| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | August 6, 2014 |
| Latest Amendment Date: | August 6, 2014 |
| Award Number: | 1446765 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Bruce Kramer
CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | January 1, 2015 |
| End Date: | December 31, 2019 (Estimated) |
| Total Intended Award Amount: | $999,935.00 |
| Total Awarded Amount to Date: | $999,935.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
506 S WRIGHT ST URBANA IL US 61801-3620 (217)333-2187 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1901 S. First Street, Suite A Champaign IL US 61820-7406 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CPS-Cyber-Physical Systems |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
This Cyber-Physical Systems (CPS) award supports research to enable the automated monitoring of building and infrastructure construction projects. The purpose of construction monitoring is to provide developers, contractors, subcontractors, and tradesmen with the information they need to easily and quickly make project control decisions. These decisions have a direct impact on the overall efficiency of a construction project. Given that construction is a $800 billion industry, gains in efficiency could lead to enormous cost savings, benefiting both the U.S. economy and society. In particular, both construction cost and delivery time could be significantly reduced by automated tools to assess progress towards completion (progress monitoring) and how construction resources are being utilized (activity monitoring). These tools will be provided by advances in the disciplines of computer vision, robotics, and construction management. The interdisciplinary nature of this project will create synergy among these disciplines and will positively influence engineering education. Partnerships with industry will also ensure that these advances have a positive impact on construction practice.
The process of construction monitoring involves data collection, analysis, and reporting. Research will address the existing scientific challenges to automating these three activities. Data collection will be automated by recording video with aerial robots and a network of cameras. Key research objectives are to derive planning algorithms that guarantee complete coverage of a construction site and to derive vision-based control algorithms that enable robust placement and retrieval of cameras. Analysis will be automated with a digital building information model with respect to which construction resources can be tracked. Key research objectives are to improve the efficiency and reliability of image-based reconstruction, to recognize material properties as well as geometry, to establish a formal language for representing construction activities, and to extend a parts-based approach for automated activity recognition. Reporting will be automated with a ubiquitous display of the digital building information model. Key research objectives are to formalize a constraint construction ontology with associated classification mechanisms and allow for systematic earned value analysis of construction progress. Experimental validation will focus on monitoring construction of substructure and superstructure skeletal elements in buildings and infrastructure systems as well as the associated earth-moving, concrete placement, and steel erection activities that are common in construction projects.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Team-based planning and real-time communication of progress and schedule risk are two important mechanisms of a proactive project controls program; a program that maintains a smooth flow of production on construction projects. Towards this goal, this NSF project delivered the scientific theories and methods behind the development of a visual and virtual project control system that improves understanding of how construction progress can be captured, communicated, and analyzed in the form of a production system. This system predicts the reliability of the short-term construction plans, supports root-cause assessment on plan failure, facilitates information flows, and decentralizes decision-making.
Our system benefits from the growth of images and videos on construction sites -captured through unmanned aerial vehicles and ground cameras- and the increasing maturity level of 3D information models, to map the current state of production on construction sites in 3D and expose waste. A number of CPS methods ranging from computer vision to robotics to information modeling and verification methods were developed to automatically capture and generate these 3D models and align them over project timeline. Project teams use these models as a time machine in a web based environment to explore past, current and future state of a construction project in a visual environment. By modeling production trends, reliability in the future state of production is forecasted to highlight potential delay issues. A visual 3D interface is also developed to support collaborative decision-making to eliminate root causes of waste, enable pull flows between people and information, decentralize work tracking, and facilitate in-process quality control and hand-overs among contractors. This system was implemented on real world construction projects to validate the underlying algorithms. In addition to contributions to the body of knowledge, our findings show that the functional aspects of the system improve transparency, accountability, and traceability in project execution on construction sites, and streamlines communications between the field and the office.
The findings from this research were integrated into education and outreach activities and were broadly disseminated to the construction industry and academia through publications, presentations, and posting of datasets and software. A large body of undergraduate students, particularly from underrepresented groups, were involved in research activities. The higher education in engineering related to this project was also expanded to incarcerated population at a local correction facility. A startup company was formed based on the intellectural property produced from this project. This company has raised substational funding and has hired 10s of individuals. The underlying solution offered by the company --which is based on findings from this CPS project- is now deployed on 100s of projects in the United States and around the world, helping project teams keeping their projects on schedule and on budget.
Last Modified: 05/12/2020
Modified by: Mani Golparvar-Fard
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