Grupo de Ingeniería Estadística Multivariante GIEM
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- PublicationA methodology for discriminant time series analysis applied to microclimate monitoring of fresco paintings(MDPI AG, 2021-01) Ramírez, Sandra; Zarzo Castelló, Manuel; Perles Ivars, Ángel Francisco; García Diego, Fernando Juan; Dpto. de Física Aplicada; Dpto. de Informática de Sistemas y Computadores; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Grupo de Ingeniería Estadística Multivariante GIEM; Centro de Investigación en Acuicultura y Medio Ambiente; Pontificia Universidad Javeriana; COMISION DE LAS COMUNIDADES EUROPEA; Instituto Colombiano de Crédito Educativo y Estudios Técnicos en el Exterior[EN] The famous Renaissance frescoes in Valencia¿s Cathedral (Spain) have been kept under confined temperature and relative humidity (RH) conditions for about 300 years, until the removal of the baroque vault covering them, carried out in 2006. In the interest of longer-term preservation and in order to maintain these frescoes in good condition, a unique monitoring system was implemented to record both air temperature and RH. Sensors were installed in different points at the vault of the apse, during the restoration process. The present study proposes a statistical methodology for analyzing a subset of RH data recorded in 2008 and 2010, from the sensors. This methodology is based on fitting different functions and models to the time series, in order to classify the sensors. The methodology proposed, computes classification variables and applies a discriminant technique to them. The classification variables correspond to estimates of parameters of the models and features such as mean and maximum, among others. These features are computed using values of the functions such as spectral density, sample autocorrelation (sample ACF), sample partial autocorrelation (sample PACF), and moving range (MR). The classification variables computed were structured as a matrix. Next, Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) was applied in order to discriminate sensors according to their position in the vault. It was found that the classification of sensors derived from Seasonal ARIMA-TGARCH showed the best performance (i.e., lowest classification error rate). Based on these results, the methodology applied here can be useful for characterizing the differences in RH, measured at different positions in a historical building.
- PublicationReconstruction of historical hygrometric time series for the application of the European standard EN 15757:2010 and its comparison with current time series(BioMed Central, 2023-03-08) Díaz-Arellano, Ignacio; Zarzo Castelló, Manuel; Aransay, Cristina; Gonzalez de Aspuru, Sara; Laborda Macario, Jaime; Perles Ivars, Ángel Francisco; Dpto. de Informática de Sistemas y Computadores; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Informática; Grupo de Ingeniería Estadística Multivariante GIEM; COMISION DE LAS COMUNIDADES EUROPEA[EN] The quality and quantity of thermo-hygrometric data are essential to carry out an appropriate assessment of the microclimate from a preventive conservation standpoint in those spaces where the artefacts to be preserved are located. These analyses are fundamental for long-term preventive conservation plan to assess chemical, biological or fracture risks. However, many small and medium-sized museums as well as heritage buildings have only a limited amount of historical data, with various problems that hinder the evaluation of microclimatic conditions. Two of the most common problems are short monitoring time periods, usually less than one year, and low sampling rates of measurements. In many of these situations, guidelines such as the European standard EN 15757:2010 cannot be applied because they require a monitoring period of at least 13 months and a minimum sampling frequency of one measurement per hour. In addition to these issues, there are other drawbacks such as missing values or lack of regularity in data collection. This paper proposes a procedure for the reconstruction of historical thermo-hygrometric data using multivariate statistical methods. The methodology allows the arrangement of long historical series of sufficient quality, enabling museums to restore their datasets for further analysis regarding the application of guidelines for preventive conservation. The methodology has been validated on the basis of real data. The application of the European standard EN 15757:2010 is presented as a practical example of the procedure using historical data collected at a partner museum of the H2020 CollectionCare project, together with data currently being collected for some months by a set of wireless sensor nodes.
- PublicationCharacterization of temperature gradients according to height in a baroque church by means of wireless sensors(MDPI AG, 2021-10) Ramírez, Sandra; Zarzo Castelló, Manuel; Perles Ivars, Ángel Francisco; García Diego, Fernando Juan; Dpto. de Física Aplicada; Dpto. de Informática de Sistemas y Computadores; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Grupo de Ingeniería Estadística Multivariante GIEM; Centro de Investigación en Acuicultura y Medio Ambiente; COMISION DE LAS COMUNIDADES EUROPEA[EN] The baroque church of Saint Thomas and Saint Philip Neri (Valencia, Spain), which was built between 1727 and 1736, contains valuable paintings by renowned Spanish artists. Due to the considerable height of the central nave, the church can experience vertical temperature gradients. In order to investigate this issue, temperatures were recorded between August 2017 and February 2018 from a wireless monitoring system composed of 21 sensor nodes, which were located at different heights in the church from 2 to 13 m from the floor level. For characterizing the temperature at high, medium and low altitude heights, a novel methodology is proposed based on sparse Partial Least Squares regression (sPLS), Linear Discriminant Analysis (LDA), and the Holt-Winters method, among others, which were applied to a time series of temperature. This approach is helpful to discriminate temperature profiles according to sensor height. Once the vertical thermal gradients for each month were characterized, it was found that temperature reached the maximum correlation with sensor height in the period between August 10th and September 9th. Furthermore, the most important features from the time series that explain this correlation are the mean temperature and the mean of moving range. In the period mentioned, the vertical thermal gradient was estimated to be about 0.043 ºC/m, which implies a difference of 0.47 ºC on average between sensor nodes at 2 m from the floor with respect to the upper ones located at 13 m from the floor level. The gradient was estimated as the slope from a linear regression model using height and hourly mean temperature as the predictor and response, respectively. This gradient is consistent with similar reported studies. The fact that such gradient was only found in one month suggests that the mechanisms of dust deposition on walls involved in vertical thermal gradients are not important in this case regarding the preventive conservation of artworks. Furthermore, the methodology proposed here was useful to discriminate the time series at high, medium and low altitude levels. This approach can be useful when a set of sensors is installed for microclimate monitoring in churches, cathedrals, and other historical buildings, at different levels and positions.
- PublicationA Methodology for the Multi-Point Characterization of Short-Term Temperature Fluctuations in Complex Microclimates Based on the European Standard EN 15757:2010: Application to the Archaeological Museum of L'Almoina (Valencia, Spain)(MDPI AG, 2021-11) Díaz-Arellano, Ignacio; Zarzo Castelló, Manuel; García Diego, Fernando Juan; Perles Ivars, Ángel Francisco; Dpto. de Física Aplicada; Dpto. de Informática de Sistemas y Computadores; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Grupo de Ingeniería Estadística Multivariante GIEM; Centro de Investigación en Acuicultura y Medio Ambiente; COMISION DE LAS COMUNIDADES EUROPEA[EN] The monitoring and control of thermo-hygrometric indoor conditions is necessary for an adequate preservation of cultural heritage. The European standard EN 15757:2010 specifies a procedure for determining if seasonal patterns of relative humidity (RH) and temperature are adequate for the long-term preservation of hygroscopic materials on display at museums, archives, libraries or heritage buildings. This procedure is based on the characterization of the seasonal patterns and the calculation of certain control limits, so that it is possible to assess whether certain changes in the microclimate can be harmful for the preventive conservation of artworks, which would lead to the implementation of corrective actions. In order to discuss the application of this standard, 27 autonomous data-loggers were located in different points at the Archaeological Museum of l¿Almoina (Valencia). The HVAC system (heating, ventilation and air conditioning) at the museum tries to reach certain homogeneous environment, which becomes a challenge because parts of the ruins are covered by a skylight that produces a greenhouse effect in summer, resulting in severe thermo-hygrometric gradients. Based on the analysis of temperatures recorded during 16 months, the air conditions in this museum are discussed according to the standard EN 15757:2010, and some corrective measures are proposed to improve the conservation conditions. Although this standard is basically intended for data recorded from a single sensor, an alternative approach proposed in this work is to find zones inside the museum with a homogeneous microclimate and to discuss next the average values collected in each area. A methodology is presented to optimize the application of this standard in places with a complex microclimate like this case, when multiple sensors are located at different positions.
- PublicationMultivariate characterization of temperature fluctuations in a historical building using energy-efficient IoT wireless sensors(MDPI AG, 2021-12) Zarzo Castelló, Manuel; Perles Ivars, Ángel Francisco; Mercado Romero, Ricardo; García Diego, Fernando Juan; Dpto. de Física Aplicada; Dpto. de Informática de Sistemas y Computadores; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Grupo de Ingeniería Estadística Multivariante GIEM; Centro de Investigación en Acuicultura y Medio Ambiente; COMISION DE LAS COMUNIDADES EUROPEA[EN] Adequate thermic conditions are required for the preventive conservation of artworks, but such optimum conditions cannot always be achieved in historical buildings such as ancient churches. In those cases, it is of interest to assess the potential risk of punctual changes in indoor environments that can be harmful to artworks. These conditions can be assessed by means of a microclimate monitoring system comprised of a set of energy¿efficient wireless sensors connected to the cloud using IoT techniques. This approach was followed at the baroque church of Saint Thomas and Saint Philip Neri in Valencia (Spain). A set of 26 wireless nodes was installed, which recorded values of temperature and relative humidity every hour for a period of 7 months. Small differences of temperature were obtained among sensors, so that an efficient methodology based on principal component analysis (PCA) was applied for the characterization of similarities and dissimilarities between sensors. Daily ranges of temperatures were studied as well as mean trajectories, differences between days of the week, and changes in the correlation structure of daily median values over time. Results provide a framework for an efficient characterization of temperatures in heritage buildings based on a network of wireless sensors. Such a framework is useful to assess the potential risk of temperature fluctuations on the preventive conservation of historical buildings and artworks.
- PublicationAn energy-efficient internet of things (IoT) architecture for preventive conservation of cultural heritage(Elsevier, 2018) Perles Ivars, Ángel Francisco; Pérez Marín, Eva; Mercado Romero, Ricardo; Segrelles Quilis, José Damián; Blanquer Espert, Ignacio; Zarzo Castelló, Manuel; García Diego, Fernando Juan; Dpto. de Física Aplicada; Dpto. de Informática de Sistemas y Computadores; Dpto. de Sistemas Informáticos y Computación; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Estadística e Investigación Operativa Aplicadas y Calidad; Escuela Técnica Superior de Ingeniería del Diseño; Dpto. de Conservación y Restauración de Bienes Culturales; Facultad de Bellas Artes; Instituto Universitario de Restauración del Patrimonio; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Instituto de Instrumentación para Imagen Molecular; Grupo de Ingeniería Estadística Multivariante GIEM; Centro de Investigación en Acuicultura y Medio Ambiente; Generalitat Valenciana; Ministerio de Economía, Industria y Competitividad[EN] Internet of Things (IoT) technologies can facilitate the preventive conservation of cultural heritage (CH) by enabling the management of data collected from electronic sensors. This work presents an IoT architecture for this purpose. Firstly, we discuss the requirements from the artwork standpoint, data acquisition, cloud processing and data visualization to the end user. The results presented in this work focuses on the most critical aspect of the architecture, which are the sensor nodes. We designed a solution based on LoRa and Sigfox technologies to produce the minimum impact in the artwork, achieving a lifespan of more than 10 years. The solution will be capable of scaling the processing and storage resources, deployed either in a public or on-premise cloud, embedding complex predictive models. This combination of technologies can cope with different types of cultural heritage environments.