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The chancellor highlight that “innnovación occurs through the transfer of knowledge and universities are the most important research centers in the country”. The University of Salamanca was the main protagonist of the last day of the second cycle of Innova Club, a forum for reflection and analysis focusing this time on the “important” role of …
The University of Salamanca designed a robotic helicopter that captures thermal images. It study the energy efficiency and structural damage to buildings and also allows to reconstruct three-dimensional monuments. A multidisciplinary team from the University Of Salamanca (USAL), composed by surveyors, physicists, mathematicians and industrial and mining engineers are working from Ávila developing a research …
The new system will be adapted for people with disabilities. For two years, the Group of Information Technologies for the Heritage Documentation at the University of Salamanca (TIDOP) has worked to develop the project on laser surveying and virtual viewer for the metric documentation and cataloging of the Walls of Ávila, called “Virtual Wall”. It …
Pindal cave, listed as World Heritage by UNESCO since July of this year, can tour in 3D thanks to a research by a team of professors at the Polytechnic School of Avila, who heads Diego González Aguilera. This team, known as Tidop Research Group (Information Technology for Heritage Documentation) just completed under the supervision of …
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E.P.S de Avila |
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Arturo Farfán Martín
Doctor from the University of Salamanca (2012). He is Professor of the University in the Department of Cartographic and Terrain Engineering of the Higher Polytechnic School of Ávila in the Degree of Mining and Energy Technology Engineering. He is currently directing several doctoral theses in the energy field within the Doctoral program “Geotechnologies applied to Construction, Energy and Industry”. Thanks to this, in recent years, highlights its development in the field of research with numerous scientific publications.
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El uso de la termografía infrarroja com
o técnica sobradamente provada para la inspección de edificios y localización de patologías como fugas de aire, humedades, etc. Nos permite realizar un examen visual “in-situ” de calidad de los objetos de estudio gracias a la posibilidad de visualizar en tiempo real los resultados pudiendo detectar sin dificultad los desperfectos o elementos característicos de estos. Estas técnicas de medición cualitativa nos proporcionan la posibilidad de realizar inspecciones rápidas y eficaces sin contacto directo con el objeto y de forma no destructiva, lo que disminuye tanto el riesgo de incidentes para los operarios como los daños producidos en los propios objetos de estudio ocasionados por otras técnicas intrusivas. Además, también se ha demostrado la utilidad de la termografía infrarroja como técnica puramente de medida a través de su utilización para el cálculo de propiedades termofísicas de materiales tales como difusividad y transmitancia térmica.
En el caso de termografía cualitativa, las publicaciones existentes tratan de estudios realizados in-situ, principalmente en edificios históricos o elementos del patrimonio cultural, mientras que los estudios cualitativos se realizan, en la mayor parte de los casos, en laboratorios sobre muestras de tamaño limitado. En aquellos casos en los que se han realizado estudios termográficos cuantitativos sobre edificios in-situ, los valores de temperatura son empleados con el objetivo de obtener propiedades termofísicas (conductancia térmica) reales del cerramiento, sin embargo su distribución espacial no es considerada.
Conjugar ambas aplicaciones permitirá la automatización del cálculo de pérdidas de calor a partir de las temperaturas medidas con una cámara termográfica. De este modo, no solo se usa la termografía para representar el estado de la pared, sino que también se usan los valores de temperatura contenidos en la termografía para la extracción de parámetros métricos del edificio en estudio, por lo que la hibridación de la información termográfica con el material cartográfico de precisión permitiría extraer la geometría real del objeto de estudio con textura termográfica, pudiendo así realizar mediciones precisas de los elementos de interés directamente sobre el resultado obtenido.
Estudios como el publicado por EuroACE en 2010 colocan la mejora de la eficiencia energética en edificación en cabeza de las acciones necesarias para la reducción de emisiones de gases del efecto invernadero y gasto energético, así como para servir de empuje a la generación de empleo. Especial es el caso del parque de edificios ya construidos, la mayoría procedente de los años 1940-80, con normativa inexistente y recursos escasos. En ellos las obras de rehabilitación energética pueden suponer un ahorro de hasta el 75% en consumo de energía. En España existen 13 millones de viviendas susceptibles de intervención, cuya rehabilitación energética supondría una reducción de las emisiones del sector del 34% con respecto al año 2001.
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The use of infrared thermography as a widely tested technique for building inspection and location of pathologies such as air leakage and moisture allows the performance of quality “in-situ” visual examination of the objects under study due to the possibility of obtaining real-time results, being able to detect without difficulty damages or material characteristics. This qualitative measurement technique provides the capability of doing quick, effective and non-destructive inspection without direct contact with the object under study, decreasing the risk of incidents to operators and the damage of the objects comparing with other intrusive techniques. Furthermore, the utility of infrared thermography as a measurement technique has been proved by its use for the determination of the thermophysical properties of materials such as diffusivity and thermal transmittance.
In the qualitative approach, some authors have performed in-situ studies, mainly in historical buildings or cultural heritage elements, whereas quantitative studies are performed mainly in laboratories with limited size samples. In those cases where quantitative thermography studies were performed in-situ, temperature values were employed in order to obtain the real thermophysical properties (thermal conductance) of the building envelope, but their spatial distribution is not considered.
Combine both applications will enable the automation of the heat loss computation from the measured temperatures with a thermographic camera. Thus, the thermography is not only used to represent the state of the wall, but also temperature values represented on the thermography for extracting the metric parameters of the study object so the hybridization of the thermographic information with precise cartographic material would allow to extract the actual geometry of the object of study with thermal texture, being able to make accurate measurements of the elements of interest directly on the obtained results.
Studies such as the one published by EuroACE in 2010, places improved energy efficiency in building construction at the top of the list of actions that need to be taken to reduce greenhouse gases and energy costs, in addition to acting as a stimulus to generate employment. In particular is the case of existing buildings stock, most of which dates back to the period 1940-80, constructed using non-existent standards and scarce resources. Here, energy refurbishment works could represent a saving of up to 75% in energy consumption. In Spain there are 13 million homes that could be the subject of intervention, where energy refurbishment could result in a reduction in sector emissions of 34% compared to 2001.
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In urbanized Western Europe trees are considered an important component of the built-up environment. This also means that there is an increasing demand for tree inventories. Laser mobile mapping systems provide an efficient and accurate way to sample the 3D road surrounding including notable roadside trees. In this research line, a processing chain aiming at the extraction of tree locations and tree sizes from laser mobile mapping data is reached.
Such steps, in combination with code optimization are expected to be sufficient to reach the final goal of automatized estimation of features sampled by mobile mapping at a rate that matches the acquisition speed and at a quality that matches the result of a human operator.
Julia Aramendi Picado
Julia Aramendi has a BA degree in Archaeology from the Complutense University of Madrid (2010-2014). She received a scholarship from La Caixa for postgraduate studies abroad to perform the MSc of Human Anatomy and Evolution (2014-2015) at the University of York (United Kingdom). Then, she received a FPU grant from the Spanish Ministry of Education (2016-2021) to investigate the biomechanics of the long bones of some of the African hominin species through the use of three-dimensional models, and the application of geometric morphometrics and machine learning techniques. Since 2012, she has participated in the excavations carried out in Olduvai under the direction of TOPPP (The Olduvai Palaeoanthropology and Paleoecology Project), as well as in the subsequent study of the archaeological materials. She has collaborated in teaching in the Department of Prehistory of the Complutense University and the Institute of Evolution in Africa (IDEA). Since 2015, she has participated in a project aimed at the application of virtual reconstruction techniques and geometric morphometrics to the study of taphonomic marks. During her academic training she has made several research stays including a year of study in Mainz (Germany), and short stays in Toulouse, Poitiers (France) and York (United Kingdom). She has also participated in the archaeological campaigns of Pinilla del Valle (Madrid) and Cuesta de la Bajada (Teruel). She worked as a research assistant for the classification of the faunal material found at the Neanderthal site of Neukmard-Nord 2 during her stay in Germany. During the past years she has contributed to several Archaeology and Human Evolution conference sessions. Her research is reflected in several publications in high-impact journals.
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Lloyd A. Courtenay
Arqueólogo por la Universidad Complutense de Madrid (2017), especializado en aplicaciones estadísticas para el estudio de los restos faunísticos en los yacimientos arqueológicos y paleontológicos. En el año 2019 obtuvo un Máster en Ciencias del Cuaternario y Evolución Humana (ERASMUS MUNDUS) por la Universidad Rovira i Virgili (URV, Tarragona), además realizando una estancia en el Muséum National d’Histoire Naturelle (Paris). A lo largo de su Máster, Lloyd empezó a trabajar y especializarse en temas de Inteligencia Artificial y Estadística Robusta aplicado al procesado de modelos 3D en algunos de los yacimientos arqueológicos de la Garganta de Olduvai (Tanzania). Su trabajo fin de Máster obtuvo el Premio Extraordinario por la URV y la máxima calificación, finalmente presentado en el Institut de Paléntologie Humaine en Paris. Ahora mismo se encuentra realizando su tesis doctoral en la Universidad de Salamanca, y en colaboración con la Universidad Complutense, sobre temas de aprendizaje computacional e estadística robusta para el procesado de modelos 3D. Está financiado por el Ministerio de Ciencia e Innovación con un contrato pre-doctoral tipo FPI (Ref.: PRE2019-089411)
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Lloyd A. Courtenay
Archaeologist formed in the Complutense University of Madrid (2017), specialised in statistical applications for the study of faunal remains in archaeological and palaeontological sites. In 2019 Lloyd finished his Master’s degree in Quaternary Sciences and Human Evolution (ERASMUS MUNDUS) in the Rovira I Virgili University (URV, Tarragona), with an overseas stay in the Muséum National d’Histoire Naturelle (Paris). Throughout his Master’s degree, Lloyd began working and specialising in Artificial Intelligence and Robust Statistical applications applied to 3D models from the archaeological sites of the Olduvai Gorge (Tanzania). His Master’s Thesis won the extraordinary prize from the URV, as well as the highest grade, finally presented in the Institut de Paléntologie Humaine in Paris. Lloyd is currently working on his doctorate in the University of Salamanca, in collaboration with the Complutense University of Madrid, about computational learning and robust statistics for the processing of 3D models. Lloyd is funded by the Spanish Ministry of Science and Innovations, with an FPI pre-doctoral contract (Ref.: PRE2019-089411).
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Equipar drones con sensores láser, detectores de obstáculos y sistemas de control remoto permite obtener de forma segura y fiable los modelos tridimensionales de escenarios críticos, entendiendo como escenarios críticos todos aquellos escenarios en los que una persona correría peligro realizando los trabajos.
Este tipo de escenarios abarcan desde grutas angostas y estrechas a las que es difícil acceder, hasta escenarios industriales complejos, como subestaciones eléctricas, en las que existen riesgos de descargas eléctricas, salas de calderas, edificios con problemas estructurales etc.
A pesar de ser lugares críticos, su mantenimiento e inspección es un aspecto clave en el campo del control preventivo de averías y deformaciones, por lo que obtener el modelo tridimensional de estos lugares es fundamental. En este sentido, los drones terrestres, cada vez más sofisticados, permiten integrar escáner láser terrestre para capturar el entorno, asi como detectores de obstáculos y diferentes sistemas de comunicación, de modo que pueden moverse de forma autónoma o ser teledirigidos de forma remota.
Hasta el momento se ha investigado la integración de drones terrestres y escáner láser utilizando dos metodologías de trabajo diferentes, según el grado de precisión y detalle que se necesite y dependiendo de las dimensiones del espacio en el que se esté trabajando.
Finalmente, se está investigando la manera de combinar los modelos tridimensionales obtenidos por los drones terrestres con datos procedentes de drones aéreos equipados con cámaras fotográficas o cámaras termográficas. Combinar ambos modelos es esencial para obtener una cobertura total de la escena de estudio y poder detectar anomalías en cualquier lugar. Ésta línea de acción se está introduciendo para controlar subestaciones eléctricas y plantas solares fotovoltaicas ya que en ambos casos es posible detectar zonas con un calentamiento anormal que indiquen un funcionamiento que deberá revisarse.
Land drones can be armed with different devices such as terrestrial laser scanner, obstacle detectors or remote control systems, in order to provide accurate 3D models of unattended or critical environments in a safe way.
Environments like narrow caves that are difficult to access, electrical substations where there are risk of electric shock, boiler rooms or buildings with structural problems are considered critical environments for human operators due to the danger they entail.
Despite being critical spaces, its maintenance, inspection and control are essential to prevent damages and detect breakdowns, so accurate three-dimensional models are indispensable. For this purpose, terrestrial drones allow the integration of terrestrial laser scanners to capture the environment, as well as obstacle detectors and different communication systems, so that they can be autonomous vehicles or remote-controlled vehicles.
Depending on the accuracy needed and the dimensions of the study case, two different combinations of technologies have been explored, both combining laser scanner with land drones.
To complete this research line, we are working in different methodologies to combine 3D models obtained with land drones and data obtained with aerial drones equipped with conventional cameras or thermo graphic cameras.
Mix both kind of models make the three-dimensional model much more complete and it is possible to detect pathologies in almost everywhere. Some of this process has been used with success in electrical substations and photovoltaic solar plants, detecting, for example, anomalies in some panels.
Mariano González de Soto
He received the PhD in Science and Technology of the Environment and Processes from the University of León (2016), he developed his thesis on the reduction of energy and contaminants in precision agriculture using robotic systems, which was awarded in the Call for “Doctor ULE-TCUE”. He studied a Master’s Degree in Renewable Energy at the University of León (2010) in which he researched about hydrogen and renewable energies. He previously studied Electronics Engineering (2009) and I.T. of Telecommunications specialization in electronic systems (2007) at the University of Valladolid. He has several scientific publications in international and national journals, lectures in congresses and chapters in scientific books. He has worked in the Spanish National Research Council (CSIC) (2012-2016) participating in a European project of robotics applied to effective agriculture and in another national on integral automation of agriculture. Later he joined at the Spanish Centre for Energy, Environment and Technology (CIEMAT) (2016-2018) to collaborate in a national project on hybrid energy storage. In 2019 he joined the TIDOP group, as a postdoctoral researcher, to participate in the research of intelligent systems for road safety, job that since 2020 he combines with that of a contracted professor at the Catholic University of Ávila. In addition, in 2018 he started an entrepreneurship project based on Industry 4.0 applied to organic eggs production, which participated and was awarded in the “Entrepreneurship Program 1,131” of the “Tatiana Pérez de Guzmán el Bueno Foundation”.
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Damián Ortega Terol
PhD en Geotecnologías Aplicadas a la Construcción, Energía e Industria (2018, Universidades de Salamanca y Vigo) con mención “cum laude” tras la finalización de su tesis doctoral titulada: “Innovación en el desarrollo de herramientas basadas en software libre para la explotación de imágenes aéreas y espaciales adquiridas con sensores de última generación”. Completa su formación académica con las titulaciones del graduado en Ingeniería Geomática y Topografía (2013, Universidad de Salamanca), Master Universitario en Geotecnologías Cartográficas en Ingeniería y Arquitectura (2011, Universidades de Salamanca y Valladolid), Ingeniero en Geodesia y Cartografía (2001, Universidad Politécnica de Valencia) e Ingeniero Técnico en Topografía (1998, Universidad Politécnica de Valencia). Posee una amplia experiencia en la programación de herramientas geomáticas basadas en software libre desarrollada en los diferentes puestos que ha ocupado: empresa pública Tragsatec (2001-2008), funcionario grupo A1 de la Escala de Técnicos Facultativos Superiores de los OOAA del Ministerio de Medio Ambiente (2008-2016) y en su reciente incorporación como funcionario de carrera en el Instituto Geográfico Nacional del Ministerio de Fomento (2016-actualidad).
Líneas de investigación:
Damián Ortega Terol
PhD in Geotechnologies Applied to Construction, Energy and Industry (2018, Universities of Salamanca and Vigo) with a “Cum laude” mention of his doctoral thesis entitled: “Innovation in the development of tools based on free software for the exploitation of aerial and spatial images acquired with state-of-the-art sensors ”. He completed his academic training with the graduate degrees in Geomatics and Topography Engineering (2013, University of Salamanca), Master’s Degree in Cartographic Geotechnologies in Engineering and Architecture (2011, Universities of Salamanca and Valladolid), Engineer in Geodesy and Cartography (2001, University Polytechnic of Valencia) and Technical Engineer in Topography (1998, Polytechnic University of Valencia). He has extensive experience in programming geomatic tools based on free software developed in the different positions he has held: public company Tragsatec (2001-2008), official group A1 of the Scale of Superior Facultative Technicians of the OOAA of the Ministry of the Environment (2008-2016) and in his recent incorporation as a career civil servant at the National Geographic Institute of the Ministry of Development (2016-present).
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Mario Soilán Rodríguez
He received the M.Sc. degree in industrial electronics and automation engineering from the University of Vigo, in 2014. He obtained his PhD in Applied Geotechnologies in Construction, Energy and Industry at University of Vigo in 2018, with International Mention, Extraordinary PhD Award, and Abertis International Award 2018 to the best PhD thesis in road safety. He has been a visiting researcher at the Urban Modelling Group, University College Dublin, Ireland (2016), at the Photogrammetry and Remote Sensing Group, ETH Zürich, Switzerland (2017), and at the Remote Sensing Group, TU Delft, The Netherlands (2018). He is currently a Juan de la Cierva postdoctoral researcher. His research interests include automatic processing of LiDAR data for mobility and traffic safety applications, and infrastructure analysis.
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Throughout history wolves and humans have had a conflictive and complex love-hate relationship. On one hand, wolves are frequently the culprits of livestock predation, creating tension with local farmers and landowners, while on the other, their domestic relative the dog is considered a cultural extension of the family. Due to the attacks produced on livestock, tension has formed over the years among rural populations. Unfortunately, Castilla y León is one of the country’s most affected areas by wolf attacks on livestock; with Ávila being a focal point for most of these damages. 
The objectives of this line of research are to use artificially intelligent algorithms to model and study the impact of wolves in the province of Ávila. Using spatial data, statistical Geographical Information System (GIS) approaches and Machine/Deep Learning, we hope to provide a new perspective to the study of wolf activities and attacks on local livestock. 
The advantages of artificially intelligent algorithms are multiple. These algorithms provide a new means of predicting when and where the next attack is most likely to occur. Likewise, additional research may be able to highlight which animals are more likely to be attacked. This data could be of great benefit to local agricultural communities, thus helping protect their assets and help alleviate tension that could better protect the wolf from danger of extinction.
A lo largo de la historia los humanos y los lobos han tenido una relación de amor-odio bastante compleja y conflictiva. Por un lado, en muchas ocasiones los lobos son los culpables de los daños o ataques al ganado, generando tensión con ganaderos y terratenientes, mientras que por otro lado el perro, su pariente domesticado, es considerado culturalmente como un miembro más de la familia. Debido a los ataques al ganado, con el paso de los años se han ido acrecentando las tensiones con las poblaciones rurales. Por desgracia, la Comunidad Autónoma de Castilla y León es una de las zonas del país más afectadas por ataques de lobo, siendo Ávila uno de los focos que más daños acumula. Los objetivos de esta línea de investigación es emplear algoritmos de inteligencia artificial para modelar y estudiar el impacto del lobo en la provincia de Ávila. Utilizando datos espaciales, enfoques estadísticos de Sistemas de Información Geográfica (SIG) y algoritmos de aprendizaje computacional, esperamos poder presentar una nueva perspectiva para el estudio de las actividades de los lobos y sus ataques al ganado local en la península. Las ventajas que presenta la inteligencia artificial son múltiples. Estos algoritmos son capaces de predecir con alta precisión dónde y cuándo es más probable que se produzca un nuevo ataque. De la misma forma, la investigación adicional puede destacar cual es el tipo de ganado más propenso a ser atacado. Estos datos pueden beneficiar a las comunidades ganaderas locales, ayudando a proteger a sus animales y a aliviar las tensiones generadas por los ataques, lo que puede a su vez ayudar a proteger mejor al lobo de su extinción.
Paula Villanueva
Graduated in Architecture (2012) and International PhD in Structures, Materials and Foundations (2017), at Universidad Politécnica de Madrid (Spain). In 2016, she went on a three months’ research stay at the University of Bath (UK), where she developed an analytical model on the framework of her PhD thesis “Influence of installation parameters on the performance of spike anchors for FRP reinforcements bonded to concrete members”. During the last three years, she has collaborated with engineering and architecture companies in the field of structural retrofitting of buildings and civil works, and has worked as a lecturer in different institutions including Universidad Politécnica de Madrid.
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Rocío Mora Fernández de Córdoba
Survey Engineer (2005-2009) and Graduated in Computer Engineering (2012 – 2016) from the University of Salamanca, is currently developing her PhD thesis in the TIDOP research group. Her researching lines try to combine her surveying knowledge with computer science, developing algorithms that allow the automatic creation of BIM models from point clouds. In 2018 he was awarded a Grant for the Hiring of Research Personnel by the Junta de Castilla y León linked to the National Research Project called Auto-BIM, for which she carried out research and development work and thanks to which she is carrying out teaching tasks in the Department of Terrain Cartographic Engineering. She has collaborated in other research projects related to new technologies and renewable energies, as well as she has participated as the organizing committee of some international congresses.
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Alberto Morcillo Sanz
Higher technician in development of multiplatform applications (2020). Nowadays, he is studying the degree in Computer Engineering at the University of Valladolid. He has experience in the field of programming due to the development of several projects and software using programming languages such as Java, C, C++, C#, Python, Kotlin or JavaScript. He is a specialist in low-level programming, development of libraries and frameworks and graphics programming.
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