Improving Production Management in a Modular Construction Facility Using Data Modeling and Analytics

Prefabricated construction, as an alternative to the traditional stick-built construction, has its advantages in shortening the schedules and reduce onsite construction exposure. The prefabricated construction components are often produced in offsite controlled environment and shipped to site for installation. Due to its similarity to manufacturing, prefabricated construction provides opportunities for continuous productivity improvements. Through such improvements, production data is required and critical to construct analytical models for measuring progresses.

Artificial Intelligence to Support Autonomous Seabed Mapping Operations

Presently the Ocean Mapping Community is spending a lot of time manually cleaning the raw sonar survey files. If this cleaning process is done by an Artificial Intelligence system as clean as a human would do, this could be transforming the entire Ocean Mapping community. Therefore, we propose a novel solution of using an Artificial Intelligence Algorithm – Reinforcement Learning to clean the sonar survey files. The proposed algorithm was used by Google’s DeepMind to beat GO Grandmasters.

Business Model Innovation for Power Utilities

Research and Development for Modeling the Perceived Value of Energy Consumers is a novel area of study which should help to better understand the energy consumers and the perceived value they place on different services and products. By identifying, understanding potential new products and services the related business models can be developed.

Fish use of restored and natural salt marshes in Maritime Canada

Salt marshes are coastal wetlands that provide many ecosystem services. Many fish species are known to use salt marshes as habitat at some point throughout their lives including those that hold commercial and recreational value. Depending on their location, salt marshes may experience varying degrees of tidal flooding, not only making more areas of the marsh accessible to fish but resulting in excess particulate and dissolved organic matter being drawn out with the ebbing tide.

Life-saving early detection of lung cancer is just a breath away

Screening for lung cancer may soon be as routine as having your blood pressure taken and as convenient as picking up your prescriptions, thanks to a breakthrough innovation by a Moncton-based company. 

As a result of the AI and machine learning expertise of University of New Brunswick biomedical engineering master’s student and Mitacs intern Robyn Larracy, biotech firm Picomole Inc. has developed a first-of-its-kind screening tool that makes lung cancer detection as simple as breathing into a tube. The innovation is expected to be commercialized as early as 2024. 

STRATUM: A Digital Field Notes Tool for Archaeologists

Under the Lab2Market Program, the intern will develop and test a field notes tool called STRATUM to alleviate stresses caused by documentation in the field.

Improving Construction Permitting Process using Predictive Analytics

In public sector, the decision making of construction permitting can have direct impacts on the ongoing urban development. The efficiency and predictability of the review process is critical for municipalities to provide timely and accurate results to the public. As the review process is managed digitally with process data available, using data analytics to develop predictive models can result in improvement of efficiency and predictability.

Application of Light Detection and Ranging in Right-of-Way Management Program

Light detection and ranging (LiDAR) is a method that uses light in the form of a pulsed laser to measure variable distances. These pulses are combined with other data (Global Navigation Satellite System (GNSS) and inertial navigation system (INS)) to precisely obtain the position of points over the shape of the earth and its surface characteristics. The capability of LiDAR to collect an enormous amount of data makes it perfect for pipeline right-of-way (ROW) management.

Relation between biometrics and traumatic brain injury risk: developing a data analysis procedure for concussion risk assessment and management

This project will attempt to uncover more insights into the importance of certain biological, situational and environmental factors that contribute to traumatic brain injuries (TBIs), especially in youth sports. By doing this, we hope to work towards better prediction, prevention, diagnosis and treatment of concussions and other TBIs.

Symbolic Model-Based Design of a Semi-Autonomous Vehicle Prototype Implementing Independent Wheel Torque Vectoring for Training an Advanced Driver Assistance System

There is a strong belief that autonomous vehicles will play a vital role in the future of the global transportation economy. There, however, exists many open challenges which need to be overcome to realize this future vision. One such challenge is the acceptance from the driver to relinquish full control of a vehicle and ultimately putting one’s safety in the hands of a computer.