Grant: Discovery Grants Program - Individual
Concordia University
$62,000.00
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
EF 2020-21
Résumé
The productivity and safety of construction projects are two major goals of the construction industry. Current project management approaches mainly depends on human site observations and manual data collection for detecting potential hazards and progress monitoring, respectively. Advancements in Artificial Intelligence (AI) and sensing technologies are providing new means for affordable, efficient and accurate automated data collection, which is expected to contribute to revolutionizing many industries. However, because of the complexity and the dynamic nature of construction projects, applying these advancements in the construction industry is more challenging. In order to take full advantage of these advancements, there is a need to have scientific understanding of the advantages and limitations of each technology, and then to develop innovative solutions to address the specific needs and challenges of the construction industry.
This proposal aims to improve productivity and safety of construction projects using a cyber-physical system approach. The long-term objective of this research program is the knowledge creation related to improving productivity and safety of construction projects using the state-of-the-art AI techniques combined with Building Information Modeling (BIM), near real-time simulation and multi-agent systems, and ultimately realizing the concept of the Smart Construction Site.
The proposed methodology has the following main tasks: (1) Updating the model of the site for progress monitoring using an Unmanned Aerial Vehicle (UAV) equipped with a Light Detection and Ranging (LiDAR) scanner; (2) Recognizing the activities of workers and equipment using an advanced computer vision method; (3) Developing real-time digital twin of the construction project based on a detailed 4D simulation model; and (4) Supporting decision-making on construction sites using a multi-agent system.
The proposed research program is expected to have an impact on the construction industry by improving productivity and safety and reducing the effect of delays caused by unforeseen problems on construction sites. The resulting near real-time simulation calibrated by actual construction progress data will provide practitioners with accurate and reliable information about their projects, which will enhance risk management. It is expected that the results of this program and its HQP training will give the Canadian construction sector a competitive advantage based on technological innovations.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2019-05508
Name nom
Hammad, Amin
Department département
Concordia Institute for Information System Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2019
Award amount
62000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
1001
Area of application group en
Northern development
Area of application group fr
Développement du nord
Area of application en
Construction, transportation and communications
Area of application fr
Construction, transports et communications
Research subject code
1001
Research subject group en
Civil engineering
Research subject group fr
Génie civil
Research subject en
Construction engineering and management
Research subject fr
Génie et gestion du bâtiment
Installment
inst:2-5
Partie
4
Nb partie
5
Application title
Cyber-Physical System Approach for Improving Productivity and Safety of Construction Projects
Keyword
NSERC
Application summary
The productivity and safety of construction projects are two major goals of the construction industry. Current project management approaches mainly depends on human site observations and manual data collection for detecting potential hazards and progress monitoring, respectively. Advancements in Artificial Intelligence (AI) and sensing technologies are providing new means for affordable, efficient and accurate automated data collection, which is expected to contribute to revolutionizing many industries. However, because of the complexity and the dynamic nature of construction projects, applying these advancements in the construction industry is more challenging. In order to take full advantage of these advancements, there is a need to have scientific understanding of the advantages and limitations of each technology, and then to develop innovative solutions to address the specific needs and challenges of the construction industry.
This proposal aims to improve productivity and safety of construction projects using a cyber-physical system approach. The long-term objective of this research program is the knowledge creation related to improving productivity and safety of construction projects using the state-of-the-art AI techniques combined with Building Information Modeling (BIM), near real-time simulation and multi-agent systems, and ultimately realizing the concept of the Smart Construction Site.
The proposed methodology has the following main tasks: (1) Updating the model of the site for progress monitoring using an Unmanned Aerial Vehicle (UAV) equipped with a Light Detection and Ranging (LiDAR) scanner; (2) Recognizing the activities of workers and equipment using an advanced computer vision method; (3) Developing real-time digital twin of the construction project based on a detailed 4D simulation model; and (4) Supporting decision-making on construction sites using a multi-agent system.
The proposed research program is expected to have an impact on the construction industry by improving productivity and safety and reducing the effect of delays caused by unforeseen problems on construction sites. The resulting near real-time simulation calibrated by actual construction progress data will provide practitioners with accurate and reliable information about their projects, which will enhance risk management. It is expected that the results of this program and its HQP training will give the Canadian construction sector a competitive advantage based on technological innovations.