scholarly journals Utilizing drone technology in the civil engineering

2019 ◽  
Vol 14 (1) ◽  
pp. 27-37
Author(s):  
Matúš Tkáč ◽  
Peter Mésároš

Abstract An unmanned aerial vehicle (UAVs), also known as drone technology, is used for different types of application in the civil engineering. Drones as a tools that increase communication between construction participants, improves site safety, uses topographic measurements of large areas, with using principles of aerial photogrammetry is possible to create buildings aerial surveying, bridges, roads, highways, saves project time and costs, etc. The use of UAVs in the civil engineering can brings many benefits; creating real-time aerial images from the building objects, overviews reveal assets and challenges, as well as the broad lay of the land, operators can share the imaging with personnel on site, in headquarters and with sub-contractors, planners can meet virtually to discuss project timing, equipment needs and challenges presented by the terrain. The aim of this contribution is to create a general overview of the use of UAVs in the civil engineering. The contribution also contains types of UAVs used for construction purposes, their advantages and also disadvantages.

2020 ◽  
Vol 12 (17) ◽  
pp. 2738
Author(s):  
Benjamin Steven Vien ◽  
Leslie Wong ◽  
Thomas Kuen ◽  
Frank Courtney ◽  
Jayantha Kodikara ◽  
...  

Large structures and high-value assets require inspection and integrity assessment methodologies that ensure maximum availability and operational capabilities. Large membranes are used as floating covers at the anaerobic wastewater lagoons of Melbourne Water’s Western Treatment Plant (WTP). A critical function of this high-value asset pertains to the harnessing of the biogas gas generated at these lagoons as well as protecting the environment from the release of odours and greenhouse gases. Therefore, a proactive inspection and efficient management strategy are required to ensure these expensive covers’ integrity and continued operation. Not only is identifying the state of stress on the floating cover crucial for its structural integrity assessment, but the development of rapid and non-contact inspections will significantly assist in determining the “real-life” performance of the cover for superior maintenance management. This study investigates a strain determination method for WTP floating cover which integrates unmanned aerial vehicle (UAV)-assisted photogrammetry with finite element analyses to determine the structural integrity of these covers. Collective aerial images were compiled to form 3D digital models of the deformed cover specimens, which were then employed in computational and statistical analyses to assess and predict the strain of the cover. The findings complement the future implementation of UAV-assisted aerial photogrammetry for structural health assessment of the large floating covers.


2021 ◽  
Author(s):  
Kshitij Nair Nair ◽  
Sibi Chakkaravarthy S ◽  
Ramya Krishna Dhulipalla ◽  
Suresh Chandra Satapathy ◽  
Abhrankash Kanungo ◽  
...  

Abstract In this paper, a novel system is proposed to detect coconut trees from the images taken on an unmanned aerial vehicle (UAV). We propose a model based on the YOLOv4 Detector (CSPDarknet53) to achieve accurate prediction and fast speeds that enable real-time detection and object localization for a single object class-coconut tree. The pipeline is trained on two separate datasets of images from camera embedded UAV and images from multiple sources are fed into the multi-scale detector to predict bounding boxes and labels. A simple procedure is also proposed to enable detection on a larger scale, whereby the bigger image can be cropped into multiple single images and then fed into the detector. This model is compared statistically with the other state-of-the-art deep-learning models for object detection. After field studies and experiments on the images shot via a UAV (drone), it is proved that this system can efficiently and accurately detect coconut trees on a field at a speed of 15 frames per second when trained on 500 aerial images of the coconut trees.


Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 327 ◽  
Author(s):  
Riccardo Dainelli ◽  
Piero Toscano ◽  
Salvatore Filippo Di Gennaro ◽  
Alessandro Matese

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.


2020 ◽  
Vol 5 (1) ◽  
pp. 71-84
Author(s):  
Adhyta Harfan ◽  
Dipo Yudhatama ◽  
Imam Bachrodin

Metode Fotogrametri telah banyak digunakan dalam survei dan pemetaan. Seiring dengan kemajuan ilmu pengetahuan dan teknologi, metode fotogrametri saat ini berbasiskan pesawat tanpa awak atau yang lebih dikenal dengan UAV (Unmanned Aerial Vehicle). Kelebihan metode fotogrametri berbasiskan UAV untuk pengukuran garis pantai adalah memiliki resolusi spasial yang sangat tinggi dan dapat menjagkau daerah-daerah yang sulit dan berbahaya. Di samping itu juga dapat memberikan data foto udara terkini dengan sekala detail. Dalam penelitian ini membandingkan ketelitian horisontal antara hasil pengukuran garis pantai menggunakan metode fotogrametri berbasiskan UAV secara rektifikasi dengan GCP (Ground Control Point) maupun secara PPK (Post Processed Kinematic) dengan pengukuran garis pantai metode GNSS RTK (Real Time Kinematic). Hasil perhitungan ketelitian horisontal mengacu pada standar publikasi IHO S-44 tentang pengukuran garis pantai. Pemotretan dilakukan dengan ketinggian terbang 180 m, dengan tampalan depan dan samping 80%. Hasil perhitungan ketelitian horisontal foto udara terektifikasi 5 GCP, foto udara PPK dan foto udara PPK terektifikasi 1 GCP terhadap pengukuran garis pantai dengan metode GNSS RTK diperoleh nilai standar deviasi (σ) dan 95% selang kepercayaan (CI95%) masing-masing sebagai berikut: σ5gcp=10,989 cm dengan CI95% 16.8 cm < μ < 21.2 cm , σppk=26,066 cm dengan CI95% 26.5 cm < μ < 37 cm dan σppk1gcp=10,378 cm dengan CI95% 15.6 cm < μ < 19.8 cm. Kemudian terdapat 10 objek tematik berdasarkan Peta Laut Nomor 1 yang dapat diinterpretasi pada hasil orthomosaic foto udara.


Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 919 ◽  
Author(s):  
Hao Du ◽  
Wei Wang ◽  
Chaowen Xu ◽  
Ran Xiao ◽  
Changyin Sun

The question of how to estimate the state of an unmanned aerial vehicle (UAV) in real time in multi-environments remains a challenge. Although the global navigation satellite system (GNSS) has been widely applied, drones cannot perform position estimation when a GNSS signal is not available or the GNSS is disturbed. In this paper, the problem of state estimation in multi-environments is solved by employing an Extended Kalman Filter (EKF) algorithm to fuse the data from multiple heterogeneous sensors (MHS), including an inertial measurement unit (IMU), a magnetometer, a barometer, a GNSS receiver, an optical flow sensor (OFS), Light Detection and Ranging (LiDAR), and an RGB-D camera. Finally, the robustness and effectiveness of the multi-sensor data fusion system based on the EKF algorithm are verified by field flights in unstructured, indoor, outdoor, and indoor and outdoor transition scenarios.


SIMULATION ◽  
2018 ◽  
Vol 95 (6) ◽  
pp. 569-573
Author(s):  
Igor Korobiichuk ◽  
Yuriy Danik ◽  
Oleksyj Samchyshyn ◽  
Sergiy Dupelich ◽  
Maciej Kachniarz

The proposed observation model provides for calculating the probability of detection of different types of unmanned aerial vehicle (UAV) at a certain range with regard to their tactical and technical characteristics and security equipment capabilities. The comparison of the obtained values of generalized indicators of security equipment use efficiency is based on a specified criterion. To take into account factors that significantly affect a modeling object, calculations are carried out under specified conditions and restrictions. UAVs should be detected until a covering object gets in a swath width given the time required for countermeasures. Based on the software implementation of the algorithm we have evaluated the efficiency of use of hypothetical security equipment for detecting certain types of UAVs, and defined means of further use or improvement.


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