Conestoga news

August 9, 2024 3:22 PM

Students use AI and machine learning to tackle real-world challenges

Students in Conestoga’s Applied Artificial Intelligence & Machine Learning (AAIML) program shared innovative approaches to tackling real-world challenges at their recent project showcase.

Showcase for Applied Artificial Intelligence & Machine Learning program
Vinith Shadu Shetty and Rubel Thomas Binu harnessed machine learning to advance drone technology significantly for their project AeroWatch.

Drone surveillance, improving diagnostic accuracy to reduce hospital readmissions, investment optimization and plant identification were among the projects presented at the Waterloo campus on July 29.

“The students in the AAIML program have demonstrated creativity and originality in these capstone projects,” said Jim Edwards, dean of the School of Applied Computer Science & Information Technology. “We are incredibly proud of their solution-oriented approach to solving industry challenges using AI competencies they have learned over their time with us.”

The competition open to students in the final term is a chance to demonstrate what they’ve learned in the program that combines a basis in artificial intelligence (AI) algorithms and computer science.

Judges listened to presentations by each team and one was chosen to represent the program at the Tech Showcase on August 13, which presents the Best of Program student projects from the School of Engineering & Technology and the School of Applied Computer Science & Information Technology.

The showcase highlighted the students’ contributions to AI and machine learning advancements, said Pejman Salehi, executive dean of the School of Applied Computer Science & Information Technology and School of Creative Industries.

“Students in Conestoga’s AAIML program gain skills in AI algorithms, machine learning frameworks, data analysis, and programming. They also learn to design technology stacks, evaluate AI and machine learning algorithms, and develop software solutions,” Salehi said. “Project showcases provide students with real-world experience, valuable feedback, and preparation for successful careers in the evolving field of AI and machine learning.”

The project going on to Tech Showcase is AeroWatch by Vinith Shadu Shetty and Rubel Thomas Binu.

The pair harnessed machine learning to advance drone technology significantly, improving the accuracy and reliability of object detection in drone imagery to become an invaluable tool for many users, including search and rescue operations, environmental monitoring and urban planning. 

“Essentially, anyone who needs accurate, real-time information from drones will find our work valuable,” the team explained in a written summary.

As drones become more integral to various sectors, their ability to perceive their environment accurately is crucial. Traditional object detection models often fall short when dealing with the complexities of images, such as cluttered backgrounds, and addressing those challenges makes drones more effective and reliable in critical applications.

“This improvement means better safety, faster emergency response, and more precise data for research and planning, benefiting everyone who relies on drone technology.”

Another team developed Road Sense, providing real-time road damage detection and severity assessment using open-source images to save drivers money by reducing vehicle damage from hazards and enhance road safety.

Earlier diagnosis of autism is the aim of ASDInsight, a tool parents can use at home to assess their child’s autism risk by capturing eye movement and social interactions through a webcam combined with a questionnaire. The hope is to leverage technology to reduce the gaps in diagnosis and improve outcomes and quality of life through early intervention.

School chair Leigh Willis said the showcase is an opportunity for the students to share their original ideas and the hard work that went into making them reality. “Students expressed originality with their project proposals. They were looking forward to showcasing potential solutions benefitting needs within industry.”

Conestoga’s Applied Artificial Intelligence & Machine Learning program is a two-semester graduate certificate teaching how to design a successful technology stack for the acquisition, analysis and resolving of emerging industry challenges with advanced computer resources and infrastructure. Students will advance their existing software development skills with real-world projects designed by Conestoga's experienced faculty and researchers.

The program is part of the college’s School of Applied Computer Science & Information Technology.