A Cost-Effective System for Aerial 3D Thermography of Buildings

Daffara, Claudia; Muradore, Riccardo; Piccinelli, Nicola; Gaburro, Nicola; Rubeis, Tullio de; Ambrosini, Dario

doi:10.3390/jimaging6080076

Cited by 29 publications

(14 citation statements)

References 59 publications

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“…The thermal cameras available on the market include portable medium-sized devices for on field measurements, up to more recent and compact devices suitable for machine vision and drone applications [7] . Recent advances in sensor technology has lead to the availability of small and cost-effective LWIR camera cores, mounting uncooled microbolometers [8] , allowing researchers to prototype thermal vision systems tailored to very peculiar applications and specific environments, such as the endoscopic thermal inspection proposed in this paper.…”

Section: Hardware In Contextmentioning

confidence: 99%

Thermal endoscope based on cost-effective LWIR camera cores

et al. 2022

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Section: Hardware In Contextmentioning

confidence: 99%

Thermal endoscope based on cost-effective LWIR camera cores

et al. 2022

Self Cite

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“…The application of infrared and thermographic images can be considered in the conservation and restoration of heritage assets, being widely used in the energy efficiency analysis [48,49]. On the other hand, multispectral images can be employed to analyse the environment in which the heritage assets are located.…”

Section: Opportunitiesmentioning

confidence: 99%

Graphic Applications of Unmanned Aerial Vehicles (UAVs) in the Study of Industrial Heritage Assets

et al. 2020

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As a typology of cultural heritage, a wide range of singularities must to be taken into account when analysing industrial heritage assets. Graphical resources have been usually employed in heritage assets research. Nowadays, Unmanned Aerial Vehicles (UAVs) offer the possibility to obtain images of complex and difficult access areas that cannot be observed on the ground. Furthermore, aerial images allow to analyse heritage assets as a whole. Therefore, in this work, different photographs and videos has been carried out in the San Joaquin sugar cane factory and in the Aguila aqueduct, located in Nerja (Spain). These images have been used to analyse both assets as a set. Different indirect measurements on the factory chimney and irrigation water pond were taken. A Strengths, Weaknesses, Opportunities, and Threats (SWOT) about the use of UAV graphic applications in heritage assets was developed. Finally, the possibilities of conventional photograph technologies and UAV application were compared. Using UAVs allows more image acquisition possibilities than conventional systems. However, both technologies can be complemented and applied together when analysing heritage assets.

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“…One technique to obtain thermal imagery is by using drones, which creates opportunities in building assessment and inspections [ 7 , 8 , 9 ]. Drones enables fast and safe building inspections, which are necessary to complete proactive maintenance to mitigate problems before they become costly.…”

Section: Introductionmentioning

confidence: 99%

An Instance Segmentation and Clustering Model for Energy Audit Assessments in Built Environments: A Multi-Stage Approach

Arjoune

Peri

Sugunaraj

et al. 2021

Sensors

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Heat loss quantification (HLQ) is an essential step in improving a building’s thermal performance and optimizing its energy usage. While this problem is well-studied in the literature, most of the existing studies are either qualitative or minimally driven quantitative studies that rely on localized building envelope points and are, thus, not suitable for automated solutions in energy audit applications. This research work is an attempt to fill this gap of knowledge by utilizing intensive thermal data (on the order of 100,000 plus images) and constitutes a relatively new area of analysis in energy audit applications. Specifically, we demonstrate a novel process using deep-learning methods to segment more than 100,000 thermal images collected from an unmanned aerial system (UAS). To quantify the heat loss for a building envelope, multiple stages of computations need to be performed: object detection (using Mask-RCNN/Faster R-CNN), estimating the surface temperature (using two clustering methods), and finally calculating the overall heat transfer coefficient (e.g., the U-value). The proposed model was applied to eleven academic campuses across the state of North Dakota. The preliminary findings indicate that Mask R-CNN outperformed other instance segmentation models with an mIOU of 73% for facades, 55% for windows, 67% for roofs, 24% for doors, and 11% for HVACs. Two clustering methods, namely K-means and threshold-based clustering (TBC), were deployed to estimate surface temperatures with TBC providing consistent estimates across all times of the day over K-means. Our analysis demonstrated that thermal efficiency not only depended on the accurate acquisition of thermal images but also relied on other factors, such as the building geometry and seasonal weather parameters, such as the outside/inside building temperatures, wind, time of day, and indoor heating/cooling conditions. Finally, the resultant U-values of various building envelopes were compared with recommendations from the American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE) building standards.

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A Cost-Effective System for Aerial 3D Thermography of Buildings

Cited by 29 publications

References 59 publications

Thermal endoscope based on cost-effective LWIR camera cores

Thermal endoscope based on cost-effective LWIR camera cores

Graphic Applications of Unmanned Aerial Vehicles (UAVs) in the Study of Industrial Heritage Assets

An Instance Segmentation and Clustering Model for Energy Audit Assessments in Built Environments: A Multi-Stage Approach

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