What is Artificial Intelligence (AI)? Branches of Artificial Intelligence AI in Construction Engineering & Management Roles of AI in Construction Engineering & Management Smart optimization for mega construction projects Case study- Bispevika, a building Project in Oslo, Norway Human-AI Collaboration Applications of AI in Construction Industry Future Application of AI Presented by Team Bispevika References

1. Roles of Artificial Intelligence In
Construction Engineering &
Management; review & future trend
• Name- Kundan Sahadev Sanap
• Roll No.- 202030016
• Subject- Technical Seminar
• Guide- Dr. Vishakha Sakhare
Veermata Jijabai Technological Institute,
Matunga

2. What is Artificial Intelligence (AI)?
• AI = Artificial intelligence
(Human Made) (Ability to understand, think and learn)
• Artificial Intelligence is a way of making a computer, a
computer controlled robot, or a software think
intelligently, in a similar manner as an intelligent human
think.

3. Branches of Artificial Intelligence
• Expert Systems:
• An expert system is an artificial intelligence application that uses a knowledge base of human
expertise to aid in solving problems.
• Robotics:
• It is designing, operating and constructing the robots by
using the concepts of both science and engineering
techniques
• The main objective behind robotics is to help human kind
in making tough tasks easier.

4. Branches of Artificial Intelligence
• Machine Learning:
• It enables the machine and computer systems to process, analyze and interpret data with the aim
of providing solutions for the problems that humans face.
• Fuzzy Logic:
• Its approach imitates the way of decision making in human behavior which covers every
possibilities between Yes or No.
• Neural Networks:
• It comprised of a node layers, containing an input layer, one or more
hidden layers, and an output layer
• If the output of any individual node is above the specified threshold value,
that node is activated, sending data to the next layer of the network.
Otherwise, no data is passed along to the next layer of the network.

5. Branches of Artificial Intelligence
• Genetic Algorithms:
• The genetic algorithm is based on the evolutionary idea of natural selection and genetics.
• Also is an evolutionary algorithm which produces each individual from some encoded form
known as a "genome" or "chromosome”.
• Natural Language Processing:
• This process involves a machine receiving human
sound from interaction and converting it to text
format so that it can be easily read and
understood.

6. AI in Construction Engineering & Management
• Automation:
• Make the project management more Automable.
• E.g. Monitoring of construction sites by drones & sensors to record data,
• Risk Mitigation:
• We can monitor, recognize, evaluate & predict the potential risks in all terms like safety,
quality & cost
• Also can measure the probability of failure occurrence
• High Efficiency:
• Process mining
• Use of robots on construction sites

7. AI in Construction Engineering & Management
• Digitalization:
• Leading role by BIM
• Integration of BIM & AI
• Computer Vision:
• Towards making an Intelligent management of construction project, it is used for
inspection and monitoring purposes.
• For inspections like Automated damage detection, structural component recognition and
condition identification.
• For monitoring like strain estimation, displacement, crack width, etc

8. Roles of AI in Construction Engineering & Management
• Smart Optimization for mega construction projects
• Case study on AI based Digital tools

9. Smart optimization for mega construction projects
• Optimization-
• The action of making the best or most effective use of a situation or resource.
• Main Objective-
• To optimize the resource utilization in order to minimize the project duration & cost
and to maximize the quality simultaneously.
• Proposed software-
• Based on CPM & GAs named as SCPMS i.e. Smart Critical Path Method System.
• Objectives:
• To increase resource use efficiency
• To reduce construction time
• To minimize construction cost
• Measure and Improve the quality of work

10. Smart optimization for mega construction projects
• Decision Variables- The present model is designed to
consider all relevant decision variables that may have an
impact on project time, cost or quality.
• Classification
1. Construction material and/or methods
2. Crew formation or Manpower
3. Machinery efficiency
4. Contractor’s class
5. Owner’s class
• In order to control the complexity of the optimization
model, the present model combines these five major
decision variables into single alternative named resource
utilization

11. Smart optimization for mega
construction projects
• Model Implementation
• Initialization
• Evaluation
• Generation

12. Smart optimization for mega construction projects
• SCPMS is created to provide a number of new and unique capabilities, including:
• To rank the obtained optimal plans according to a set of planner specified
weights that represent the relative importance of time, cost, and quality in the
analyzed project.
• To visualize and view the generated optimal tradeoff between construction
duration, cost, and quality according to planner ranking relative weights to
facilitate the selection of an optimal plan that considers the specific project
needs.
• To provide seamless integration with available project management
calculations to benefit from their practical project scheduling and control
features.

13. Case study- Bispevika, a building Project in Oslo, Norway
• chosen case is Bispevika, a building project in Oslo, Norway.
• The project consists of approximately 7 years of construction and NOK 4.5
billion.
• Bispevika was chosen based on its non-traditional way of working regarding
innovative processes and tools.
• The Bispevika-mindset is based on a lean approach. To get a grip on the
implementation of AI, it is chosen to look closer into the implementation of the
three digital tools.

14. Case study- Bispevika, a building Project in Oslo, Norway
• Three Digital tools:
• Touch plan:
• It is a web-based construction collaborative tool, which is a digital version of the tools in the LPS.
• Digitization
• Synchro:
• It is a 4D digital construction platform, which gives the workers the opportunity to visualize,
discuss and collaborate in order to find all possible constraints before executing.
• Digitalization
• ALICE:
• It is based on AI which analyze, optimize and provide an output, such as a schedule.
• Digital transformation

15. Methodology used
• Interviews
• Internal Interviews
• Seventeen semi-structured in-depth interviews
• 1 interviewee represented the company management
• 3 represented the project management
• 10 represented the operating department and
• 3 represented different subcontractors
• External Interviews
• With the aim of unveiling useful experiences considering implementation of AI in other
industries.
• The three interviewees represented three different companies.
• Norwegian AI Lab
• Inmeta
• Spacemaker

16. Human-AI Collaboration
1. Since last few years it is proven that, Artificial Intelligence can respond better than
humans in some situations.
2. Humans can’t compete with AI regarding analysis of data, information and knowledge,
likewise AI cannot compete with a human’s ability of pedagogy, creativity, visions and
ethics.
3. Although, the tasks and responsibility are distributed between the human and AI, it can
be difficult for the human to trust the AI output. This is one reason that adoption of
some AI tools remains low in application areas where explain ability is useful or indeed
required.
4. Important factor regarding trust is time. If the machine operate reliably and predictable
over a long time, humans will start to trust AI to the same degree they trust other
humans.

17. Applications of AI in Construction Industry
• Today there are some start-ups that offers applications relevant to scheduling and image
recognition.
• Using historical figures in addition to human-inputs, algorithms can consider millions of
alternatives for project delivery and continually enhance the schedules.
• Image recognition can identify unsafe workers and aggregate this data to inform future
training and education priorities. However, any AI algorithm is based on training rather
than programmed, which means that algorithms needs a certain amount of data to perform
at the level of humans.
• AI may help the construction industry to overcome the industry’s greatest challenges,
including costs, scheduling and safety.

18. Future Application of AI Presented by Team Bispevika
1. Machine Learning- Scheduling
2. Pattern Recognition- Detection of unregistered people
3. Automation- Robots executing dangerous work
4. Automation- Self driving construction machinery
5. Automation- quality assure work

19. References
• Remon Fayek Aziz a, *, Sherif Mohamed Hafez a , Yasser Ragab Abuel-Magd, Smart
optimization for mega construction projects using artificial intelligence
• Wolfgang Eber, Potentials of artificial intelligence in construction management
• Schia, M.H., Trollsås, B.C., Fyhn, H., and Lædre, O, The Introduction of AI in the
Construction Industry and its Impact on Human Behavior
• Philip McAleenan, Moral responsibility and action in the use of artificial intelligence
in construction
• Fedor Klashanov, Artificial intelligence and organizing decision in construction

20. Thank You!