Thomas Czerniawski

• Doctor of Philosophy
• Assistant Professor at Arizona State University

City-scale facility management plays a critical role in public health. This research aims to analyze city-scale infrastructure through a cost-effective approach by utilizing light detection and ranging (LiDAR) point cloud acquisition, dimensionality reduction processing, and advanced machine learning segmentation methods. A case study in a southwes...

Bike lane width is critical information for civil infrastructure planers to promote city sustainability, health, and urban livability. This research presents a feasibility investigation to develop a workflow for the recognition of bike lane markings using city-scale point cloud data. City-scale point cloud data was collected employing a backpack mo...

Imagery is a standard modality of visual data capture on construction sites for documenting construction progress. Assimilating the data from multiple disjointed 2D images into a single 3D format enhances visualization, and scene understanding and increases the data usability for tasks like quantity estimation and progress tracking. Two popular met...

We present an automated scan-to-BIM pipeline that simplifies the 3D building object recognition problem into a 2D recognition problem. We used the Habitat Matterport 3D Dataset (HM3D) for training wall detection model. The weakly supervised learning is conducted since we used the noisy depth-projected annotation. We isolated individual building lev...

Current computer vision methods for symbol detection in piping and instrumentation diagrams (P&IDs) face limitations due to the manual data annotation resources they require. This paper introduces a versatile two-stage symbol detection pipeline that optimizes efficiency by (1) labeling only data samples with minimal cumulative informational redunda...

The increasing availability of point clouds has led to intensive research into automating point cloud processing using machine learning. While supervised systems require large and diverse labeled datasets, the cost and time of manual data creation can be overcome with synthetic data. This paper introduces DynamoPCSim, a versatile scanning simulator...

Building owners are working on converting their legacy documentation 2D floor plans into digital 3D representations, but the manual process is labor-intensive and time-consuming. In this paper, deep learning is leveraged to automate the process. This automation requires interoperability between artificial neural networks and prevailing 3D modeling...

For successfully training neural networks, developers often require large and carefully labelled datasets. However, gathering such high-quality data is often time-consuming and prohibitively expensive. Thus, synthetic data are used for developing AI (Artificial Intelligence) /ML (Machine Learning) models because their generation is comparatively fa...

Generating digital 3D buildings models from scratch is time-consuming and labor-intensive. In this paper, we present an automated detection process leveraging computer vision and the information available in 2D drawings to reduce 3D modeling time. The recognition system is limited to walls and has two parts: (1) Image classification on walls by Res...

For facility management, photography is an efficient and accurate method of recording the physical state of infrastructure. However, without an effective organizational scheme, the difficulty of retrieving relevant photos from historical databases can become overly burdensome for highly complex or long-lived assets. To make strategic decisions, it...

When updating digital models of existing buildings, changes in the built environment are detected by comparing outdated BIMs with captured point clouds representing current conditions. Here we show that point cloud completion (i.e. automated filling-in of missing data) improves the accuracy of change detection. We perform point cloud completion usi...

Building information modeling (BIM) has a semantic scope that encompasses all building systems, e.g. architectural, structural, mechanical, electrical, and plumbing. Automated, comprehensive digital modeling of buildings will require methods for semantic segmentation of images and 3D reconstructions capable of recognizing all building component cla...

The vast scale of buildings poses many challenges to the flow of information. Automatically creating and updating building information models will require the adoption of computer vision systems capable of parsing a comprehensive set of building components all the while being resilient to imperfections inherent in large-scale data collection. Exist...

Facility management information systems are difficult to manage due to the enormous scope of buildings. We present a method for organizing and retrieving photos from massive facility management photo databases using photo-metadata. Providing an intuitive organizational scheme, location, camera orientation, and semantic content description metadata...

This paper investigates the viability of using synthetic point clouds generated from building information models (BIMs) to train deep neural networks to perform semantic segmentation of point clouds of building interiors. In order to achieve these goals, this paper first presents a procedure for converting digital 3D BIMs into synthetic point cloud...

Digital building representations enable and promote new forms of simulation, automation, and information sharing. However, creating and maintaining these representations is prohibitively expensive. In an effort to make the adoption of this technology easier, researchers have been automating the digital modeling of existing buildings by applying rea...

Creating deep learning classifiers requires large labeled datasets; and creating large labeled datasets requires elaborate crowdsourcing systems and many hours of manual human effort applied to classification and data entry. Fortunately, much of this effort can be bypassed in the building industry because of as-built building information models (BI...

In the heavy construction industry, pipe spool assembly is geometrically complex and suboptimal fabrication processes inevitably lead to fabrication errors and costly rework. In an attempt to mitigate fabrication risks and improve product quality, computer aided tools are being developed to provide an additional layer of control. In this paper, the...

Due to constraints in manufacturing and construction, buildings and many of the manmade objects within them are often rectangular and composed of planar parts. Detection and analysis of planes is, therefore, central to processing of point clouds captured in these spaces. This paper presents a study of the semantic information stored in the planar o...

Determination of construction performance metrics requires intensive processing of large amounts of data collected on construction sites including cluttered laser scans. For example, for quality control of construction components using 3D laser scans, the acquired point cloud should be cleaned and the object-of-interest should be extracted for meas...

The industrial construction industry makes use of prefabrication, preassembly, modularization and off-site fabrication (PPMOF) for project execution because they offer a superior level of control as compared to on-site operations. This control is enabled by systematic and thorough performance feedback loops. Improvement of the feedback systems with...

In the heavy construction industry, pipe spool assembly is geometrically complex and suboptimal fabrication processes inevitably lead to fabrication errors and costly rework. In an attempt to mitigate fabrication risks and improve product quality, computer aided tools are being developed to provide an additional layer of control. In this paper, the...

Parallel structural systems and assemblies are challenging to erect, align and plumb on construction sites due to their complex geometries and current heuristic realignment strategies. Examples of parallel systems include complicated pipe modules and pipe racks in the industrial construction sector. This paper presents a generalized approach analog...

Dimensional compliance assessment of prefabricated assemblies is a critical part of mitigating rework on heavy industrial construction projects. As assemblies become more complex, manual direct contact metrology becomes ineffective at detecting fabrication error and so automated alternatives that offer objective, fast, and continuous data collectio...

Image-based frameworks for automated as-built modeling and infrastructure 3D reconstruction are increasingly being used in the construction industry. The increasing use of image-based technologies in the construction processes is due to the ease of application, cheap cost of enhancement, time effectiveness and high level of accuracy and automation....

Taking into account the increasing complexity and scale of construction projects recently, interface management (IM) has been emerging as an important aspect of project management practices. It is believed that effective IM improves alignment and reduces conflicts among project stakeholders by increasing visibility on roles, responsibilities and de...