leisure truck driver corresponding to the specified vehicle type, L ' and T ' are respectively expressed as the reference driving mileage and the reference driving time of the driver, and B ' r g is the driving age of the r-th leisure van driver corresponding to the specified vehicle type, and a1, a2 and a3 are respectively expressed as influence factors corresponding to the driving mileage, the driving duration and the driving age;
extracting the rest duration of each leisure van driver corresponding to the appointed vehicle type from the rest duration of each leisure van driver corresponding to each vehicle type, and calculating the fatigue index of each leisure van driver corresponding to the appointed vehicle type, wherein the specific calculation formula is
Expressed as fatigue index, B 'of the assigned model corresponding to the r-th leisure lorry driver' r t represents the rest time length of the r-th leisure truck driver corresponding to the specified vehicle type, b represents the correction coefficient corresponding to the rest time length, and rjt' represents the suggested rest time length corresponding to the age of the r-th truck driver;
driving experience index and index corresponding to each leisure truck driver based on specified vehicle typeThe fatigue indexes of the drivers of the leisure goods vehicles corresponding to the specified vehicle type are comprehensively analyzed to obtain the optimal influence coefficient of the drivers of the leisure goods vehicles corresponding to the specified vehicle type, and the specific calculation formula is
σB′ r Expressing the preferred influence coefficient of the r-th leisure van driver corresponding to the specified vehicle type, wherein e1 and e2 respectively express weight factors corresponding to driving experience indexes and fatigue indexes;
and sequencing the preferred influence coefficients of the designated vehicle type corresponding to the drivers of the leisure trucks from large to small, screening out the corresponding drivers of the leisure trucks with the highest preferred influence coefficients, recording the drivers as the drivers of the target transport trucks, and extracting the numbers of the drivers of the target transport trucks.
Preferably, the target transport wagon driver notification unit is configured to match the number of the target transport wagon driver corresponding to the specified vehicle type with the contact information of each wagon driver corresponding to each vehicle type in the storage database, so as to obtain the contact information of the target transport wagon driver, and further send the number of the target transport vehicle to the target transport wagon driver, so that the target transport wagon driver performs the transportation work of the current cargo transportation order.
It should be noted that the invention effectively solves the problem that the current freight vehicle management platform cannot analyze the optimal influence coefficient, obtains the optimal influence coefficient by comprehensively analyzing the driver driving experience index and the driver fatigue index, overcomes the defect that the analysis of the driver driving experience and the driver fatigue index is not generated in the current technology, avoids the irrationality caused by the incomplete consideration when distributing the truck drivers, ensures that the analysis of the truck driver fatigue index has more rigorous and scientific evidences, and effectively reduces the potential safety hazard of the truck drivers in the driving process.
The truck vehicle entrance and exit monitoring module is used for counting the number of the distributed truck vehicles in a set time period, acquiring the entrance and exit images of each distributed truck vehicle through an intelligent camera to obtain the entrance image and the exit image of the truck body corresponding to each distributed truck vehicle, analyzing the maintenance coefficient of the truck corresponding to each distributed truck vehicle according to the entrance image and the exit image of the truck body, counting the number of the vehicles needing to be maintained according to the maintenance coefficient of the truck, and extracting the number of the vehicles needing to be maintained.
Preferably, the analysis of the vehicle maintenance coefficients corresponding to the respective assigned trucks is as follows:
sequentially numbering the allocated truck vehicles according to allocation time, wherein the allocated truck vehicles are numbered as 1,2, a.
Comparing the vehicle body entrance image and the vehicle body exit image corresponding to each distributed wagon vehicle one by one, counting the wear quantity of each distributed vehicle body and the recess quantity of each distributed vehicle body, and acquiring the wear area corresponding to each wear part of each distributed vehicle body and the recess area and the recess depth corresponding to each recess part of each distributed vehicle body;
the degree of wear of the corresponding vehicle of each distributed truck vehicle is calculated by the specific calculation formula
γ f Expressed as the degree of body wear, f, of the f-th allocated wagon n m represents the corresponding wear area of the nth truck body in the f-th allocated truck vehicle, n represents the number of the truck body wear, and n is 1, 2.
Calculating the body depression index of each assigned truck vehicle by the specific calculation formula
μ f Expressed as the corresponding body sag index, f, for the f-th assigned van vehicle q m' is expressed as the body depression area corresponding to the qth depression in the f-th allocated van vehicle, f q h denotes the body depression depth of the qth depression in the f-th allocated wagon, q denotes the depression number, q is 1,2Showing the allowable vehicle body depression depth corresponding to the f-th distributed wagon vehicle, wherein c1 and c2 are respectively shown as influence factors corresponding to the vehicle body depression area and the vehicle body depression depth;
calculating the vehicle maintenance coefficient corresponding to each distributed wagon vehicle according to the vehicle body abrasion degree and the vehicle body depression index of each distributed wagon vehicle, wherein the specific calculation formula is
ζ f The f-th assigned truck vehicle corresponds to the vehicle maintenance coefficient, and d1 and d2 respectively correspond to the vehicle body abrasion degree and the vehicle body depression index.
The invention effectively solves the defect that the current freight transport vehicle management platform can not analyze the vehicle maintenance coefficient, obtains the vehicle maintenance coefficient through comprehensive analysis of the vehicle body abrasion degree and the vehicle body depression index, overcomes the defect that the analysis of the vehicle body abrasion degree and the vehicle body depression index is not generated in the prior art, provides a powerful data base for vehicle maintenance, realizes the timely maintenance and adjustment of the freight transport vehicle, avoids the reduction of the freight transport vehicle utilization rate, reduces the economic loss to a great extent, and simultaneously ensures the running stability and safety of the freight transport vehicle.
Preferably, the statistics of the vehicles to be maintained according to the vehicle maintenance coefficients includes:
and comparing the corresponding maintenance coefficient of each distributed truck vehicle with a preset vehicle maintenance threshold value, recording the corresponding maintenance coefficient of the distributed truck vehicle as a vehicle needing to be maintained if the corresponding maintenance coefficient of a certain distributed truck vehicle is greater than the preset vehicle maintenance threshold value, simultaneously extracting the number of the vehicle needing to be maintained, and further counting the number of the vehicles needing to be maintained.
And the maintenance vehicle display is used for displaying the number of vehicles needing to be maintained and the corresponding numbers.
It should be noted that, in this embodiment, the number of each vehicle to be maintained and the corresponding number are displayed through the maintenance vehicle display, so that the management personnel of the freight transportation company can know the number of the vehicles to be maintained and the corresponding number in time, and implement remote dynamic guidance.
The storage database is used for storing the corresponding ages and driving ages of truck drivers corresponding to the truck types, the corresponding nuclear cargo volumes of the truck types, the driving mileage and driving duration of the truck drivers corresponding to the truck types, the body surface areas of the truck vehicles corresponding to the truck types, the suggested rest duration corresponding to the ages of the truck drivers and the contact modes of the truck drivers corresponding to the truck types.
The foregoing is merely illustrative and explanatory of the present invention and various modifications, additions or substitutions may be made to the specific embodiments described by those skilled in the art without departing from the scope of the invention as defined in the accompanying claims.
Claims (9)
1. The utility model provides a long-range on-line monitoring management cloud platform of freight vehicle based on commodity circulation trade which characterized in that includes:
the system comprises a basic information acquisition module of a freight carrier, a basic information acquisition module of the freight carrier, a basic information processing module of the freight carrier, and a basic information processing module of the freight carrier, wherein the basic information comprises the quantity of freight vehicles corresponding to each vehicle type and the number of the freight drivers corresponding to each vehicle type and the freight carrier;
the vehicle and personnel information acquisition module is used for monitoring the use state of each truck vehicle corresponding to each vehicle type and the working state of each truck driver corresponding to each vehicle type in real time through the intelligent camera, acquiring the rest duration of each free truck driver corresponding to each vehicle type, and further acquiring a set of free truck vehicles corresponding to each vehicle type and a set of free truck drivers corresponding to each vehicle type;
the system comprises a cargo transportation order information acquisition module, a cargo transportation order information acquisition module and a cargo transportation information processing module, wherein the cargo transportation order information acquisition module is used for acquiring current cargo transportation order information, and the cargo transportation order information comprises a cargo volume and a cargo transportation place;
the goods transportation order distribution module is used for acquiring a target transportation vehicle number and a target transportation truck driver number distributed by the current goods transportation order from a free truck set corresponding to each vehicle type and a free truck driver set corresponding to each vehicle type, and further carrying out goods transportation work notification on the target transportation truck driver;
the system comprises a truck vehicle entrance and exit monitoring module, a monitoring module and a monitoring module, wherein the truck vehicle entrance and exit monitoring module is used for counting the number of distributed truck vehicles in a set time period, acquiring an entrance image and an exit image of each distributed truck vehicle through an intelligent camera to obtain a body entrance image and a body exit image corresponding to each distributed truck vehicle, analyzing a vehicle maintenance coefficient corresponding to each distributed truck vehicle according to the body entrance image and the body exit image, counting the number of vehicles needing maintenance according to the vehicle maintenance coefficient, and extracting the number of each vehicle needing maintenance;
the maintenance vehicle display is used for displaying the number of vehicles needing to be maintained and the corresponding serial numbers;
the storage database is used for storing the corresponding ages and driving ages of truck drivers corresponding to the truck types, the corresponding nuclear cargo volumes of the truck types, the driving mileage and driving duration of the truck drivers corresponding to the truck types, the body surface areas of the truck vehicles corresponding to the truck types, the suggested rest duration corresponding to the ages of the truck drivers and the contact modes of the truck drivers corresponding to the truck types.
2. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform as claimed in claim 1, wherein: the method is characterized in that the freight vehicles corresponding to all the vehicle types and the freight drivers corresponding to all the vehicle types are numbered, and the method specifically comprises the following steps: marking the truck vehicles corresponding to all the vehicle types as A kc ，A kc The model is expressed as that the kth model corresponds to the c-th truck vehicle, c is 1,2, the kr ，B kr The kth model is shown to correspond to the r-th truck driver, and r is 1, 2.
3. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform as claimed in claim 1, wherein: the use status of the truck vehicle includes use and idle, and the working status of the truck driver includes delivery and leisure.
4. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform as claimed in claim 1, wherein: the goods transportation order distribution module comprises a goods target transportation vehicle distribution unit, a goods target transportation truck driver distribution unit and a target transportation truck driver notification unit.
5. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform of claim 4, wherein: the cargo target transport vehicle allocation unit is used for acquiring a target transport vehicle number allocated in the current cargo transport order, and the specific analysis is as follows:
extracting the cargo volume from the current cargo transportation order information, comparing the cargo volume with the nuclear cargo volume corresponding to each vehicle type stored in the storage database, further analyzing the vehicle type with the matched cargo volume, and recording the vehicle type with the matched cargo volume as the specified vehicle type;
and acquiring an idle truck vehicle set corresponding to the specified vehicle type from the idle truck vehicle set corresponding to each vehicle type based on the specified vehicle type, recording the idle truck vehicle corresponding to the specified vehicle type as a target transport vehicle, and extracting a number corresponding to the target transport vehicle.
6. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform of claim 4, wherein: the driver allocation unit of the target freight wagon is used for acquiring the number of the driver of the target freight wagon allocated in the current freight order, and the specific analysis is as follows:
based on the appointed vehicle type, acquiring the corresponding appointed vehicle type from the set of leisure truck drivers corresponding to each vehicle typeThe method comprises the steps of collecting leisure truck drivers and calculating driving experience indexes of all the leisure truck drivers in the collection of the leisure truck drivers corresponding to a specified vehicle type, wherein the specific calculation formula is
ηB′ r Representing driving experience index, B ', corresponding to the r-th leisure van driver for a specified vehicle type' r L、B′ r T is respectively expressed as the driving mileage and the driving time of the r-th leisure truck driver corresponding to the specified vehicle type, L ' and T ' are respectively expressed as the reference driving mileage and the reference driving time of the driver, and B ' r g is the driving age of the r-th leisure van driver corresponding to the specified vehicle type, and a1, a2 and a3 are respectively expressed as influence factors corresponding to the driving mileage, the driving duration and the driving age;
extracting the rest duration of each leisure van driver corresponding to the appointed vehicle type from the rest duration of each leisure van driver corresponding to each vehicle type, and calculating the fatigue index of each leisure van driver corresponding to the appointed vehicle type, wherein the specific calculation formula is
Representing fatigue index, B ', for the r-th leisure van driver for a given model' r t represents the rest time length of the r-th leisure truck driver corresponding to the specified vehicle type, b represents the correction coefficient corresponding to the rest time length, and rjt' represents the suggested rest time length corresponding to the age of the r-th truck driver;
based on the driving experience indexes of all leisure goods vehicle drivers corresponding to the appointed vehicle type and the fatigue indexes of all leisure goods vehicle drivers corresponding to the appointed vehicle type, the optimal influence coefficient of all leisure goods vehicle drivers corresponding to the appointed vehicle type is obtained through comprehensive analysis, and the specific calculation formula is
σB′ r Expressing the preferred influence coefficient of the r-th leisure van driver corresponding to the specified vehicle type, wherein e1 and e2 respectively express weight factors corresponding to driving experience indexes and fatigue indexes;
and sequencing the preferred influence coefficients of the designated vehicle type corresponding to the drivers of the leisure trucks from large to small, screening out the corresponding drivers of the leisure trucks with the highest preferred influence coefficients, recording the drivers as the drivers of the target transport trucks, and extracting the numbers of the drivers of the target transport trucks.
7. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform of claim 4, wherein: the target transport freight car driver notification unit is used for matching the serial number of the target transport freight car driver corresponding to the specified vehicle type with the contact way of each freight car driver corresponding to each vehicle type in the storage database, so that the contact way of the target transport freight car driver is obtained, the serial number of the target transport freight car is sent to the target transport freight car driver, and the target transport freight car driver carries out the transportation work of the current cargo transportation order.
8. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform as claimed in claim 1, wherein: the analysis of the vehicle maintenance coefficients corresponding to the distributed truck vehicles is specifically as follows:
sequentially numbering the allocated truck vehicles according to allocation time, wherein the allocated truck vehicles are numbered as 1,2, a.
Comparing the vehicle body entrance image and the vehicle body exit image corresponding to each distributed wagon vehicle one by one, counting the wear quantity of each distributed vehicle body and the recess quantity of each distributed vehicle body, and acquiring the wear area corresponding to each wear part of each distributed vehicle body and the recess area and the recess depth corresponding to each recess part of each distributed vehicle body;
the degree of wear of the corresponding vehicle of each distributed truck vehicle is calculated by the specific calculation formula
γ f Expressed as the degree of body wear, f, of the f-th allocated wagon n m represents the corresponding wear area of the nth truck body in the f-th allocated truck vehicle, n represents the number of the truck body wear, and n is 1, 2.
Calculating the body depression index of each assigned truck vehicle by the specific calculation formula
μ f Expressed as the corresponding body sag index, f, for the f-th assigned van vehicle q m' is expressed as the body depression area corresponding to the qth depression in the f-th allocated wagon vehicle, f q h is the body depression depth of the q-th depression in the f-th assigned truck vehicle, q is the number of the depression, q is 1, 2.. the p, fH is the allowable body depression depth corresponding to the f-th assigned truck vehicle, and c1 and c2 are respectively the influence factors corresponding to the body depression area and the body depression depth;
calculating the vehicle maintenance coefficient corresponding to each distributed wagon vehicle according to the vehicle body abrasion degree and the vehicle body depression index of each distributed wagon vehicle, wherein the specific calculation formula is
ζ f The f-th assigned truck vehicle corresponds to the vehicle maintenance coefficient, and d1 and d2 respectively correspond to the vehicle body abrasion degree and the vehicle body depression index.
9. The logistics industry-based cargo transportation vehicle remote online monitoring and management cloud platform as claimed in claim 1, wherein: the statistics of the vehicles needing to be maintained according to the vehicle maintenance coefficients specifically comprises the following steps:
and comparing the corresponding maintenance coefficient of each distributed truck vehicle with a preset vehicle maintenance threshold value, if the corresponding maintenance coefficient of a certain distributed truck vehicle is greater than the preset vehicle maintenance threshold value, recording the corresponding maintenance coefficient of the distributed truck vehicle as a vehicle needing maintenance, extracting the number of the vehicle needing maintenance, and further counting the number of the vehicles needing maintenance.
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