Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency

Abstract

In recent years 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited because most models are pure representations with no or little associated semantics. In this paper we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Among other things, these algorithms enable the system to differentiate between objects in a room and objects that are part of the room, e.g. floor, windows. Subsequently, the thermal information is used to construct a stochastic mathematical modelnamely Markov Random Field-of the temperature distribution of the detected windows. As a result, the MAP(Maximum a posteriori) framework is used to further label the windows as either open, closed or damaged based upon their temperature distribution.

Understanding the Role of Thermography in Energy Auditing

“…Recent automated thermography efforts have focused on two areas ( Figure 2): transforming thermal images into 3D-reconstructions of buildings (e.g., [17,20,29,31,38]) and employing robots and vehicles to scale up data collection (e.g., [6,10,13,30,34,35,41]). Researchers argue that traditional 2D thermal images: (i) do not include geometry and spatial relationships, which are important for interpreting thermography [20,29]; (ii) are unordered, messy, and difficult to organize [17,20]; (iii) and require time-consuming and labor intensive post-hoc analysis [17,20,38].…”

“…Both require large amounts of data. Thus, researchers are increasingly using robots for data collection, including ground-based rovers for indoor thermography (e.g., [6,10]) and UAVs for outdoor thermography (e.g., [13,30,35,41]). The robots are equipped with a suite of sensors such as thermal and optical cameras, laser scanners, and GPS.…”

“…Researchers have primarily explored technical approaches for automatically transforming thermal images into higher fidelity 3D representations of buildings [17,20,29,31,38] and employing robots for data collection [6,10,13,30,35,41]. However, user studies of these tools have not been performed.…”

“…For the design probes, we developed five scenarios of automated thermography based on the research literaturee.g., indoor robotic thermography [6,10] and large-scale urban thermography using unmanned aerial vehicles (UAVs) [13,30,35,41]. The scenarios were designed to provoke and ground discussion and critically assess how automated thermography may be used in the future.…”

Door recognition in cluttered building interiors using imagery and lidar data

“…Adán et al, (2011) andPrevitali et al (2014) detect openings in indoor scenes by analysing data density and classifying lowdensity areas as openings, thus limiting the scope to low-density windows and doorways. Demisse et al, (2013) In this work, we propose a simple but effective methodology based on automatic data-driven approach for the reconstruction of building indoor scenes using both 3D point clouds and RGB images, going in depth with door detection and classification. The methodology is tested through a case study, acquired under unmodified-furniture conditions.…”