Temporal-Clustering Based Technique for Identifying Thermal Regions in Buildings

Adán, Antonio; García, José Manuel García; Quintana, Blanca Hernández; Castilla, Francisco Javier García; Pérez, Víctor

doi:10.1007/978-3-030-40605-9_25

Cited by 3 publications

(2 citation statements)

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“…(II) In the case of thermal point clouds, the processing can be very varied and complex. Specifically, we refer to the following topics and references: creation of thermal point clouds [55], multi-session point cloud alignment procedure [56], data segmentation by structural elements [57], creation of semantic 3D models [44,58], processing of thermal orthoimages [59], clustering algorithms of characteristic regions in thermal orthoimages [59], and software tools for the visualisation and exploration of 3D thermal models obtained with scanners [55]. In Section 4.4.3, a brief summary of the processes used in the case study with our 3D-TCV platform is provided.…”

Section: Data Processing Results and Diseminationmentioning

confidence: 99%

Proposing 3D Thermal Technology for Heritage Building Energy Monitoring

Adán¹,

Pérez²,

Vivancos³

et al. 2021

Remote Sensing

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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.

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Section: Data Processing Results and Diseminationmentioning

confidence: 99%

Proposing 3D Thermal Technology for Heritage Building Energy Monitoring

Adán¹,

Pérez²,

Vivancos³

et al. 2021

Remote Sensing

Self Cite

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“…A flowchart illustrating the whole process is presented in Figure 8. More information on this algorithm can also be found in [42].…”

Section: Segmenting Ses Into Smaller Regions Through a Temporal Analy...mentioning

confidence: 99%

3D-TTA: A Software Tool for Analyzing 3D Temporal Thermal Models of Buildings

et al. 2020

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Many software packages are designed to process 3D geometric data, although very few are designed to deal with 3D thermal models of buildings over time. The software 3D Temporal Thermal Analysis (3D-TTA) has been created in order to visualize, explore and analyze these 3D thermal models. 3D-TTA is composed of three modules. In the first module, the temperature of any part of the building can be explored in a 3D visual framework. The user can also conduct separate analyses of structural elements, such as walls, ceilings and floors. The second module evaluates the thermal evolution of the building over time. A multi-temporal 3D thermal model, composed of a set of thermal models taken at different times, is handled here. The third module incorporates several assessment tools, such as the identification of representative thermal regions on structural elements and the comparison between real and simulated (i.e., obtained from energy simulation tools) thermal models. The potential scope of this software and its applications within the field of energy efficiency are presented in various case studies at the end of the paper.

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