Uso de drones en actuaciones de enfermería en emergencias y catástrofes : una propuesta de formación

Objetivo: Diseñar un programa educativo para dar a conocer la utilidad de los drones y su aplicación por profesionales de Enfermería en la mejora de las actuaciones en emergencias y catástrofes. Metodología: Búsqueda bibliográfica basada en la evidencia científica más actualiza-da y, por otro lado, ha sido necesario consultar la legislación actual publicada en el Boletín Oficial del Estado para comprender el estado actual y evolución de los drones en España, con el fin de desarrollar una propuesta de formación dirigida a profesionales de Enfermería. Plan de Trabajo: Siete sesiones teórico-prácticas, siendo dos de inicio, cuatro de desarrollo y una de síntesis. Justificación: La formación a profesiona-les de Enfermería sobre el uso de drones en emergencias y catástrofes aporta numerosos beneficios en la gestión de éstas: respuesta eficiente en cuanto a organización y activación de recursos, comunicación adecuada con los pacientes, anticipación a la llegada de los Servicios de Emergencias, entre otros.Objective: Design an educational program to make visible the usefulness of drones and their application for nursing professionals in the im-provement of emergency and disaster situations. Methodology: Bibliographic search based on the most updated scientific evidence and, on the other hand, it has been necessary to consult the current legislation published in the Official State Gazette to understand the current status and evolution of drones in Spain, in order to develop a training proposal aimed at nursing professionals. Work Plan: Seven theoretical-practical sessions, two being of beginning, four of development and one of synthesis. Justification: Training nurses on the use of drones in emergencies and disasters provides numerous benefits in the management of these: efficient response in terms of organization and activation of resources, adequate communication with patients, anticipation of the arrival of emergency services, among others

Geometric Quality Assessment of a Modular House using BIM and Photogrammetric Point Clouds

As-built documentation of modular structures is an important set of records for a project, that consist of construction drawings and specifications, project design modifications, prefabrication, and component assembly. In particular, manual geometric quality assessments of a structure’s prefabricated components are generally fraught with errors, making it extremely difficult to compare the as-built construction with the specified drawings, which affects the project. Furthermore, if the prefabricated components are manufactured with errors, this can result in construction schedule delays and high additional costs due to rework. Several technologies, such as point cloud data generated using laser sensors and LiDAR, have been developed to verify as-built construction accuracy. However, such technologies have been associated with high equipment costs, equipment mobilization difficulties, high computing powers, long-duration to generate models, and the need for expertise. The photogrammetric approach for point cloud generation has advantages in terms of cost, easiness of data collection, and shorter time to generate models. However, due to a lack of capabilities to generate high-quality, accurate point clouds, there were minimal research studies. However, there was an advancement in the photogrammetric approach in terms of software recently. This research aims to verify an advancement of the photogrammetric approach for generating a 3D point cloud model of an existing structure, especially in modular construction, using pictures taken by a digital handheld camera, followed by refinement of the model, and an accuracy assessment, compared to the 3D BIM model. The proposed approach consists of taking photographs of the structure at equidistant viewpoints around the structure and processing the images for the point cloud generation. Furthermore, geometric quality assessment was conducted by comparing point clouds’ dimensions with 3D BIM model dimensions to analyze the dimensional accuracy of the point clouds. This research demonstrated the development of an accurate point cloud model of a modular house with a photogrammetric approach through numerous trials and errors. The error percentage of the best model was a range of -0.6133% to 1.0514% for structural geometry and 0.7250% to 0.0011% for building components. Additionally, challenges faced during this research and reasons for model generation failure were analyzed, and the lessons learned from it were documented to establish a foundation for future research. This study demonstrated that using a photogrammetric approach to develop point cloud models in the modular construction industry can be useful for geometric quality inspection of the structural elements, and several other purposes. The study also revealed that photogrammetric point cloud models could be generated with high accuracy, at a low cost with a reasonable time and effort

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable

Influência da calibração in situ na fototriangulação de imagens adquiridas por VANT com posicionamento direto

Orientador: Professor Edson Aparecido MitishitaDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências da Terra, Programa de Pós-Graduação em Ciências Geodésicas. Defesa : Curitiba, 28/07/2021Inclui referências: p. 89-95Resumo: Com o desenvolvimento de sensores e de plataformas de baixo custo, a extração de dados espaciais por Fotogrametria vem se tornando cada vez mais usual, visto que o uso de sistemas fotogramétricos embarcados em VANT (Veículos Aéreos Não Triupulados) e do método Structure from Motion - Multi-view Stereo (SfM-MVS) possibilitam um alto grau de automação no mapeamento de superfícies. O sistema fotogramétrico a bordo de um RPAS consiste em uma câmara digital e em sensores de posição e orientação (GNSS/IMU). Desse modo, para que seja possível determinar diretamente os Parâmetros de Orientação Exterior, é necessário que seja realizada uma calibração desse sistema. Portanto, faz-se necessário o desenvolvimento de estudos com o intuito de investigar a exatidão posicional de nuvens de pontos obtidas utilizando técnicas de pré-calibração de câmaras em imagens obtidas com VANT integrados a medidas da posição direta do sensor com alta precisão. Desta forma, o principal objetivo deste estudo consiste em analisar a influência da estimação dos Parâmetros de Orientação Interior por autocalibração e por calibração in situ com sub-bloco de imagens na qualidade posicional da extração de dados geoespaciais, associadas a medidas diretas da posição da câmara. Para isso foi realizado um estudo de caso no município de Curitiba (PR), no bairro Cidade Industrial. O levantamento fotogramétrico foi executado com o VANT DJI Phantom 4 Pro, compondo três faixas de voo paralelas, com 60 imagens aéreas verticais e sobreposição longitudinal de 80%. O receptor GNSS-PPK utilizado nessa pesquisa fornece a posição do sensor com precisão de 10 cm nas componentes horizontais e 20 cm na componente vertical. A etapa de apoio de campo, para determinação das coordenadas geodésicas de pontos no terreno, foi realizada por posicionamento cinemático com par de receptor GNSS da Topcon, modelo Hiper SR. Para os processamentos fotogramétricos de autocalibração e Orientação Integrada de Sensores com o uso da metologia SfM, utilizou-se o programa Agisoft Metashape v 1.5. Já os procedimentos de Orientação Integrada do Sensor e calibração in situ com subbloco de imagens usando Fotogrametria tradicional, são executadas no programa Erdas Imagine e CALIBRAV da UFPR. Considerando os experimentos realizados no Metashape, a execução da calibração in situ com sub-bloco de imagens não permitiu melhorar a qualidade da extração de informações tridimensionais em experimentos sem pontos de apoio. Para os processamentos realizados com Fotogrametria Tradicional, o experimento de Orientação Integrada de Sensores usando os Parâmetros de Orientação Interior obtidos na calibração in situ, apresentou melhora de 19% em planimetria e de 86% em altimetria comparado ao experimento de Orientação Integrada de Sensores realizado com Parâmetros de Orientação Interior da autocalibração do Metashape.Abstract: The extraction of spatial data by photogrammetry is becoming more and more usual due to the development of low-cost sensors and platforms since the use of photogrammetric systems onboard UAV (Unmanned Aerial Vehicle) and the Structure from Motion - Multi-view Stereo method enable a high degree of automation in surface mapping The photogrammetric system onboard an UAV consists of a digital camera and position and orientation sensors (GNSS/IMU). Thus, calibration of this system is required for the direct determination of the Exterior Orientation Parameters. Therefore, it is necessary to develop studies aimed at investigating the positional accuracy of point clouds obtained using camera pre-calibration techniques in images obtained with UAV integrated with direct sensor position measurements with high accuracy. Thus, the main purpose of this study is to analyze the influence of the estimation of the Interior Orientation Parameters by autocalibration and by in situ calibration with sub-block of images on the positional quality of geospatial data, associated with direct camera position measurements. To this end, a case study was conducted in Curitiba (PR), in the Cidade Industrial neighborhood. The photogrammetric survey was performed with the RPAS DJI Phantom 4 Pro, composing three parallel flight strips, with 60 vertical aerial images and a longitudinal overlap of 80%. The GNSS-PPK receiver used in this research provides the sensor position with a precision of 10 cm in the horizontal coordinates and 20 cm in the vertical coordinate. The field survey stage, for determining the geodetic coordinates of points on the terrain, was performed by kinematic positioning with a Topcon GNSS receiver, model Hiper SR. Agisoft Metashape v 1.5 program was used. for the photogrammetric processing of selfcalibration and Integrated Sensor Orientation using the SfM method. Integrated Sensor Orientation and in-situ calibration procedures with sub-block of images using Traditional Photogrammetry are performed in Erdas Imagine and UFPR's CALIBRAV programs. Considering the experiments performed on Metashape, the in-situ calibration with sub-block images did not improve the quality of three-dimensional information extraction in experiments without Ground Control Points. For the Bundle Adjustment performed with Traditional Photogrammetry, the Integrated Sensor Orientation experiment using Interior Orientation Parameters obtained in the in situ calibration showed an improvement of 19% in planimetry and 86% in altimetry compared to the Integrated Sensor Orientation experiment performed with Interior Orientation Parameters from the Metashape self-calibration