Plateau area construction monitoring system based on unmanned aerial vehicle and three-dimensional simulation technology

Abstract

The invention discloses a plateau area construction monitoring system based on an unmanned aerial vehicle and a three-dimensional simulation technology. The system is especially suitable for construction whole-process digital management in a plateau complex environment. Comprising an unmanned aerial vehicle platform carrying multiple sensors, a three-dimensional modeling module, a data processing module and a monitoring terminal. The unmanned aerial vehicle obtains high-precision topographic data and constructs a digital twin reference model; the data processing module recognizes safety equipment in real time based on an AI visual algorithm, monitors the temperature of the frozen soil roadbed, and early warns geological disasters through the GIS + Beidou technology; the monitoring terminal integrates construction progress analysis, quality detection and operation and maintenance path planning functions. According to the invention, through full-process digital management of "before-construction-in-construction-after-construction", the core problems of severe plateau climate, complex geology and the like are solved, and the construction efficiency and safety are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of highland region construction monitoring, and in particular to a highland region construction monitoring system based on unmanned aerial vehicles and three-dimensional simulation technology. BACKGROUND

[0002] As a key construction region for major national energy and transportation projects, the unique geographical environment and climate conditions of the plateau region pose severe challenges to engineering construction. Currently, highland region construction relies mainly on traditional monitoring and management methods, and some technical solutions have attempted to introduce unmanned aerial vehicle aerial surveying and mapping and three-dimensional modeling technology. However, these existing technologies still have systematic defects in actual application and are difficult to meet the special needs of highland construction. Specifically, the existing technologies face the following core problems: Technical concepts and standards are fragmented: the plateau region is vast, and the economic development level and technical concepts of different regions differ significantly, leading to non-uniform construction monitoring standards. For example, the monitoring process suitable for the eastern plain region cannot be directly migrated to the plateau environment, resulting in distorted data collection and analysis results and significantly reduced monitoring effectiveness.

[0003] Insufficient technical implementation and environmental adaptability: the highland construction environment is highly complex, and existing technologies lack targeted design. In tunnel engineering, disasters such as rock burst and high ground stress occur frequently, but existing monitoring methods are limited to static data collection and cannot dynamically respond to geological changes. In terms of climate, the large diurnal temperature difference, low temperature leading to abnormal concrete setting, and strong ultraviolet light accelerating material aging, the existing technology does not integrate climate factors for prediction, significantly affecting engineering quality and progress.

[0004] Lack of whole-chain management: Personnel management: high altitude reaction leads to high health risk and low work efficiency of construction personnel, and the existing technology does not establish a dynamic health monitoring mechanism, and the personnel training and selection lack highland adaptability evaluation standards.

[0005] Material management: remote geographical location leads to a significant increase in the cost of material procurement and transportation (such as an increase of more than 40% compared to the plain region), and climate conditions pose special requirements for material storage (such as frost and moisture protection), and the existing system cannot achieve digital tracking of the whole process of materials, which is prone to cause supply shortages or waste.

[0006] Quality and safety control: quality standards are not refined for highland environment (such as missing temperature threshold for permafrost roadbed), inspection and detection frequency is insufficient and accuracy is low (such as conventional detection error of ±10mm), safety risk assessment is one-sided, and emergency plans lack real-time response capability, leading to frequent accidents such as geological disasters and high altitude reactions.

[0007] Environmental pressure: The highland ecological system is fragile, and the existing technology does not include ecological protection in the monitoring system. Construction activities are easy to cause vegetation damage and pollution (such as non-standard waste water and solid waste treatment), which is difficult to meet the requirements of the ecological priority policy.

[0008] In summary, the existing technology fails to build a digital management system covering the whole process before, during and after construction, resulting in low efficiency, rising costs, prominent safety risks and increasing environmental pressure. An innovative solution that deeply integrates unmanned aerial vehicles and three-dimensional simulation technology is urgently needed to systematically solve the multi-dimensional technical bottlenecks in the highland environment and provide reliable support for highland regional engineering construction. SUMMARY

[0009] The present application provides a highland regional construction monitoring system based on unmanned aerial vehicles and three-dimensional simulation technology, which can solve the technical problems of lack of whole-process digital monitoring system in highland regional construction, resulting in low construction efficiency, high safety risk and inaccurate quality control.

[0010] In a first aspect, the present application provides a highland regional construction monitoring system based on unmanned aerial vehicles and three-dimensional simulation technology, which comprises an unmanned aerial vehicle platform, a three-dimensional modeling module, a data processing module and a monitoring terminal. The unmanned aerial vehicle platform carries a laser radar and an oblique photography module for collecting high-precision terrain data of the highland region. The three-dimensional modeling module constructs a digital elevation model and a digital orthographic image based on the terrain data, and superimposes a BIM model to form a digital twin benchmark. The data processing module analyzes the data in real time during construction based on the digital twin benchmark, generates progress deviation reports, quality detection results and safety warning information. The monitoring terminal is used to display and manage progress deviation reports, quality detection results and safety warning information.

[0011] In combination with the first aspect, in an embodiment, the unmanned aerial vehicle platform also carries an infrared thermal imager for real-time monitoring of the temperature field distribution of the frozen soil roadbed and triggering thermal insulation measures when detecting local temperature anomalies.

[0012] In combination with the first aspect, in an embodiment, the data processing module includes an AI vision algorithm for identifying the wearing of safety equipment by construction personnel and correcting in real time through a voice intercom system.

[0013] In combination with the first aspect, in an embodiment, the three-dimensional modeling module further includes a geological disaster warning sub-module that uses GIS and Beidou technology to model landslide and debris flow hazard points in three dimensions and sets a deformation threshold to achieve early warning.

[0014] With the first aspect, in one implementation, the monitoring accuracy of the infrared thermal imager is ±1℃, which is used to ensure that the frozen soil roadbed temperature is controlled within the design range.

[0015] With the first aspect, in one implementation, the AI vision algorithm adopts the YOLO algorithm to realize automatic identification of safety helmets and oxygen masks.

[0016] With the first aspect, in one implementation, the data processing module is further used to generate a three-dimensional completion model after construction, and the three-dimensional completion model contains material, size and installation position information.

[0017] With the first aspect, in one implementation, the three-dimensional completion model is constructed by collecting geometric information and texture information through a total station and a laser scanner.

[0018] With the first aspect, in one implementation, the monitoring terminal supports unmanned aerial vehicle inspection route planning based on the three-dimensional model, which is used to optimize photovoltaic panel cleaning and fan blade detection and other operation and maintenance tasks.

[0019] With the first aspect, in one implementation, the unmanned aerial vehicle inspection route planning algorithm automatically calculates the optimal inspection path based on obstacle data and terrain features in the three-dimensional model.

[0020] The technical scheme provided by the embodiments of the present application has the following beneficial effects: Through dynamic comparison of the digital twin benchmark and real-time construction data, the system presents the construction progress and quality state in a three-dimensional model, so that the management personnel can identify deviations in time and make quick adjustments, significantly improving the timeliness of monitoring; at the same time, the unmanned aerial vehicle integrated with meteorological monitoring and AI analysis realizes active sensing and early warning of environmental risks, effectively preventing construction safety risks; in view of the particularity of the plateau environment, the system continuously monitors key elements such as frozen soil thermal field and geological disasters through three-dimensional simulation and unmanned aerial vehicle technology, realizes closed-loop management of construction safety and quality, and avoids the problem of insufficient adaptability of traditional methods in complex environments. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 FIG. 1 is a functional module schematic diagram of an embodiment of a plateau regional construction monitoring system based on unmanned aerial vehicles and three-dimensional simulation technology of the present application. DETAILED DESCRIPTION

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0024] In one aspect, embodiments of this application provide a construction monitoring system for high-altitude areas based on unmanned aerial vehicles (UAVs) and three-dimensional simulation technology.

[0025] In one embodiment, reference is made to Figure 1 , Figure 1 This is a schematic diagram of the functional modules of an embodiment of the construction monitoring system for high-altitude areas based on UAV and 3D simulation technology, as described in this application. Figure 1 As shown, the system includes an unmanned aerial vehicle (UAV) platform, a 3D modeling module, a data processing module, and a monitoring terminal. The unmanned aerial vehicle platform is equipped with a lidar and oblique photography module for collecting high-precision terrain data in the plateau region; The 3D modeling module constructs a digital elevation model and a digital orthophoto map based on the terrain data, and overlays them with the BIM model to form a digital twin benchmark; The data processing module performs real-time analysis of data during the construction process based on the digital twin benchmark, generating progress deviation reports, quality inspection results, and safety early warning information; The monitoring terminal is used to display and manage progress deviation reports, quality inspection results, and safety warning information.

[0026] In this embodiment, by dynamically comparing digital twin benchmarks with real-time construction data, the system presents the construction progress and quality status intuitively in a three-dimensional model, enabling managers to instantly identify deviations and make rapid adjustments, significantly improving the timeliness of monitoring. At the same time, drones integrating meteorological monitoring and AI analysis enable proactive perception and early warning of environmental risks, effectively preventing construction safety risks. In response to the special characteristics of the plateau environment, the system continuously monitors key elements such as permafrost thermal fields and geological hazards through three-dimensional simulation and drone technology, realizing closed-loop management of construction safety and quality, and avoiding the problem of insufficient adaptability of traditional methods in complex environments.

[0027] Furthermore, in one embodiment, the drone platform is also equipped with an infrared thermal imager for real-time monitoring of the temperature field distribution of the frozen soil subgrade, and for triggering insulation measures when local temperature rise anomalies are detected.

[0028] In this embodiment, in the construction of highland tunnels, the unmanned aerial vehicle platform carries an infrared thermal imager, which collects roadbed temperature data daily according to the preset flight route. The system compares the real-time temperature field distribution with the digital twin benchmark, and when it detects local temperature anomalies (such as a certain area with a temperature 0.8°C higher than the benchmark value), it automatically triggers the insulation measures (such as starting the electric blanket coverage). This embodiment effectively prevents the roadbed settlement caused by the thawing of frozen soil through high-precision temperature monitoring (accuracy ±1°C), ensuring that the concrete solidification quality meets the requirements of highland construction.

[0029] Further, in an embodiment, the data processing module includes an AI vision algorithm for identifying the wearing of safety equipment by construction personnel and making real-time corrections through a voice intercom system.

[0030] In this embodiment, at the highland construction site, the unmanned aerial vehicle carries an AI vision system (YOLO algorithm) to analyze the wearing of safety equipment by construction personnel in real time. The system extracts image features from aerial video streams, automatically identifies the absence or improper wearing of safety helmets and oxygen masks (such as an untied safety helmet), and immediately reminds the violating personnel through a voice intercom system. This embodiment significantly reduces safety risks in high-altitude environments on the plateau and avoids protection omissions caused by altitude sickness.

[0031] Further, in an embodiment, the three-dimensional modeling module further includes a geological disaster warning sub-module that performs three-dimensional modeling of landslide and debris flow hazard points based on GIS and Beidou technology and sets a deformation threshold to achieve early warning.

[0032] In this embodiment, in the highland landslide-prone area, the three-dimensional modeling module integrates the GIS geographic information system and Beidou positioning data to perform three-dimensional modeling of landslide hazard points. The system sets a deformation threshold (such as a displacement speed > 2mm / day), and when the unmanned aerial vehicle detects displacement data exceeding the threshold, it automatically generates geological disaster warning information and pushes it to the monitoring terminal. This embodiment achieves a 72-hour early warning of geological disasters and avoids construction safety accidents.

[0033] Further, in an embodiment, the monitoring accuracy of the infrared thermal imager is ±1°C, which is used to ensure that the temperature of the frozen soil roadbed is controlled within the designed range.

[0034] In this embodiment, in the construction of highland frozen soil roadbeds, the infrared thermal imager monitors the temperature field distribution with an accuracy of ±1°C. The system compares the monitoring data with the frozen soil design temperature range (-5°C to -2°C) of the digital twin benchmark, and when the local temperature exceeds the range, the insulation equipment adjusts the construction plan. This precision control avoids the misjudgment caused by traditional monitoring (±3°C) and ensures the stability of the roadbed.

[0035] Further, in an embodiment, the AI vision algorithm adopts the YOLO algorithm to realize automatic identification of safety helmets and oxygen masks.

[0036] In this embodiment, in the highland construction scene, the AI vision algorithm adopts the YOLOv4 model for safety equipment identification. The system uses 10,000+ training images of highland construction personnel wearing safety equipment (including close-up of oxygen masks and safety helmets) to optimize the recognition accuracy of the model in strong ultraviolet and low visibility environments (>95%). The UAV analyzes the aerial video in real time, automatically marks the violation and generates a safety report.

[0037] Further, in an embodiment, the data processing module is further configured to generate a three-dimensional completion model after construction, wherein the three-dimensional completion model comprises material, size and installation position information.

[0038] In this embodiment, after the construction is completed, the data processing module fuses the real scene point cloud data collected by the UAV with the BIM model to generate a three-dimensional completion model comprising material (such as the light reflection coefficient of photovoltaic panels), size (support height error <5mm) and installation position (coordinate accuracy ±2cm). The model is directly used for operation and maintenance management, such as accurately marking the installation angle of wind turbine blades in a wind farm, to guide subsequent maintenance.

[0039] Further, in an embodiment, the three-dimensional completion model is constructed by collecting geometric information and texture information through a total station and a laser scanner.

[0040] In this embodiment, in the highland environment, the three-dimensional completion model is constructed by a total station (collecting geometric coordinates) and a laser scanner (obtaining texture details). The total station is stably erected in the permafrost area to avoid device errors caused by low temperature; the laser scanner adopts a dustproof design to cope with the highland sandy environment. The collected point cloud data and texture information are fused to generate a high-fidelity completion model.

[0041] Further, in an embodiment, the monitoring terminal supports UAV inspection route planning based on the three-dimensional model, which is used to optimize photovoltaic panel cleaning and wind turbine blade detection and other operation and maintenance tasks.

[0042] In this embodiment, the monitoring terminal plans an optimal UAV inspection route for photovoltaic panel cleaning in a wind farm based on the three-dimensional completion model. The system automatically avoids obstacles such as wind turbine blades and calculates the minimum flight path (such as reducing 30% of redundant flight range). Under strong wind conditions on the plateau, the route dynamically adjusts the flight altitude to ensure safety and improve operation and maintenance efficiency.

[0043] Further, in an embodiment, the UAV inspection route planning algorithm automatically calculates the optimal inspection path based on obstacle data and terrain features in the three-dimensional model.

[0044] In this embodiment, the unmanned aerial vehicle inspection route planning algorithm analyzes the obstacle data (such as the position of the fan blade and the contour of the mountain) and the terrain features (such as the area with a slope greater than 15°) in the three-dimensional model, and automatically generates an obstacle avoidance path. In the complex terrain of the plateau, the algorithm calculates the optimal flight height in real time (such as maintaining a distance of more than 5m from the obstacle), ensuring the safety and efficiency of the inspection process.

[0045] In a second aspect, the embodiments of the present application also provide a monitoring method of a plateau area construction monitoring system based on an unmanned aerial vehicle and three-dimensional simulation technology, which comprises: S1. Before construction, a three-dimensional reference model is constructed and a risk is predicted.

[0046] Specifically, high-precision topographic mapping is performed, including the unmanned aerial vehicle carrying a laser radar or a tilt photography module, and the cm-level precision topographic data of the construction area is collected before the active period of frozen soil to generate a digital elevation model (DEM) and a digital orthophoto map (DOM).

[0047] The DEM is a solid ground model representing the ground elevation by using an ordered numerical array (X, Y, Z), which records the elevation value of each grid point by discretizing the earth's surface into a regular grid or an irregular triangular net to simulate the terrain undulation.

[0048] The DOM is an image dataset generated by correcting the projection difference of the scanned and processed digital aerial photograph or remote sensing image (monochrome or color) pixel by pixel, image mosaicking, and cutting according to the sheet range, using the digital elevation model (DEM).

[0049] When performing three-dimensional design integration, the BIM model is superimposed with the real scene three-dimensional model to construct a "digital twin" reference. For the plateau permafrost area, the influence of different construction schemes (such as ventilated roadbed and heat preservation guard path) on the thermal balance of frozen soil is analyzed through three-dimensional simulation to optimize the design parameters.

[0050] When performing geological disaster early warning, the hidden points such as landslides and debris flows are three-dimensionally modeled in combination with GIS+Beidou technology, and a deformation threshold is set.

[0051] S2. During construction, dynamic monitoring and quality control are performed.

[0052] Specifically, when tracking the progress, the unmanned aerial vehicle patrols according to the preset route every day, takes photos / videos of the construction progress, automatically compares the BIM model through image recognition technology, and generates a progress deviation report.

[0053] When quality detection is performed, the detection performed on the frozen soil roadbed includes a UAV carrying an infrared thermal imager, which monitors the temperature field distribution of the roadbed in real time to ensure the stability of the frozen soil layer. If local abnormal heating is found, insulation measures (such as covering insulation materials) are immediately triggered. The detection performed on the structural safety includes detecting the thickness of the tunnel lining and the verticality of the bridge pier column through laser point cloud scanning, with the deviation controlled within ±5 mm. The safety control includes a UAV carrying an AI vision algorithm, which identifies the wearing of safety equipment (such as safety helmets and oxygen masks) by construction personnel in real time and immediately corrects the illegal behavior through a voice intercom system.

[0054] S3. After construction, completion acceptance and operation and maintenance preparation are performed.

[0055] Specifically, the construction actual data is imported into the BIM model to generate a completed digital twin containing material, size, and installation position. The geometric information and texture information of the building are collected through measuring equipment (such as total station, laser scanner, etc.). The collected data is processed, including denoising, filtering, registration of point cloud data, and processing of texture information. A three-dimensional model is established using professional three-dimensional modeling software (such as 3DMAX, SketchUp, etc.), including the main structure of the building and auxiliary facilities. The processed texture information is mapped to the three-dimensional model to make the model more realistic. The model is optimized, including reducing the number of model surfaces and optimizing the model structure, to improve the rendering speed and display effect of the model.

[0056] Based on the three-dimensional model, the UAV inspection route is simulated, and the execution efficiency of operation and maintenance tasks such as photovoltaic panel cleaning and fan blade detection is optimized. Through reasonable path planning, the efficiency of operation and maintenance work is improved by avoiding repeated labor and invalid inspection of operation and maintenance personnel. Scientific path planning can ensure that operation and maintenance personnel work according to established safety specifications and operation procedures, reducing the risk of safety accidents and operation errors. Through timely and accurate operation and maintenance services, customer satisfaction and loyalty are improved, and the competitiveness of the enterprise is enhanced.

[0057] In summary, the present application can realize effective monitoring of construction projects by combining the self-directing cruise technology of unmanned aerial vehicles with three-dimensional simulation technology. The relevant departments plan to use unmanned aerial vehicles equipped with sensors and camera equipment to obtain ground image data through self-directing cruise flight and shooting, and by combining advanced machine vision and AI image analysis algorithms, high-precision plane and 3D model generation can be realized. The actual situation of the construction site is displayed in the form of a three-dimensional model, enabling construction management personnel to visually see the construction progress and discover problems in the construction process in a timely manner and make adjustments. At the same time, the UAV can also monitor the safety of the construction site. The UAV is equipped with various sensors such as wind speed and direction, which can monitor the weather conditions of the construction site in real time and issue an alarm when the wind speed exceeds the safety threshold, reminding the construction personnel to stop work and ensuring construction safety.

[0058] It should be noted that the above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent the advantages or disadvantages of the embodiments.

[0059] The terms "comprise", "comprising", "include", "including", "have" and "having" in the specification and claims of the present application and the above-described drawings are intended to cover a non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but can optionally include steps or units not listed, or can optionally include other steps or units inherent to the process, method, product or device. The terms "first", "second" and "third" and the like descriptions are used to distinguish different objects, and do not represent the order or limit the types of "first", "second" and "third".

[0060] In the description of the embodiments of the present application, "exemplary", "for example", "for instance" or "such as" are used to represent an example, illustration or description. Any embodiment or design scheme described as "exemplary", "for example" or "for instance" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. In fact, the words "exemplary", "for example", "for instance" or the like are intended to present the relevant concept in a specific manner.

[0061] In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in the text only describes the relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone, in addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0062] In some of the processes described in the embodiments of the present application, a plurality of operations or steps are included in a specific order, but it should be understood that these operations or steps can be executed or executed in parallel without the order in which they appear in the embodiments of the present application, and the sequence number of the operation is only used to distinguish each different operation, and the sequence number itself does not represent any execution order. In addition, these processes can include more or fewer operations, and these operations or steps can be executed in sequence or in parallel, and these operations or steps can be combined.

[0063] Those skilled in the art can clearly understand the above-mentioned embodiment method can be realized by means of software and the necessary general hardware platform, of course, can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a plurality of instructions for making a terminal device execute the method described in each embodiment of the present application.

[0064] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A construction monitoring system for high-altitude areas based on unmanned aerial vehicles (UAVs) and 3D simulation technology, characterized in that: The system includes an unmanned aerial vehicle (UAV) platform, a 3D modeling module, a data processing module, and a monitoring terminal. The unmanned aerial vehicle platform is equipped with a lidar and oblique photography module for collecting high-precision terrain data in the plateau region; The 3D modeling module constructs a digital elevation model and a digital orthophoto map based on the terrain data, and overlays them with the BIM model to form a digital twin benchmark; The data processing module performs real-time analysis of data during the construction process based on the digital twin benchmark, generating progress deviation reports, quality inspection results, and safety early warning information; The monitoring terminal is used to display and manage progress deviation reports, quality inspection results, and safety warning information.

2. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 1, characterized in that, The drone platform is also equipped with an infrared thermal imager to monitor the temperature field distribution of the frozen soil subgrade in real time and trigger insulation measures when local temperature rise anomalies are detected.

3. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 1, characterized in that, The data processing module includes an AI vision algorithm to identify the safety equipment worn by construction workers and to make real-time corrections through a voice intercom system.

4. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 1, characterized in that, The 3D modeling module also includes a geological disaster early warning submodule, which uses GIS and BeiDou technology to perform 3D modeling of landslide and debris flow hazard points and sets deformation thresholds to achieve early warning.

5. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 2, characterized in that, The infrared thermal imager has a monitoring accuracy of ±1℃, which is used to ensure that the temperature of the frozen soil subgrade is controlled within the design range.

6. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 3, characterized in that, The AI ​​vision algorithm uses the YOLO algorithm to automatically identify safety helmets and oxygen masks.

7. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 1, characterized in that, The data processing module is also used to generate a three-dimensional as-built model after construction, which includes material, size, and installation location information.

8. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 7, characterized in that, The three-dimensional as-built model is constructed by collecting geometric and texture information using a total station and a laser scanner.

9. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology as described in claim 1, characterized in that, The monitoring terminal supports drone inspection route planning based on the 3D model, which is used to optimize maintenance tasks such as photovoltaic panel cleaning and wind turbine blade inspection.

10. The construction monitoring system for plateau areas based on UAVs and 3D simulation technology according to claim 9, characterized in that, The UAV inspection route planning algorithm automatically calculates the optimal inspection path based on obstacle data and terrain features in the 3D model.

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