Proposing 3D Thermal Technology for Heritage Building Energy Monitoring

The energy monitoring of heritage buildings has, to date, been governed by methodologies and standards that have been defined in terms of sensors that record scalar magnitudes and that are placed in specific positions in the scene, thus recording only some of the values sampled in that space. In this paper, however, we present an alternative to the aforementioned technologies in the form of new sensors based on 3D computer vision that are able to record dense thermal information in a three-dimensional space. These thermal computer vision-based technologies (3D-TCV) entail a revision and updating of the current building energy monitoring methodologies. This paper provides a detailed definition of the most significant aspects of this new extended methodology and presents a case study showing the potential of 3D-TCV techniques and how they may complement current techniques. The results obtained lead us to believe that 3D computer vision can provide the field of building monitoring with a decisive boost, particularly in the case of heritage buildings.

[1]  Stefano Sfarra,et al.  Quantitative thermography for the estimation of the U-value: state of the art and a case study , 2014 .

[2]  Antonio Adán,et al.  Semantic scan planning for indoor structural elements of buildings , 2016, Adv. Eng. Informatics.

[3]  E. Zendri,et al.  A new methodology to characterize indoor variations of temperature and relative humidity in historical museum buildings for conservation purposes , 2020 .

[4]  Manolis I. A. Lourakis,et al.  Toward automated generation of parametric BIMs based on hybrid video and laser scanning data , 2010, Adv. Eng. Informatics.

[5]  W. D. Hoff,et al.  Moisture dynamics in walls: response to micro-environment and climate change , 2011, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[6]  Fernando-Juan García-Diego,et al.  An energy-efficient internet of things (IoT) architecture for preventive conservation of cultural heritage , 2018, Future Gener. Comput. Syst..

[7]  C. Valderrama-Ulloa,et al.  Indoor Environmental Quality in Latin American Buildings: A Systematic Literature Review , 2020, Sustainability.

[8]  Alberto Olivares,et al.  Towards the Automatic Scanning of Indoors with Robots , 2015, Sensors.

[9]  Antonio Adán,et al.  An Autonomous Thermal Scanning System with Which to Obtain 3D Thermal Models of Buildings , 2019 .

[10]  Constantinos A. Balaras,et al.  Infrared thermography for building diagnostics , 2002 .

[11]  Burcu Akinci,et al.  Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data , 2013 .

[12]  Mani Golparvar-Fard,et al.  Mapping actual thermal properties to building elements in gbXML-based BIM for reliable building energy performance modeling , 2015 .

[13]  M. I. Martínez-Garrido,et al.  Effect of solar radiation and humidity on the inner core of walls in historic buildings , 2014 .

[14]  Antonia Moropoulou,et al.  Applications of infrared thermography for the investigation of historic structures , 2004 .

[15]  Soolyeon Cho,et al.  Energy efficiency and thermal comfort in historic buildings: A review , 2016 .

[16]  Ángel Luis León-Rodríguez,et al.  Air conditioning and passive environmental techniques in historic churches in Mediterranean climate. A proposed method to assess damage risk and thermal comfort pre-intervention, simulation-based , 2016 .

[17]  Ángel Luis León-Rodríguez,et al.  Hygrothermal performance of worship spaces: preservation, comfort, and energy consumption , 2018 .

[18]  A. Audenaert,et al.  An integrated approach for indoor microclimate diagnosis of heritage and museum buildings: The main exhibition hall of Vleeshuis museum in Antwerp , 2018 .

[19]  Bryan P. Rasmussen,et al.  Energy analysis of religious facilities in different climates through a long-term energy study , 2015 .

[20]  Mani Golparvar-Fard,et al.  Segmentation of building point cloud models including detailed architectural/structural features and MEP systems , 2015 .

[21]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Jingdao Chen,et al.  Performance evaluation of 3D descriptors for object recognition in construction applications , 2018 .

[23]  M. I. Martínez-Garrido,et al.  Experimental assessment of a wireless communications platform for the built and natural heritage , 2016 .

[24]  Antonio Adán,et al.  An autonomous robotic platform for automatic extraction of detailed semantic models of buildings , 2020, Automation in Construction.

[25]  Girum G. Demisse,et al.  Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency , 2013, 2013 16th International Conference on Advanced Robotics (ICAR).

[26]  Dario Camuffo,et al.  Quantitative Evaluation of Water Deposited By Dew on Monuments , 2003 .

[27]  Dario Camuffo,et al.  Microclimate for Cultural Heritage , 1998 .

[28]  Antonio Adán,et al.  Temporal-Clustering Based Technique for Identifying Thermal Regions in Buildings , 2020, ACIVS.

[29]  Alfonso P. Ramallo-González,et al.  Commissioning of the Controlled and Automatized Testing Facility for Human Behavior and Control (CASITA) , 2018, Sensors.

[30]  Burcu Akinci,et al.  Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques | NIST , 2010 .

[31]  R. Vella,et al.  A study of thermal comfort in naturally ventilated churches in a Mediterranean climate , 2020 .

[32]  M. I. Martínez-Garrido,et al.  A comprehensive study for moisture control in cultural heritage using non-destructive techniques , 2018, Journal of Applied Geophysics.

[33]  Zheng Yang,et al.  Modeling personalized occupancy profiles for representing long term patterns by using ambient context , 2014 .

[34]  Marco Filippi,et al.  A methodology for microclimatic quality evaluation in museums: Application to a temporary exhibit , 2009 .

[35]  Antonio Adán,et al.  3D-TTA: A Software Tool for Analyzing 3D Temporal Thermal Models of Buildings , 2020, Remote. Sens..

[36]  Adriana Bernardi,et al.  Study of the Microclimate of the Hall of the Giants in the Carrara Palace in Padua , 1995 .

[37]  Yong K. Cho,et al.  As-Is 3D Thermal Modeling for Existing Building Envelopes Using a Hybrid LIDAR System , 2013 .

[38]  Sirkka Rissanen,et al.  An advanced church heating system favourable to artworks: A contribution to European standardisation , 2010 .

[39]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[40]  Ainara Zornoza-Indart,et al.  Fluctuations in the indoor environment in Spanish rural churches and their effects on heritage conservation: Hygro-thermal and CO2 conditions monitoring , 2014 .

[41]  M. I. Martínez-Garrido,et al.  Monitoring the thermal–hygrometric conditions induced by traditional heating systems in a historic Spanish church (12th–16th C) , 2014 .

[42]  José Emilio Meroño de Larriva,et al.  Monitoring Heritage Buildings with Open Source Hardware Sensors: A Case Study of the Mosque-Cathedral of Córdoba , 2016, Sensors.

[43]  Maria Danese,et al.  INVESTIGATING MATERIAL DECAY OF HISTORIC BUILDINGS USING VISUAL ANALYTICS WITH MULTI‐TEMPORAL INFRARED THERMOGRAPHIC DATA , 2009 .

[44]  Stefano Paoloni,et al.  Infrared Thermography Applied to the Study of Cultural Heritage , 2015 .

[45]  Antonio Adán,et al.  As-is building-structure reconstruction from a probabilistic next best scan approach , 2017, Robotics Auton. Syst..

[46]  Dario Camuffo Standardization activity in the evaluation of moisture content , 2018, Journal of Cultural Heritage.

[47]  Ermanno G. Grinzato,et al.  Monitoring of ancient buildings by the thermal method , 2002 .

[48]  Chris Tweed,et al.  Impacts of energy-efficiency investments on internal conditions in low-income households , 2018 .

[49]  G. Richardson,et al.  The Watcombe housing study: the short-term effect of improving housing conditions on the indoor environment. , 2006, The Science of the total environment.

[50]  Youngjib Ham,et al.  3D as-is building energy modeling and diagnostics: A review of the state-of-the-art , 2015, Adv. Eng. Informatics.

[51]  Servando Álvarez Domínguez,et al.  Climatic zoning and its application to Spanish building energy performance regulations , 2008 .