Paper and Presentation (1 of 2): Risks, limitations and value of AI and Big Data in Construction management.
Abstract: It’s no longer a matter of whether or not but rather how will AI – Artificial Intelligence transform the management of construction projects.
A large volume of data mostly unstructured data is typically generated by construction projects. Most of that data in construction has traditionally been collected on paper and very limited predictive analytics was performed.
Using big data to gain more insights and make better decisions in construction management by not only accessing significantly more data but by properly analyzing it to draw practical building project conclusions. In fact, big data, like truckloads of bricks or bags of cement, isn’t useful on its own. It’s what you do with it using big data analytics programs that count.
From the design phase using BIM – Building Information Modeling, Unmanned Systems to capture and monitor construction progress, to autonomous equipment or smart embedded sensors for asset and project management, this presentation will address the following learning objectives:
- Defining the types of data generated during the life cycle of construction projects
- Identifying the trends for integration of technology in construction management
- Reviewing case examples of AI integration in the build environment
- Recognizing the value of AI and Big data applications in construction management
- Assessing the risks and limitations of transforming and applying smart technology and AI
PMI Talent Triangle: Technical Project Management
Paper and Presentation (2 of 2): Financial impact of unmanned systems, and Artificial intelligence (AI) on construction industry and project management practices
- Lack of innovation and delayed adaptation
- Fiscally conservative company culture resistant to new technologies
- Inadequate knowledge transfer and dissemination from project to project
- Weak project monitoring
Unmanned and Artificial Intelligence (AI) based systems are disruptive technologies that can improve the above mentioned shortcomings; however, this technologies are underutilized by the construction industry. The main focus of this paper is on:
- Analysis of the cultural readiness and resistance of construction industry/companies towards technology.
- Inefficient change management and change agent proficiency in construction industry
- Analysis of the financial impact of the unmanned systems and AI technology on construction industry.
The paper consists of both qualitative and qualitative analysis. The research measured the North American based construction companies, Technology Readiness Index (TRI) in terms of unmanned systems and AI implementation. Qualitative method was used to determine the root cause for the construction industry’s cultural and organizational resistance towards integration of Unmanned and AI based systems into their practice. Quantitative method was used to determine the potential financial impact of disruptive technologies (unmanned and AI systems) on construction industry and particularly construction project management practices.
PMI Talent Triangle: Strategic and Business Management
Biography: Shahab Moeini has over 25 years of experience in leading complex engineering, research and development (R&D), also unmanned autonomous systems projects with various stakeholders in both national and international level. Shahab holds an engineering and geospatial science degree. Shahab is also completing a doctorate degree with a focus on integration of the Artificial Intelligence (AI) into organizational management with the University of Liverpool in the UK.
Shahab started his professional career as an engineer led emergency construction projects from damage estimation to rehabilitation and reconstruction of municipal infrastructure after natural disasters or conflicts. Shahab then worked for 10 years as project manager on hydroelectric and water infrastructure projects before moving on to international relief agencies as a water/habitat engineer and project manager. He managed construction of urban infrastructure and emergency response projects in conflict and post-conflict zones throughout Africa, Asia, and the Middle East, and continued to study advanced programming, geospatial science, and unmanned systems design and development.
Currently Shahab works as senior lead researcher at Centre for Innovation and Research in Unmanned Systems (CIRUS) at Southern Alberta Institute of Technology (SAIT). His research focus is on design and development for aerial, ground and underwater autonomous AI based systems for civil, industrial and humanitarian purposes. Shahab also works on “big-data” processing and cognitive computing and machine learning services.
With over 30 publications and presentations at international conferences, Shahab has served as reviewer, and also chaired several sessions at academic conferences and workshops.