Research Grants/Fellowships/SBIR

Vision-Based Monitoring and Control of Construction Operations Carbon Footprint

EPA Grant Number: SU835352
Title: Vision-Based Monitoring and Control of Construction Operations Carbon Footprint
Investigators: Golparvar-Fard, Mani , Marr, Linsey C.
Current Investigators: Golparvar-Fard, Mani , Haratmeh, Bardia Heidari , Khare, Peeyush , Khosrowpour, Ardalan , Marr, Linsey C. , Zelkowicz, Moshe
Institution: Virginia Polytechnic Institute and State University
EPA Project Officer: Lank, Gregory
Phase: I
Project Period: August 15, 2012 through August 14, 2013
Project Amount: $15,000
RFA: P3 Awards: A National Student Design Competition for Sustainability Focusing on People, Prosperity and the Planet (2012) RFA Text |  Recipients Lists
Research Category: Pollution Prevention/Sustainable Development , P3 Challenge Area - Built Environment , P3 Challenge Area - Green Infrastructure , P3 Awards , Sustainability


The objective of this research project is to test whether a hypothesized framework proposed by the PIs can benchmark and automatically monitor carbon footprint of construction activities. This objective will be achieved using emerging networks of fixed cameras and Green House Gas (GHG) emission inventories of construction actions, for the purpose of minimizing excessive environmental impacts of construction performance deviations. This interdisciplinary research goes beyond traditional boundaries of construction management, environmental engineering, and computer science disciplines. It particularly provides the construction industry with a cost-effective and easy-to-use tool that can support benchmarking, monitoring, and improvement of construction operations, ultimately leading to reductions in construction operations carbon footprint. The research and educational activities will also provide students with real-world experience, which they would not be able to achieve solely in the classroom. Finally, the project also benefits the society by providing a new visualization technique which facilitates non-experts to get a better understanding of the construction industry and the excessive emissions due to performance deviations.


According to the proposed framework, video streams from a network of installed cameras are continuously processed to track equipment in 3D and recognize their actions. Once a time-series of equipment actions and their locations is formed, construction carbon footprint, i.e., emissions associated with construction operations are measured using a carbon footprint inventory of equipment actions. Using the same inventory and based on a simulation model, the planned construction activities are simulated and the emissions expected from these operations are benchmarked. Next, the actual and expected carbon footprints are compared at the construction schedule activity level. Finally, the construction operations are visualized in an augmented reality environment and performance deviations (i.e., impacts on environment, cost, and project schedule) are highlighted using a metaphor of traffic-light colors. The social impact of excessive emissions due to performance deviations is also visualized using EPA’s metaphor of number of tree seedlings grown for 10 years.

Expected Results:

Automated and continuous carbon footprint monitoring of construction operations support the contractors and project managers with information required for assessment on carbon footprint of various construction operation alternatives. This can ultimately lead to reduction of excessive environmental impacts associated with performance deviations. By benchmarking, monitoring, and improving construction performance, this research not only minimizes negative environmental impacts of performance deviations on human health, but also provides an economic competitiveness for the construction companies that are adopting this easy to use technology. It further minimizes GHG emissions and can help meet the emission reduction goals set by EPA and other government agencies. In addition to publications of the findings of this research in leading journals and magazines, the outcome will also be integrated into a variety of educational programs, including K-12, undergraduate and graduate student projects as well as construction industry educational workshops.

Contribution to Pollution Prevention and/or Control: Successful execution of the proposed research will transform the way construction operations are currently being monitored and offers a new possibility for low-cost and effective monitoring of construction carbon footprint at reasonable accuracy. Construction operations will be more frequently and continuously assessed through an inexpensive and easy to install solution. Combination of detailed assessment and continuous improvement can help minimize the idle time, improve productivity of operations, save time and money, and result in reduction of fuel use, construction emissions and carbon footprint. It can further relieve construction companies from the time-consuming and subjective task of manual method analysis of construction operation, or installation of expensive location tracking and telematics devices. Any small improvement in emission control of the $900 billion construction industry, the third highest producer of industrial-related GHG emissions, can significantly support the goals of GHG emission reductions and can facilitate establishment of carbon footprint monitoring and control policies.

Supplemental Keywords:

Sustainability monitoring, Model for sustainability, Decision-making, Computer models, Computational simulations, Computer generated alternatives, Green construction operations, Emission control technologies, Energy conservation, Monitoring resource consumption

Progress and Final Reports:

Final Report