Qualitative fault tree for the analysis of slope stability loss in road infrastructure

TRA Lisbon 2022 Conference Proceedings Transport Research Arena (TRA Lisbon 2022),14th-17th November 2022, Lisboa, PortugalLandslides are natural hazards all over the world, being the loss of slope stability in transport infrastructures considered small-scale landslides causing economic and human losses. Although there are many examples in the literature for the general analysis of landslides susceptibility, little information is available to analyze slopes at a local scale. The objective of this work is to identify all the slopes in road infrastructure, select those located in landslide susceptibility areas and apply a qualitative fault tree, also defined in this work, to determine the factors which can cause the slope stability loss. The results obtained are useful for each critical slope.Agencia Estatal de Investigación | Ref. PID2019-108816RB-I00Agencia Estatal de Investigación | Ref. PRE2020-09622

Zeolites and ordered porous solids: fundamentals and applications

Pérez Pariente, J.; Martínez Sánchez, MC. (2011). Zeolites and ordered porous solids: fundamentals and applications. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/11205Archivo delegad

External multi-modal imaging sensor calibration for sensor fusion: A review

Multi-modal data fusion has gained popularity due to its diverse applications, leading to an increased demand for external sensor calibration. Despite several proven calibration solutions, they fail to fully satisfy all the evaluation criteria, including accuracy, automation, and robustness. Thus, this review aims to contribute to this growing field by examining recent research on multi-modal imaging sensor calibration and proposing future research directions. The literature review comprehensively explains the various characteristics and conditions of different multi-modal external calibration methods, including traditional motion-based calibration and feature-based calibration. Target-based calibration and targetless calibration are two types of feature-based calibration, which are discussed in detail. Furthermore, the paper highlights systematic calibration as an emerging research direction. Finally, this review concludes crucial factors for evaluating calibration methods and provides a comprehensive discussion on their applications, with the aim of providing valuable insights to guide future research directions. Future research should focus primarily on the capability of online targetless calibration and systematic multi-modal sensor calibration.Ministerio de Ciencia, Innovación y Universidades | Ref. PID2019-108816RB-I0

SWE bridge: software interface for plug & work instrument integration into marine observation platforms

The integration of sensor systems into marine observation platforms such as gliders, cabled observatories and smart buoys requires a great deal of effort due to the diversity of architectures present in the marine acquisition systems. In the past years important steps have been taken in order to improve both standardization and interoperability, i.e. the Open Geospatial Consortium’s Sensor Web Enablement. This set of standards and protocols provide a well -defined framework to achieve standardized data chains. However a significant gap is still present in the lower -end of the data chain, between the sensor systems and the acquisition platforms. In this work a standard s -based architecture to bridge this gap is proposed in order to achieve plug & work, standardized and interoperable acquisition systems.Award-winningPostprint (published version

Automatic detection to inventory road slopes using open LiDAR point clouds

The transport infrastructure of a country facilitates the development and growth of its economy and improves the quality of life of its inhabitants. Increasing its resilience to different types of risks to improve performance is becoming more important. In the current context of climate change, natural hazards are more severe and frequent. In this article, we focus on rockfall as a natural hazard for roads that occurs in small areas in the vicinity of natural or cut slopes, causing road safety problems by invading part of the road. This article aims to inventory the slopes along the road, identifying the area of the road which would be invaded in case of a rockfall. A methodology divided into two blocks is proposed. First, for slope detection and inventory, an algorithm is developed based on open LiDAR point clouds analysis. The second block consists of estimating the invaded road area if a rockfall occurs on each of the inventoried slopes, using a combination of RockGIS software and the Monte Carlo method. The methodology was applied in five case studies: three sections on motorways and two sections on national roads. The results obtained for slope detection show higher rates in the case studies analyzing motorways, with a precision of 100%, a recovery rate of greater than 93.4%, and an F1 score of greater than 0.96. The results in the invaded area of the road show that 11 slopes would cause a total cut of the motorway in one of the directions if a rockfall occurs. These results are useful for infrastructure managers to remotely obtain an inventory of road slopes and know which of them would affect road safety. Also, the results can serve as input for the Intelligent Transportation System and allow the exchange of information under the Building Information Model approach.Ministerio de Ciencia, Innovación y Universidades | Ref. PID2019-108816RB-I00Ministerio de Ciencia, Innovación y Universidades | Ref. PRE2020-096222European Commission | Ref. H2020, n. 95533

Comparing Mobile and Aerial Laser Scanner point cloud data sets for automating the detection and delimitation procedure of safety-critical near-road slopes

An inappropriately maintained road cut-slope is likely to fail, resulting in landslides or falling rocks that compromise road safety. Thus, road managers need to know the location of dangerous slopes along the road in order to prevent these events from happening. In this article, we compare two different approaches for conducting the digitization of the road environment and the automatic detection and delimitation of road slopes: Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS). The point clouds obtained using the first kind of devices are dense, rich in detail and generated from a ground perspective; the second type of scanners produce less dense clouds from a zenithal perspective. We explore what is the effect of the point cloud density and scanner point of view over the slope detection procedure. Two road segments from the Spanish A55 and A52 highways were used as study zones, and a total of 28.61 km were analyzed. Better detection and delimitation results were achieved when using the ALS data and its corresponding algorithm. It was observed that the higher point density and detail of the MLS clouds were not an advantage for the slope detection task, and that measuring the road from a terrestrial perspective affected in a negative way during the detection process: the crest of the slopes often remained unmeasured, hidden behind vegetation or man-made elements, thus resulting in the slopes not being complete in the MLS clouds. Meanwhile, the whole slope structure is scanned when the scene is measured from an aerial perspective, henceforth obtaining better detection rates despite the relatively low resolution. The findings of this study provide valuable information in the field of road asset management, and help road managers make decisions when choosing what technology to use for the data gathering process.Agencia Estatal de Investigación | Ref. PID2022-140662OB-I00Universidade de Vigo/CISU

Generador de currículos en diferentes estilos: aplicación web

Este proyecto recoge la creación de una aplicación web destinada a realizar el Currículum Vitae en diferentes formatos de forma personalizada. Dicha aplicación servirá de soporte a distintos usuarios, que podrán gestionar sus datos profesionales de forma automatizada. Se les permitirá generar distintos formatos y estilos del mismo sin necesidad de rellenar sus datos de forma repetitiva y ajustándose a la normativa necesaria para el mismo. Proporciona una herramienta colaborativa en la cual los diferentes usuarios podrán crear y compartir estilos y secciones del documento, manteniendo siempre la privacidad en sus datos. Para esta aplicación se ha incluido a modo de ejemplo el formato Europeo requerido en los currículos del personal docente de la universidad UCM (Universidad Complutense de Madrid). [ABSTRACT] This project includes the creation of a web application designed to make your CV in different formats in a personalized way. This application will support different users, they can automatically manage their business data. They will generate different formats and styles of the same without filling your data on repetitive times and according to the regulations necessary for it. It provides a collaborative tool in which different users can create and share styles and sections of the document, while maintaining privacy in their data. For this application has been included as an example the European format required in the curricula of the faculty of the UCM University (Universidad Complutense de Madrid)

Heuristic generation of multispectral labeled point cloud datasets for deep learning models

Abstract. Deep Learning (DL) models need big enough datasets for training, especially those that deal with point clouds. Artificial generation of these datasets can complement the real ones by improving the learning rate of DL architectures. Also, Light Detection and Ranging (LiDAR) scanners can be studied by comparing its performing with artificial point clouds. A methodology for simulate LiDAR-based artificial point clouds is presented in this work in order to get train datasets already labelled for DL models. In addition to the geometry design, a spectral simulation will be also performed so that all points in each cloud will have its 3 dimensional coordinates (x, y, z), a label designing which category it belongs to (vegetation, traffic sign, road pavement, …) and an intensity estimator based on physical properties as reflectance.Ministerio de Ciencia, Innovación y Universidades | Ref. PCI2020-120705-

A top-down approach for a multi-scale identification of risk areas in infrastructures: particularization in a case study on road safety

Introduction: Transport infrastructures have an important function in society and the development of a country. In Spain, the most used modes of traveler transport are road and rail, far ahead of other means of transport such as air or maritime transport. Both rail and road infrastructures can be affected by numerous hazards, endangering their performance and the safety of users. This study proposes a methodology with a multiscale top-down approach to identify the areas affected by fire, landslide, and safety in road and rail infrastructures in Galicia (Northwest Spain).Methodology: The methodology is developed in three steps, coinciding with the three scales considered in this work: network-, system-, and object-level. In the first step, risk areas are identified and prioritized, resulting in the most critical safety risk in a motorway section. This area defines a study scenario composed of a location (A-55 motorway) and the associated risk (road safety). In the second step, the road safety factors within this scenario are selected, hierarchized, and weighted using a combination of Multi-Criteria Decision-Making methods including the Analytical Hierarchy Process and the Best–Worst Method. Finally, a risk map is generated based on the weighting of infrastructure-related safety factors and compared to real historical accident data for validation. The methodology is based on road and risk assessment standards and only information in the public domain is used.Results: Results show that only 3 segments out of 153 were classified incorrectly, which supports a probability higher than 95% of agreement with real data (at 5% significance level). In a conclusion, the overall methodology exhibits a high potential for hazard prevention and road-safety enhancement.Agencia Estatal de Investigación | Ref. PID2019-108816RB-I00Agencia Estatal de Investigación | Ref. PRE2020-09622