Pavement construction early warning method and device based on multi-dimensional data and electronic equipment

Abstract

The invention provides a pavement construction early warning method and device based on multi-dimensional data and electronic equipment, and relates to the technical field of intelligent monitoring, and the method comprises the steps: obtaining pavement vibration data, equipment inclination data and positioning environment data through ground nail equipment; inputting the road surface vibration data, the equipment inclination data and the positioning environment data into a data cleaning model, and performing false alarm filtering through the dynamic integral accumulation algorithm to obtain a construction early warning comprehensive score; and determining a construction early warning strategy based on the construction early warning comprehensive score. According to the invention, vibration monitoring, inclination angle sensing and geographical environment multi-dimensional data are fused, an intelligent construction early warning system is constructed, and the early warning accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent monitoring technology, and in particular to a road construction early warning method, device and electronic equipment based on multi-dimensional data. Background Art

[0002] In the existing field of municipal infrastructure monitoring, the technical solution of using ground-spiked vibration sensors for road construction monitoring has significant flaws. Traditional methods rely primarily on a single vibration intensity threshold collected by ground-spiked equipment to judge construction behavior, and their alarm mechanism has the following technical bottlenecks: 1. When the device is deployed in areas such as traffic arteries and crosswalks, the road vibration spectrum generated by heavy vehicles (such as muck trucks and container trucks) overlaps with the low-frequency shock waves of the road breaker, resulting in a high false alarm rate when relying solely on vibration amplitude detection. 2. There is a lack of a collaborative analysis mechanism for weather conditions and equipment cluster status. Misjudgments of equipment tilt caused by soil loosening due to rainwater infiltration during heavy rainstorms, as well as isolated alarms triggered by temporary municipal construction (such as street light maintenance), cannot be effectively filtered.

[0003] Therefore, a road construction early warning method, device and electronic equipment based on multi-dimensional data are proposed. Summary of the Invention

[0004] This manual provides a road construction early warning method, device and electronic equipment based on multi-dimensional data, integrating vibration monitoring, inclination perception and multi-dimensional data of the geographical environment to build an intelligent construction early warning system, thereby improving the accuracy of early warning.

[0005] This specification provides a road construction early warning method based on multi-dimensional data, including: Obtain road vibration data, equipment tilt data, and positioning environment data through ground nail equipment; The road vibration data, equipment tilt data, and positioning environment data are input into the data cleaning model, and false alarms are filtered out using the dynamic integral accumulation algorithm to obtain a comprehensive construction early warning score; A construction early warning strategy is determined based on the comprehensive construction early warning score.

[0006] Optionally, the positioning environment data includes positioning location type, acquisition time type, and positioning weather type; wherein the positioning location data includes business district location, park location, traffic artery location, and other locations.

[0007] Optionally, the performing false alarm filtering by the dynamic integral accumulation algorithm includes: Dynamically adjusting the basic integral of the dynamic integral accumulation algorithm based on the acquisition time type includes: A self-model for weekday operating hours is established for commercial areas. When the alarm time falls into the first preset time period on weekdays or the second preset time period on holidays, the integral suppressor is activated to reset the alarm integral to zero. A peak interval recognition module is configured for the park area. When the alarm time falls into the third period group on weekdays or the fourth period group on holidays, the points reset instruction is triggered; A continuous de-prioritization processor is loaded for traffic arterial sections, and the alarm points are converted according to a preset proportional coefficient.

[0008] Optionally, the performing false alarm filtering by the dynamic integral accumulation algorithm further includes: Access the real-time data interface of the Meteorological Bureau to analyze the positioning weather type; Generate compensation coefficient based on meteorological disaster level mapping table: When the weather type is rainy or light snow, the first compensation level is activated; When the weather type is heavy rain or strong wind, the second compensation level is activated; When the weather type is heavy rain, storm or moderate snow or above, the third compensation level is activated.

[0009] Optionally, it also includes: when the device tilt data meets the preset deformation condition, activating the independent alarm evaluation channel.

[0010] Optionally, determining a construction early warning strategy based on the comprehensive construction early warning score includes: triggering a differentiated response strategy based on the threshold range of the comprehensive construction early warning score; The dynamic change rate of the device tilt data is independently evaluated to generate a cross-level alarm instruction.

[0011] Optionally, also include: Establish equipment association network based on cable channel topology; When the associated device group reaches the coordinated alarm density within the preset time window, the points multiplication mechanism is triggered; The determination of the coordinated alarm density includes: if the number of alarms of associated devices in the same cable channel reaches a first preset number threshold, then adding a first multiplication coefficient to the total score; if the number of alarms of associated devices in the same cable channel reaches a second preset number threshold, then adding a second multiplication coefficient to the total score; Basic points accumulation is performed for isolated alarms triggered by unrelated devices.

[0012] This specification provides a road construction early warning device based on multi-dimensional data, including: The acquisition module is used to obtain road vibration data, equipment tilt data, and positioning environment data through ground nail equipment; A scoring module is used to input the road vibration data, equipment tilt data, and positioning environment data into a data cleaning model, and filter false alarms using the dynamic integral accumulation algorithm to obtain a comprehensive construction warning score; The early warning module is used to determine a construction early warning strategy based on the comprehensive construction early warning score.

[0013] Optionally, the positioning environment data includes positioning location type, acquisition time type, and positioning weather type; wherein the positioning location data includes business district location, park location, traffic artery location, and other locations.

[0014] Optionally, the scoring module includes: Dynamically adjusting the basic integral of the dynamic integral accumulation algorithm based on the acquisition time type includes: A self-model for weekday operating hours is established for commercial areas. When the alarm time falls into the first preset time period on weekdays or the second preset time period on holidays, the integral suppressor is activated to reset the alarm integral to zero. A peak interval recognition module is configured for the park area. When the alarm time falls into the third period group on weekdays or the fourth period group on holidays, the points reset instruction is triggered; A continuous de-prioritization processor is loaded for traffic arterial sections, and the alarm points are converted according to a preset proportional coefficient.

[0015] Optionally, the scoring module further includes: Access the real-time data interface of the Meteorological Bureau to analyze the positioning weather type; Generate compensation coefficient based on meteorological disaster level mapping table: When the weather type is rainy or light snow, the first compensation level is activated; When the weather type is heavy rain or strong wind, the second compensation level is activated; When the weather type is heavy rain, storm or moderate snow or above, the third compensation level is activated.

[0016] Optionally, it also includes: when the device tilt data meets the preset deformation condition, activating the independent alarm evaluation channel.

[0017] Optionally, the scoring module includes: triggering a differentiated response strategy based on the threshold range of the comprehensive construction early warning score; The dynamic change rate of the device tilt data is independently evaluated to generate a cross-level alarm instruction.

[0018] Optionally, also include: Establish equipment association network based on cable channel topology; When the associated device group reaches the coordinated alarm density within the preset time window, the points multiplication mechanism is triggered; The determination of the coordinated alarm density includes: if the number of alarms of associated devices in the same cable channel reaches a first preset number threshold, then adding a first multiplication coefficient to the total score; if the number of alarms of associated devices in the same cable channel reaches a second preset number threshold, then adding a second multiplication coefficient to the total score; Basic points accumulation is performed for isolated alarms triggered by unrelated devices.

[0019] This specification also provides an electronic device, wherein the electronic device includes: processor; and, A memory storing computer executable instructions, which, when executed, cause the processor to perform any of the above methods.

[0020] This specification also provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, any of the above methods is implemented.

[0021] This invention integrates vibration monitoring, tilt sensing, and multi-dimensional geographic environmental data to create an intelligent construction early warning system. It uses a spatiotemporal dynamic integration algorithm to accurately filter false alarms. Site feature modeling combined with a meteorological compensation mechanism effectively eliminates environmental interference. Independent alarm channels and a cross-level response mechanism overcome conventional threshold limits when sudden tilt changes or equipment cluster alarms occur, improving early warning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 A schematic diagram of the principle of a road construction early warning method based on multi-dimensional data provided in an embodiment of this specification; Figure 2 A schematic diagram of the structure of a road construction early warning device based on multi-dimensional data provided in an embodiment of this specification; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification; Figure 4 A schematic diagram of a computer-readable medium provided in accordance with an embodiment of this specification. DETAILED DESCRIPTION

[0024] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are for illustrative purposes only, and those skilled in the art will readily appreciate other obvious variations. The basic principles of the present invention defined in the following description may be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the present invention.

[0025] The following is combined with Figure 1-4 The exemplary embodiments of the present invention are described more fully. However, the exemplary embodiments can be implemented in various forms, and the present invention should not be construed as being limited to the embodiments set forth herein. On the contrary, providing these exemplary embodiments enables the present invention to be more comprehensive and complete, and more conveniently conveys the inventive concept to those skilled in the art. In the figures, the same reference numerals represent the same or similar elements, components, or parts, and thus their repeated description will be omitted.

[0026] Under the premise of being consistent with the technical concept of the present invention, the features, structures, characteristics or other details described in a specific embodiment do not exclude that they can be combined in one or more other embodiments in a suitable manner.

[0027] In the description of specific embodiments, the features, structures, characteristics, or other details of the present invention are described to enable those skilled in the art to fully understand the embodiments. However, this does not preclude those skilled in the art from practicing the technical solutions of the present invention without one or more of the specific features, structures, characteristics, or other details.

[0028] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0029] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0030] The term "and / or" or "and / or" includes all combinations of any one or more of the associated listed items.

[0031] Figure 1 A schematic diagram of the principle of a road construction early warning method based on multi-dimensional data provided in an embodiment of this specification may include: S110: Obtaining road vibration data, equipment tilt data, and positioning environment data through ground spike equipment; Optionally, the positioning environment data includes positioning location type, acquisition time type, and positioning weather type; wherein the positioning location data includes business district location, park location, traffic artery location, and other locations.

[0032] In the specific implementation of this specification, the ground nail device has a built-in three-axis accelerometer and inclination sensor to collect the original road vibration signal and device posture data in real time. Call the AutoNavi Map API to obtain POI data within a preset range of meters and automatically classify the site type: Commercial area: POI tags such as shopping malls and pedestrian streets are detected ≥ the first preset value; Park area: Identify factories, office buildings, etc. with building density greater than the second preset value; Traffic arterial road sections: Based on the road network GIS data, the distance from the subway / viaduct is ≤ the third preset value.

[0033] At the same time, it is connected to the statutory holidays database released by the State Council.

[0034] S120: Inputting the road vibration data, equipment tilt data, and positioning environment data into a data cleaning model, and filtering false alarms using the dynamic integral accumulation algorithm to obtain a comprehensive construction warning score; Optionally, the performing false alarm filtering by the dynamic integral accumulation algorithm includes: Dynamically adjusting the basic integral of the dynamic integral accumulation algorithm based on the acquisition time type includes: A self-model for weekday operating hours is established for commercial areas. When the alarm time falls into the first preset time period on weekdays or the second preset time period on holidays, the integral suppressor is activated to reset the alarm integral to zero. A peak interval recognition module is configured for the park area. When the alarm time falls into the third period group on weekdays or the fourth period group on holidays, the points reset instruction is triggered; A continuous de-prioritization processor is loaded for traffic arterial sections, and the alarm points are converted according to a preset proportional coefficient.

[0035] In the specific implementation of this specification, in the business district area: ① Weekdays: an alarm is triggered between 8-21 o'clock, and no points are added; ② Holidays: an alarm is triggered between 8-22 o'clock, and no points are added.

[0036] Park area: ① Weekdays: 7-9 11:30-13:30 17-19. Alarms will be triggered during this period and no points will be added. ② Holidays: Alarms will be triggered during 12-13. No points will be added.

[0037] Traffic arterial roads: Regardless of weekdays or holidays, the alarm points are divided by 2 when calculating.

[0038] Other areas: ① Weekdays: Alarms will be triggered during 7-8, 12-13, and 17-18, and no points will be added; ② Holidays: Alarms will be triggered during 12-13, and no points will be added.

[0039] Optionally, the performing false alarm filtering by the dynamic integral accumulation algorithm further includes: Access the real-time data interface of the Meteorological Bureau to analyze the positioning weather type; Generate compensation coefficient based on meteorological disaster level mapping table: When the weather type is rainy or light snow, the first compensation level is activated; When the weather type is heavy rain or strong wind, the second compensation level is activated; When the weather type is heavy rain, storm or moderate snow or above, the third compensation level is activated.

[0040] In the specific implementation manner of this specification, the weather mechanism is: sunny day: -0; rainy day: -1; heavy rain: -2; rainstorm or above: -3; strong wind or above: -2; storm: -3; light snow: -2; moderate snow or above: -3.

[0041] S130: Determine a construction early warning strategy based on the comprehensive construction early warning score.

[0042] Optionally, determining a construction early warning strategy based on the comprehensive construction early warning score includes: triggering a differentiated response strategy based on the threshold range of the comprehensive construction early warning score; The dynamic change rate of the device tilt data is independently evaluated to generate a cross-level alarm instruction.

[0043] In the specific implementation of this specification, based on the dual-track evaluation system of the construction early warning comprehensive score threshold range and the dynamic change rate of equipment tilt, the system implements a graded response strategy: when the comprehensive score is at the observation level of 0-6 points, the weather compensation mechanism is activated and a health briefing is generated according to the preset time; the 6-12 point early warning level triggers equipment operation freezing and 10Hz high-frequency monitoring, and simultaneously pushes disposal suggestions to the responsible person's terminal; the alarm level ≥12 points immediately cuts off the power supply and generates an encrypted work order containing a three-dimensional stress cloud map, and links the municipal platform to send the location risk code.

[0044] Optionally, it also includes: when the device tilt data meets the preset deformation condition, activating the independent alarm evaluation channel.

[0045] In the specific implementation of this specification, when the equipment tilt data reaches the preset deformation condition, the system will activate the independent alarm assessment channel for special disposal. Specifically, the three-dimensional posture monitoring model is used to detect the equipment tilt angle in real time to trigger the independent assessment thread. This channel has the highest priority and is not subject to the conventional integration rules. It immediately generates a level one red alert containing a three-dimensional deformation trajectory map, which is pushed to the operation and maintenance terminal through the dedicated network and freezes the relevant equipment operation permissions. The execution process adopts a multi-dimensional cross-validation mechanism, synchronously retrieves multiple sets of surrounding equipment data, AI video analysis and stress thermodynamic maps for composite diagnosis, and automatically generates an electronic work order containing an emergency disposal plan after confirming the abnormality, and forcibly activates the electronic fence and backup power supply protection. The system will continue to monitor until the deformation value falls back to the safe threshold range, generate a safety briefing at preset time intervals and link the municipal emergency platform, and realize the full process control from second-level warning to closed-loop disposal through the dual-axis MEMS sensor and BIM visualization interface, ensuring that major deformation risks receive a special emergency response independent of the location, weather and time period.

[0046] Optionally, also include: Establish equipment association network based on cable channel topology; When the associated device group reaches the coordinated alarm density within the preset time window, the points multiplication mechanism is triggered; The determination of the coordinated alarm density includes: if the number of alarms of associated devices in the same cable channel reaches a first preset number threshold, then adding a first multiplication coefficient to the total score; if the number of alarms of associated devices in the same cable channel reaches a second preset number threshold, then adding a second multiplication coefficient to the total score; Basic points accumulation is performed for isolated alarms triggered by unrelated devices.

[0047] In a specific embodiment of this specification, a device association network is constructed based on cable channel topology. Device groups are defined through physical connections (sharing the same trench / tower), electrical interactions, and logical associations. A hierarchical topological database encompassing trunk lines, branch lines, and terminal devices is dynamically maintained. When a group of associated devices reaches a coordinated alarm density within a preset rolling time window (the preset rolling time window is automatically shortened in severe weather), a point multiplication mechanism is triggered: Alarms from ≥2 devices in the same channel are multiplied by a factor of 1.5, and alarms from ≥4 devices are multiplied by a factor of 2. The baseline number of alarms is dynamically adjusted based on channel size. Unrelated, isolated alarms are cumulatively accumulated using basic points and weather attenuation. The technology utilizes a Neo4j graph database to store topological relationships, combined with the DBSCAN algorithm for alarm cluster identification. The threshold baseline is dynamically increased through LSTM prediction. A false alarm circuit breaker mechanism and manual review process are simultaneously implemented, forming an intelligent point multiplication strategy that balances device association strength and spatiotemporal alarm density. This strategy strengthens cluster risk response while avoiding excessive warnings, enabling precise control of cable channel safety assessments.

[0048] Specifically, ① Within the same cable channel, compare the number of ground spike devices that have uploaded alarm information within two hours with the total number of devices. If two or more devices have generated an alarm, 6 points will be added; if four or more devices have generated an alarm, 12 points will be added (excluding weather conditions). A score of 12 points or more triggers an alarm. ② Within different cable channels, if a single device generates an alarm, 3 points will be added for each alarm.

[0049] This invention integrates vibration monitoring, tilt sensing, and multi-dimensional geographic environmental data to create an intelligent construction early warning system. It uses a spatiotemporal dynamic integration algorithm to accurately filter false alarms. Site feature modeling combined with a meteorological compensation mechanism effectively eliminates environmental interference. Independent alarm channels and a cross-level response mechanism overcome conventional threshold limits when sudden tilt changes or equipment cluster alarms occur, improving early warning accuracy.

[0050] Figure 2 This is a schematic diagram of the principle of a road construction early warning device based on multi-dimensional data provided in an embodiment of this specification. The device may include: An acquisition module 10 is used to acquire road vibration data, equipment tilt data, and positioning environment data through ground spike equipment; Scoring module 20, for inputting the road vibration data, equipment tilt data, and positioning environment data into a data cleaning model, and filtering false alarms using the dynamic integral accumulation algorithm to obtain a comprehensive construction warning score; The early warning module 30 is configured to determine a construction early warning strategy based on the comprehensive construction early warning score.

[0051] Optionally, the positioning environment data includes positioning location type, acquisition time type, and positioning weather type; wherein the positioning location data includes business district location, park location, traffic artery location, and other locations.

[0052] Optionally, the scoring module 20 includes: Dynamically adjusting the basic integral of the dynamic integral accumulation algorithm based on the acquisition time type includes: A self-model for weekday operating hours is established for commercial areas. When the alarm time falls into the first preset time period on weekdays or the second preset time period on holidays, the integral suppressor is activated to reset the alarm integral to zero. A peak interval recognition module is configured for the park area. When the alarm time falls into the third period group on weekdays or the fourth period group on holidays, the points reset instruction is triggered; A continuous de-prioritization processor is loaded for traffic arterial sections, and the alarm points are converted according to a preset proportional coefficient.

[0053] Optionally, the scoring module 20 further includes: Access the real-time data interface of the Meteorological Bureau to analyze the positioning weather type; Generate compensation coefficient based on meteorological disaster level mapping table: When the weather type is rainy or light snow, the first compensation level is activated; When the weather type is heavy rain or strong wind, the second compensation level is activated; When the weather type is heavy rain, storm or moderate snow or above, the third compensation level is activated.

[0054] Optionally, it also includes: when the device tilt data meets the preset deformation condition, activating the independent alarm evaluation channel.

[0055] Optionally, the scoring module 30 includes: triggering a differentiated response strategy based on the threshold range of the comprehensive construction early warning score; The dynamic change rate of the device tilt data is independently evaluated to generate a cross-level alarm instruction.

[0056] Optionally, also include: Establish equipment association network based on cable channel topology; When the associated device group reaches the coordinated alarm density within the preset time window, the points multiplication mechanism is triggered; The determination of the coordinated alarm density includes: if the number of alarms of associated devices in the same cable channel reaches a first preset number threshold, then adding a first multiplication coefficient to the total score; if the number of alarms of associated devices in the same cable channel reaches a second preset number threshold, then adding a second multiplication coefficient to the total score; Basic points accumulation is performed for isolated alarms triggered by unrelated devices.

[0057] The functions of the device in the embodiment of the present invention have been described in the above method embodiment. Therefore, for details not fully described in this embodiment, please refer to the relevant description in the above embodiment and will not be repeated here.

[0058] Based on the same inventive concept, an embodiment of this specification also provides an electronic device.

[0059] The following describes an electronic device embodiment of the present invention, which can be considered a specific physical implementation of the method and apparatus embodiments of the present invention described above. Details described in the electronic device embodiment of the present invention should be considered supplementary to the above-mentioned method or apparatus embodiments; details not disclosed in the electronic device embodiment of the present invention can be implemented with reference to the above-mentioned method or apparatus embodiments.

[0060] Figure 3 This is a schematic diagram of the structure of an electronic device provided in the embodiment of this specification. Figure 3 The electronic device 300 according to this embodiment of the present invention will be described. Figure 3The electronic device 300 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0061] like Figure 3 As shown, electronic device 300 is implemented as a general-purpose computing device. Components of electronic device 300 may include, but are not limited to, at least one processing unit 310, at least one storage unit 320, a bus 330 connecting various system components (including storage unit 320 and processing unit 310), and a display unit 340.

[0062] The storage unit stores program codes that can be executed by the processing unit 310, so that the processing unit 310 performs the steps according to various exemplary embodiments of the present invention described in the above processing method section of this specification. For example, the processing unit 310 can perform the following steps: Figure 1 Steps shown.

[0063] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 3201 and / or a cache memory unit 3202 , and may further include a read-only memory unit (ROM) 3203 .

[0064] The storage unit 320 may also include a program / utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include an implementation of a network environment.

[0065] Bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0066] The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable viewers to interact with the electronic device 300, and / or any device that enables the electronic device 300 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 350. Furthermore, the electronic device 300 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 through the bus 330. It should be understood that although Figure 3 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0067] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the exemplary embodiments described in the present invention can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, server, or network device, etc.) to execute the above method according to the present invention. When the computer program is executed by a data processing device, the computer-readable medium is enabled to implement the above method of the present invention, that is: Figure 1 The method shown.

[0068] Figure 4 A schematic diagram of a computer-readable medium provided in accordance with an embodiment of this specification.

[0069] accomplish Figure 1 The computer program of the illustrated method can be stored on one or more computer-readable media. The computer-readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0070] The computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein the readable program code is carried. The data signal propagated may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or component. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0071] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the viewer computing device, partially on the viewer device, as a stand-alone software package, partially on the viewer computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the viewer computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0072] In summary, the present invention can be implemented in hardware, or as a software module running on one or more processors, or a combination thereof. Those skilled in the art will appreciate that, in practice, general-purpose data processing devices such as microprocessors or digital signal processors (DSPs) can be used to implement some or all of the functions of some or all of the components according to the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program or computer program product) for performing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium or in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0073] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the present invention is not inherently related to any specific computer, virtual device, or electronic device, and various general-purpose devices can also implement the present invention. The above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

[0074] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0075] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A road construction early warning method based on multi-dimensional data, characterized in that: include: Obtain road vibration data, equipment tilt data, and positioning environment data through ground nail equipment; The road vibration data, equipment tilt data, and positioning environment data are input into the data cleaning model, and false alarms are filtered out using the dynamic integral accumulation algorithm to obtain a comprehensive construction early warning score; A construction early warning strategy is determined based on the comprehensive construction early warning score.

2. The road construction early warning method based on multi-dimensional data according to claim 1, characterized in that: The positioning environment data includes positioning area type, acquisition time type, and positioning weather type; wherein the positioning area data includes business district area, park area, traffic artery area, and other areas.

3. The road construction early warning method based on multi-dimensional data according to claim 2, characterized in that: The false alarm filtering by the dynamic integral accumulation algorithm includes: Dynamically adjusting the basic integral of the dynamic integral accumulation algorithm based on the acquisition time type includes: A self-model for weekday operating hours is established for commercial areas. When the alarm time falls into the first preset time period on weekdays or the second preset time period on holidays, the integral suppressor is activated to reset the alarm integral to zero. A peak interval recognition module is configured for the park area. When the alarm time falls into the third period group on weekdays or the fourth period group on holidays, the points reset instruction is triggered; A continuous de-prioritization processor is loaded for traffic arterial sections, and the alarm points are converted according to a preset proportional coefficient.

4. The road construction early warning method based on multi-dimensional data according to claim 3, characterized in that: The false alarm filtering by the dynamic integral accumulation algorithm further includes: Access the real-time data interface of the Meteorological Bureau to analyze the positioning weather type; Generate compensation coefficient based on meteorological disaster level mapping table: When the weather type is rainy or light snow, the first compensation level is activated; When the weather type is heavy rain or strong wind, the second compensation level is activated; When the weather type is heavy rain, storm or moderate snow or above, the third compensation level is activated.

5. The road construction early warning method based on multi-dimensional data according to claim 4, characterized in that: Also includes: When the equipment tilt data meets the preset deformation conditions, an independent alarm evaluation channel is activated.

6. The road construction early warning method based on multi-dimensional data according to claim 5, characterized in that: Determining a construction early warning strategy based on the comprehensive construction early warning score includes: triggering a differentiated response strategy based on the threshold range of the comprehensive construction early warning score; The dynamic change rate of the device tilt data is independently evaluated to generate a cross-level alarm instruction.

7. The road construction early warning method based on multi-dimensional data according to claim 6, characterized in that: Also includes: Establish equipment association network based on cable channel topology; When the associated device group reaches the coordinated alarm density within the preset time window, the points multiplication mechanism is triggered; The determination of the coordinated alarm density includes: if the number of alarms of associated devices in the same cable channel reaches a first preset number threshold, then adding a first multiplication coefficient to the total score; if the number of alarms of associated devices in the same cable channel reaches a second preset number threshold, then adding a second multiplication coefficient to the total score; Basic points are accumulated for isolated alarms triggered by unrelated devices.

8. A road construction early warning device based on multi-dimensional data, characterized in that: include: The acquisition module is used to obtain road vibration data, equipment tilt data, and positioning environment data through ground nail equipment; A scoring module is used to input the road vibration data, equipment tilt data, and positioning environment data into a data cleaning model, and filter false alarms using the dynamic integral accumulation algorithm to obtain a comprehensive construction warning score; The early warning module is used to determine a construction early warning strategy based on the comprehensive construction early warning score.

9. An electronic device, wherein: The electronic device includes: processor; and, A memory storing computer executable instructions which, when executed, cause the processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, wherein: The computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the method of any one of claims 1 to 7 is implemented.

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