An Internet of Things-based intelligent management method and system for logistics engineering vehicles

Abstract

The present invention relates to an intelligent management method and system for logistics engineering vehicles based on the Internet of Things, belonging to the technical field of Internet of Things intelligent transportation management. Specifically, it relates to an intelligent management system for logistics engineering vehicles based on the Internet of Things, which includes a dispatching and monitoring center, a maintenance site, a control node, and a maintenance vehicle. The dispatching and monitoring center is configured as a central station, and the central station is equipped with a display screen. The display screen stores and configures a standard maintenance route that is combined and connected in series by the central station, the maintenance site, and the control node according to the actual distance. The standard maintenance route is used to provide a route reference for the maintenance vehicle, and the maintenance vehicle is equipped with a radio frequency identification electronic tag. By presetting the standard maintenance route and setting a radio frequency identification system at the interval nodes in the standard maintenance route, the present invention can realize information interaction and status update between the dispatching and monitoring center and each node, including automatically detecting alcohol and fatigue driving in the interval and interacting with dispatching instructions, thus realizing intelligent networked autonomous control of the line interval.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent traffic management of the Internet of Things, and in particular to an intelligent management method and system for logistics engineering vehicles based on the Internet of Things. Background Art

[0002] With the construction of the power grid, power logistics support has received great attention, and logistics work plays an important role in the normal operation of the power system. The substations in the power supply line are usually located in scattered areas, and the maintenance of substations is an important task for power supply companies. It is necessary to regularly or irregularly maintain and overhaul the substations in the area. The substation maintenance work requires very high professionalism and strict requirements for maintenance vehicles and personnel. A large number of maintenance vehicles are usually dispatched during a maintenance cycle. How to conduct overall dispatch and control of maintenance vehicles and personnel and improve dispatch capabilities in emergency situations is an urgent problem that needs to be solved. Therefore, there is an urgent need for a smart management method and system for logistics engineering vehicles based on the Internet of Things. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a logistics engineering vehicle intelligent management method and system based on the Internet of Things in view of the deficiencies in the prior art.

[0004] The technical problem to be solved by the present invention is achieved through the following technical solutions. The present invention discloses a method for intelligent management of logistics engineering vehicles based on Internet of Things data, including the following steps: step S1, inputting the location of each substation in the area into the computer of the dispatching and monitoring center, calculating the line distance between adjacent substations through map software and optimizing the overall shortest navigation route in which the substations are connected in series in sequence as a one-way standard maintenance route; step S2, installing road information stations at equal intervals between adjacent substations, marking the road information stations as control nodes and marking each substation as a maintenance site, numbering the control nodes and maintenance sites and displaying them in a On the large screen of the dispatching and monitoring center; Step S3, install RFID readers at road information stations and substations for reading vehicle locations and issuing dispatching instructions, and set up communication devices to communicate remotely with the dispatching and monitoring center; Step S4, each vehicle starts routine maintenance according to the standard maintenance route. When the dispatching and monitoring center receives a request for emergency repairs in the substation, the dispatching and monitoring center issues corresponding dispatching instructions according to the emergency level; Step S5, the selected dispatching vehicle receives the interruption instruction and executes the temporary work order task. After the temporary work order is completed, the dispatching vehicle resumes the regular maintenance mode and continues to perform the maintenance task along the standard maintenance route until the end of this maintenance cycle.

[0005] Further, step S1 includes the process of inputting the location of the dispatching and monitoring center into a computer as the starting point of the line for line calculation and optimization, and the dispatching and monitoring center is correspondingly configured as the central station in step S2 and displayed on the large screen of the dispatching and monitoring center.

[0006] Further, in step S4, it includes the process of the driver checking non-stop maintenance equipment at each control node and maintenance site on the way and the process of the driver's alcohol detection, face recognition matching and checking. The face recognition checking process includes the process of generating a virtual label using face recognition information and recording the driving duration information into the virtual label.

[0007] Further, the dispatching instruction modes in step S4 include: (1) Emergency repair mode, which preferentially allocates the vehicles closest to the target substation building, including vehicles going in the same direction, in the opposite direction, at the station and on the way, to rush to the target substation building for repair; (2) Non-emergency repair mode, which preferentially allocates the vehicles going in the same direction and on the way closest to the target substation building to rush to the target substation building for repair.

[0008] Further, the emergency repair mode includes identifying and calculating by the dispatching and monitoring center the two control nodes with pre-arriving vehicles on the way and one maintenance site with vehicles at the station that are the closest in actual navigation distance, and marking the corresponding vehicles as candidate vehicles. At the same time, it instructs the vehicles at the station to immediately start driving along the shortest navigation route through the electronic label. The dispatching and monitoring center monitors and records the driving states of the three candidate vehicles and calculates and selects one vehicle with the optimal actual navigation distance.

[0009] Further, the process of the dispatching and monitoring center calculating and selecting one vehicle with the optimal actual navigation distance includes selecting the vehicle that arrives at the corresponding control node or maintenance site first among the two vehicles on the way, and directly calculating and comparing the shortest navigation route distances by starting the communication positioning terminals of this vehicle and another original candidate vehicle at the station when it arrives, and selecting the vehicle with the shortest navigation route distance as the emergency repair vehicle.

[0010] The present invention also discloses an intelligent management system for logistics engineering vehicles based on the Internet of Things, including a dispatching and monitoring center, a maintenance site, a control node and a maintenance vehicle. The dispatching and monitoring center is configured as the central station. The central station is provided with a display large screen. The display large screen stores and configures a standard maintenance line combined and connected in series by the central station, the maintenance site and the control node according to the actual distance. The standard maintenance line is used to provide a route reference for the maintenance vehicle. The maintenance vehicle is provided with a radio frequency identification electronic tag.

[0011] Further, the maintenance site is configured to be the actual location of each substation building, and the control node is configured to be a road information site equally spaced between adjacent maintenance sites on the actual standard maintenance line. Both the maintenance site and the control node are equipped with radio frequency identification (RFID) readers and writers, which are used to read and write the RFID tag information of the maintenance vehicle without stopping the vehicle.

[0012] Further, the maintenance vehicle is equipped with a vehicle data management system, which is connected to the RFID tag. The vehicle data management system includes a level reader and writer, a sensing data system, a navigation database, and a storage center. The level reader and writer is used to read the level tags on the maintenance equipment inside the vehicle. The sensing data system is used to receive the sensing information of the vehicle driver and generate virtual tags. The navigation database is connected to a communication positioning terminal and a cloud computing center.

[0013] Further, the sensing data system includes a head recognition helmet, which is equipped with a camera and an alcohol detector. The camera can be used to confirm the driver's identity and the matching information of the steering wheel position at the same time. The alcohol detector is connected to the head recognition helmet through a rotating rod and is configured to start working at a specified rotating position.

[0014] The present invention has the following advantages compared with the prior art:

[0015] (1) By presetting a standard maintenance line and setting up an RFID system at the interval nodes on the standard maintenance line, the present invention can realize the information interaction and status update between the dispatching and monitoring center and each node, including automatically performing interval alcohol detection, fatigue driving detection, and dispatching instruction interaction, thus realizing the intelligent networked autonomous control of the line interval.

[0016] (2) By using the node dispatching method, the present invention can make full use of the preset line and position information, reduce the dependence on direct communication, and avoid problems such as inability to dispatch and emergency disposal in a timely manner due to poor signal areas.

[0017] (3) The present invention adopts three working modes, including a regular maintenance mode, an emergency repair mode, and a non-emergency repair mode, fully considering the efficiency and cost of the dispatching process, and realizing distance judgment for vehicle searching and optimal navigation route calculation through automatic matching of the dispatching mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a schematic diagram of the dispatching principle of the whole of the present invention in the emergency repair mode;

[0019] Figure 2 is a schematic diagram of the communication connection method of the present invention;

[0020] Figure 3It is the composition structure diagram of the vehicle data management system for maintaining the vehicle 3 of the present invention;

[0021] 1 - Central station, 2x - Control node, 2y - Maintenance site, 3 - Maintenance vehicle. Detailed implementation manners

[0022] As Figures 1-3 shown, the present invention also discloses an intelligent management system for logistics engineering vehicles based on the Internet of Things, including a dispatching and monitoring center, a maintenance site 2y, a control node 2x, and a maintenance vehicle 3. The dispatching and monitoring center is configured as the central station 1. Specifically, the maintenance site 2y is configured as the actual positions of each substation building. The control node 2x is configured as a road information site evenly arranged at equal intervals between adjacent maintenance sites 2y in the actual standard maintenance line. Since the distances between actual substation buildings are not equal, it is necessary to conduct on-site line mapping and set a number of road information sites approximately at equal intervals between adjacent substation buildings as virtual control nodes 2x. Therefore, in the finally formed standard maintenance line, the number of control nodes 2x between adjacent maintenance sites 2y is not the same. Radio frequency identification (RFID) readers / writers are provided at both the maintenance site 2y and the control node 2x. Through the RFID readers / writers, the RFID electronic tag information of the maintenance vehicle 3 can be read and written without stopping. When the maintenance vehicle 3 enters the specified identification area, information interaction transmission and status update occur.

[0023] The central station 1 is provided with a display screen. The display screen stores and configures a standard maintenance line combined and connected in series by the central station 1, the maintenance site 2y, and the control node 2x according to the actual distance. The standard maintenance line is used to provide a route reference for the maintenance vehicle 3. The maintenance vehicle 3 is provided with an RFID electronic tag. The maintenance vehicle 3 is provided with a vehicle data management system. The vehicle data management system is connected to the RFID electronic tag. The vehicle data management system includes a level reader / writer, a sensing data system, a navigation database, and a storage center. The level reader / writer is used to read the level tags on the maintenance equipment in the vehicle.

[0024] The sensing data system is used to receive the sensing information of the vehicle driver and generate virtual tags. The sensing data system includes an avatar recognition helmet, which is equipped with a camera and an alcohol detector. The camera can be used to simultaneously confirm the driver's identity and the steering wheel position matching information. The alcohol detector is connected to the avatar recognition helmet through a rotating rod and is configured to start working at a specified rotation position. For example, the normal position is on the helmet surface, and it flips to the corresponding mouth position of the helmet during detection, so as to ensure that the detected person is the driver and exclude the substitution detection by fellow passengers. In actual application, the start sequence of the driver's alcohol detection and face recognition can be set through the program, so as to further prevent others from substituting for the detection. The virtual tags generated corresponding to the driver are given information such as whether the driver is drunk driving and whether the driver is fatigued driving. The system only needs to directly prompt the driver to perform corresponding operations and verifications through the electronic tag near the control node 2x or the maintenance site 2y, without having to stop or get off the vehicle, and can transmit accurate information to the dispatching and monitoring center. The navigation database is connected to a communication positioning terminal and a cloud computing center. The communication positioning terminal and the cloud computing center are only turned on and used when an emergency repair mode dispatch is required to ensure accurate and complex navigation route calculations. Specifically, the communication positioning terminal can be controlled to start running through the vehicle-mounted satellite antenna and remains in a sleep state in the normal maintenance mode. The dispatching of the vehicle can be efficiently controlled for the controllable route section only through the radio frequency identification system, i.e., RFID.

[0025] Based on the above system, the following further provides an intelligent management method for logistics engineering vehicles based on Internet of Things data to more clearly express the principle of the present invention. The method may include the following steps. Step S1, first input the positions of each substation building in the area into the computer of the dispatching and monitoring center, calculate the line distance between adjacent substation buildings through map software, and optimize to obtain the overall shortest navigation line in series of substation buildings as the one-way standard maintenance line. This step includes the process of inputting the position of the dispatching and monitoring center into the computer as the starting point of the line for line calculation and optimization. The dispatching and monitoring center is correspondingly marked as the central station 1 in step S2 and displayed on the large screen of the dispatching and monitoring center, so as to form a virtual line map formed by the maintenance site 2y, the control node 2x, and the central station 1, where the actual distance between any adjacent maintenance site 2y and control node 2x or the actual distance between any adjacent control nodes 2x is equal;

[0026] Step S2, install road information sites at equal intervals between adjacent substation buildings, mark the road information sites as control nodes 2x and mark each substation building as a maintenance site 2y, number the control nodes 2x and the maintenance sites 2y and display them on the large screen of the dispatching and monitoring center;

[0027] Step S3, install RFID readers for reading vehicle positions and issuing dispatching instructions at road information stations and substation buildings, and set up communication devices to conduct remote communication with the dispatching and monitoring center. The communication device is a fixed-power radio communication;

[0028] Step S4, each vehicle departs for routine maintenance according to the standard maintenance route. When the dispatching and monitoring center receives a rush repair request from a substation building, the dispatching and monitoring center issues corresponding dispatching instructions according to the emergency level. This step also includes the process of the driver checking non-stop maintenance equipment at each control node 2x and maintenance site 2y on the way, as well as the process of the driver's alcohol detection, face recognition matching and checking. The face recognition checking process includes the process of generating a virtual tag using face recognition information and recording the driving duration information into the virtual tag;

[0029] Step S5, the selected dispatching vehicle receives the interruption instruction and executes the temporary work order task. After the temporary work order is completed, the dispatching vehicle resumes the routine maintenance mode and continues to execute the maintenance task along the standard maintenance route until the end of this maintenance cycle.

[0030] The following further describes the dispatching instruction mode in Step S4 above, including the following two rush repair modes: (1) Emergency rush repair mode, preferentially allocate the vehicle closest to the target substation building, including vehicles going forward, backward, at the station and on the way, to rush to the target substation building for rush repair; (2) Non-emergency rush repair mode, preferentially allocate the vehicle going forward and on the way closest to the target substation building to rush to the target substation building for rush repair.

[0031] In (1) the emergency rush repair mode, the specific information processing method adopted is to identify and calculate, through the dispatching and monitoring center, two control nodes 2x with pre-arriving vehicles on the way and one maintenance site 2y with vehicles at the station that are the closest in actual navigation distance, and mark the corresponding vehicles as candidate vehicles. At the same time, through the electronic tag instruction, the vehicle c at the station immediately starts to drive along the shortest navigation route. The dispatching and monitoring center monitors and records the driving status of the three candidate vehicles and calculates and selects an optimal vehicle with the shortest actual navigation distance. The calculation and selection process is as follows: Select the vehicle that arrives at the corresponding control node 2x or maintenance site 2y first among the two vehicles on the way a and b, and directly calculate and compare the shortest navigation route distance by starting the communication positioning terminals of the vehicle and the other original candidate vehicle at the station when arriving. That is, start the on-vehicle satellite antennas of the two candidate vehicles when arriving, and select the vehicle with the shortest navigation route distance as the emergency rush repair vehicle through the final direct line distance calculation.

[0032] In summary, the present invention realizes a conventional maintenance mode of status control through node intervals by pre-configuring standard maintenance lines. The node scheduling method can make full use of the preset line and position information, saving the location addressing and navigation line calculation amount. At the same time, two emergency repair modes are provided, together with the fastest line calculation method and classified emergency repair method, which balance the scheduling efficiency and cost and improve the overall scheduling efficiency of vehicles within the maintenance cycle.

[0033] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A smart management method for logistics engineering vehicles based on Internet of Things data, characterized by: The following steps are included: Step S1, input the location of each substation in the area into the computer of the dispatching and monitoring center, calculate the line distance between adjacent substations through map software and optimize the overall shortest navigation line of the substations in series as a one-way standard maintenance line, said step S1 includes the process of inputting the location of the dispatching and monitoring center into the computer as the starting point of the line to perform line calculation optimization, and said dispatching and monitoring center is correspondingly marked as a central station in step S2 and displayed on the large screen of the dispatching and monitoring center; Step S2, installing road information stations at equal intervals between adjacent substations, marking the road information stations as control nodes and marking each substation as a maintenance station, numbering the control nodes and maintenance stations and displaying them on a large screen in the dispatching and monitoring center; Step S3, installing a radio frequency identification reader / writer for reading vehicle positions and issuing dispatching instructions at the road information station and the substation, and setting a communication device to communicate remotely with the dispatching monitoring center; Step S4, each vehicle starts routine maintenance according to the standard maintenance route. When the dispatching and monitoring center receives a request for emergency repair of the substation, the dispatching and monitoring center issues a corresponding dispatching instruction according to the emergency level; The scheduling instruction mode in step S4 includes: (1) In the emergency repair mode, vehicles closest to the target substation are deployed first, including vehicles going in the forward direction, reverse direction, at the station, and on the way, to rush to the target substation for repair; (2) In non-emergency repair mode, priority is given to deploying vehicles on the way closest to the target substation to rush to the target substation for repair; Among them, the emergency repair mode includes identifying and calculating the actual navigation distance of the two control nodes with the vehicles on the way and expected to arrive and a maintenance site with the vehicles at the station through the dispatching and monitoring center, and marking the corresponding vehicles as candidate vehicles, and at the same time instructing the vehicles at the station to immediately start navigating the shortest route through the electronic tag. The dispatching and monitoring center monitors and records the driving status of the three candidate vehicles and calculates and selects a vehicle with the best actual navigation distance. The process of the dispatching and monitoring center calculating and selecting a vehicle with the best actual navigation distance includes selecting the vehicle that arrives at the corresponding control node or maintenance site first from the two vehicles on the way, and starting the communication positioning terminal of the vehicle and another original candidate vehicle at the station at the same time to directly calculate and compare the shortest navigation route distance, and selecting the vehicle with the shortest navigation route distance as the emergency repair vehicle; Step S5, the selected dispatch vehicle receives the interruption instruction and executes the temporary work order task. After the temporary work order is completed, the dispatch vehicle resumes the normal maintenance mode and continues to execute the maintenance task along the standard maintenance route until the end of this maintenance cycle.

2. According to claim 1, a method for intelligent management of logistics engineering vehicles based on Internet of Things data is characterized by: The step S4 includes the process of the driver checking the non-stop maintenance equipment at various control nodes and maintenance stations along the way, as well as the driver's alcohol detection face recognition matching inspection process. The face recognition inspection process includes the process of generating a virtual tag using face recognition information and recording the driving time information to the virtual tag.

3. A management system composed of a smart management method for logistics engineering vehicles based on the Internet of Things according to claim 1, characterized in that: It includes a dispatching and monitoring center, maintenance sites, control nodes and maintenance vehicles. The dispatching and monitoring center is configured as a central station. The central station is provided with a large display screen. The large display screen stores and configures standard maintenance routes based on actual distances and composed of a combination of the central station, maintenance sites and control nodes in series. The standard maintenance routes are used to provide route references for the maintenance vehicles. The maintenance vehicles are provided with radio frequency identification electronic tags. The maintenance sites are configured as actual locations of each substation room. The control nodes are configured as road information sites that are evenly spaced between adjacent maintenance sites in the actual standard maintenance routes. Both the maintenance sites and the control nodes are provided with radio frequency identification readers and writers. The radio frequency identification readers and writers are used to read and write the radio frequency identification electronic tag information of the maintenance vehicles without stopping.

4. According to claim 3, the intelligent management system for logistics engineering vehicles based on the Internet of Things is characterized by: The maintenance vehicle is provided with a vehicle data management system, which is connected to the radio frequency identification electronic tag. The vehicle data management system includes a level reader / writer, a sensor data system, a navigation database and a storage center. The level reader / writer is used to read the level tag on the maintenance equipment in the vehicle, the sensor data system is used to receive the sensor information of the vehicle driver and generate a virtual tag, and the navigation database is connected to a communication positioning terminal and a cloud computing center.

5. According to claim 4, the intelligent management system for logistics engineering vehicles based on the Internet of Things is characterized by: The sensor data system includes a head portrait recognition helmet, which is provided with a camera and an alcohol detector. The camera can be used to simultaneously confirm the driver's identity and steering wheel position matching information. The alcohol detector is connected to the head portrait recognition helmet through a rotating rod and is configured to start working at a specified rotation position.

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