Camera-Based Weight Estimate for the Prevention of Overloading (PI, 07/2024 – 06/2025)
Sponsor: Wisconsin Alumni Research Foundation / US$50,347
The main objective of this project is to create a novel vision-based approach for estimating the weight of a load from 2D images.
Impacts of Drone Distraction on Working Safety at Heights in Construction (PI, 09/2023 – 09/2025 )
Sponsor: National Institute for Occupational Safety and Health / US$365,028
The overall objective of this project is to investigate how the presence of a drone (visual appearance and/or flying sound) in a construction field quantitatively distracts workers at heights and impacts their working safety.
Exoskeleton Readiness-to-Use in Construction (PI, 07/2023 – 06/2024 )
Sponsor: Wisconsin Alumni Research Foundation / US$46,825
The main objective of this project is to create a readiness model to assess the readiness-to-use of the exoskeleton for construction trades.
Unmanned Aerial Vehicles Induced Worker Distraction in Construction (PI, 07/2022 – 06/2023)
Sponsor: Wisconsin Alumni Research Foundation / US$44,663
The main objective of this project is to qualitatively assess the distractions that Unmanned Aerial Vehicles (UAVs) may produce while flying over construction sites.
FW-HTF-P: Collaborative Research: Exoskeleton-Assisted Worker Performance Augmentation in Construction (PI, 10/2021 – 09/2022)
Sponsor: National Science Foundation / US$100,000
This project aims to investigate the impacts of wearing exoskeletons and exosuits (collectively called EXOs) for the future of construction trade workers. The results and findings are expected to shed light on 1) how to design affordable and safe EXO products for trade workers in construction, 2) how to replan construction work or tasks to accommodate the worker-and-EXO partnerships, and 3) how to nurture the construction workforce to embrace the EXO technology.
Multi-Sensory Data Fusion and Analytics for Construction Performance Measures (PI, 07/2021 – 06/2022 )
Sponsor: Wisconsin Alumni Research Foundation / $44,226
The objective of this project is to design a portable, robust sensory data collection platform that could conveniently monitor onsite construction operations without interfering normal construction operation processes.
Impacts of Prefabrication and Integrated Project Delivery (PI, 11/2020 – 05/2021 )
Sponsor: M.A. Mortenson Construction / US$20,000
This project collected 31 hospital/medical center construction projects (20 from UW-Madison and 11 from Mortenson) and compared their performance in the areas of cost, schedule, change management, labor productivity, communication, safety, quality, and business with 15 quantitative and qualitative metrics.
An Update to CII's PDCS Research for the DCC Sector (Co-PI, 12/2019 – 05/2021 )
Sponsor: Construction Industry Institute / US$110,000
The main objective of this project was to identify, analyze, and compare state-of-the-art Project Delivery System (PDS) options for capital projects in the DCC sector. The comparison and analysis results were integrated into the PDS selection procedure. A PDS assessment rubric and decision support tool was developed, which took the form of 36 driving statements within 10 factor groups.
Using RTLS and Computer Vision to Extend Worksite Safety (Co-PI, 04/2020 – 03/2021 )
Sponsor: Mitacs Accelerate Grants / CAD$54,333
Industry Partner: Hydro-Québec /CAD$54,333 (Cash)
This project aims to extend worksite safety of construction projects at Hydro-Québec using computer vision and Real-Time Location System (RTLS) technologies. The main safety risks that are targeted are related to equipment mobility (struck-by accidents) and not wearing Personal Protection Equipment. The idea is to have priori information about the types of expected risks in the planning phase, and then to monitor the site using video cameras and the RTLS.
Multi-Sensor Data Collection, Fusion and Analytics to Support Effective Performance Measures in Construction Projects (PI, 04/2018 – 03/2019)
Sponsor: NSERC – Discovery Grants / CAD$25,800
The objective of this project was to investigate the feasibility of integrating multi-sensory data from video, acoustic, thermal, and other Internet of Things (IoT) sensors to facilitate the measures of construction operation productivity on a construction site. It was expected to help contractors and/or subcontractors evaluate the efficiency of their work more often (e.g. on an hourly or daily basis), so that the productivity problems could be detected and corrected timely.
Video-Based Fall Detection for Construction Workers Safety (PI, 02/2017 – 01/2019)
Sponsor: Mitacs Accelerate Grants / CAD$45,000
Industrial Partner: GreenOwl Mobile / CAD$45,000 (Cash)
The objective of this research was to investigate the fall detection with vision techniques. The investigation focused on the detection feasibility under 1) a single monocular camera and 2) a distributed camera network. The results built a solid foundation to create a vision-based fall detection solution to timely detect and rescue injured workers if fall accidents happen.
Multi-Sensory Data Fusion for Métro Inspection (PI, 10/2017 – 03/2018 )
Sponsor: NSERC – Engage Grants / CAD$25,000
Industry Partner: Société de Transport de Montréal / CAD$11,200 (In-kind)
The main objective of this project was to investigate the feasibility of the fusion of multiple sensory data from ground penetration radar, thermal camera, color camera and laser scanner. The fusion of multi-sensory data helped Société de Transport de Montréal (STM) engineers locate underground water infiltration areas and facilitated their inspection and maintenance of Métro concrete structures.
Automatic Analysis of Ground Penetrating Radar Profile (PI, 12/2015 – 11/2016)
Sponsor: NSERC – Engage Grants / CAD$25,000
Industrial Partner: Radex Detection Inc. / CAD$14,400 (In-kind)
The main objective of this project was to create an automatic analysis method for interpreting the Ground Penetrating Radar (GPR) profiles from Dual-Beam radars. It was expected to reduce the time, cost, and effort required in the current GPR profiles interpretation practices and encourage the GPR use for inspecting concrete civil infrastructures.
Construction Jobsite Monitoring with Multiple Video Cameras (PI, 11/2015 – 10/2016)
Sponsor: NSERC – Collaborative Research and Development Grants / CAD$13,600
Industrial Partner: Hydro-Québec / CAD$8,000 (Cash) and CAD$37,200 (In-kind)
The main objective of this project was to create a novel vision-based prototype that monitors the utilization of labor and equipment resources at construction jobsites. The prototype could reduce the manpower and money required in the current manual monitoring practice. In addition, it helped Hydro-Québec detect potential cost overruns in terms of equipment and labor costs as early as possible.
Camera Deployment Planning and Evaluation in Construction (PI, 11/2015 – 10/2016)
Sponsor: NSERC – Engage Grants / CAD$25,000
Industrial Partner: Sectek Inc. / CAD$8,000 (In-kind)
The objective of this project was to help Sectrek Inc. enhance the effectiveness of its video surveillance systems at construction jobsites. The focus was placed on planning and evaluating the camera deployment of the video surveillance system at a construction jobsite from project owner’s perspective. It reduced the rework in Sectek, considering the current deployment was achieved through experience and trial-and-error.
Video-based Monitoring for Measuring Project Performance (PI, 04/2014 – 10/2014)
Sponsor: NSERC – Engage Grants / CAD$25,000
Industrial Partner: Hydro-Québec / CAD$8,000 (In-kind)
The main objective of this project was to recognize mobile construction equipment at the site of the Romaine Complex project from time-lapse/video cameras. It investigated the feasbility of using the time-lapse/video cameras to complement the current manual monitoring practices in terms of time and cost savings.
Automated As-is Building Information Modeling with Visual and Spatial Data Fusion (PI, 04/2012 – 03/2018)
Sponsor: NSERC – Discovery Grants / CAD$144,000
The main objective of this project was to investigate the feasibility of surveying civil infrastructure with a portable visual and spatial sensing system. The survey results from the system produced accurate, object-oriented parametric models, which facilitated infrastructure construction, maintenance, renovation, and retrofit.
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