Projets novateurs réalisés

TRLUP-MPWash

MPWash develops a reusable, cartridge-free filter that captures microplastics released during laundry. The project advances prototype validation, regulatory readiness, and commercialization to reduce pollution and strengthen Canada’s cleantech leadership.

TRLUP – GlucoSmart Nanogel – a smart bioactive nanogel for healing diabetic foot ulcers

This project focuses on developing a market and regulatory strategy for GlucoSmart Nanogel, an innovative Canadian-made wound-healing therapy designed for people with diabetes. The nanogel combines infection control, immune modulation, and tissue repair in a single, affordable treatment to improve healing outcomes for diabetic foot ulcers. Over four months, the project will evaluate regulatory requirements, market opportunities, and reimbursement pathways to create a clear roadmap for bringing GlucoSmart Nanogel to market and advancing its real-world impact in diabetic wound care.

TRLUP -VerteVUE Spinal Imaging

VerteVUE is a portable, radiation free, imaging device that will allow clinicians to assess critical anatomical features of the spine at the point of care. VerteVUE supports early clinical decision making when used alongside patient reported outcome measures (PROMs), standardized questionnaires and physical assessments. It also streamlines triage to determine conservative versus surgical care, reducing patient wait times and setting a new standard for precision spinal care.

AI-assisted image segmentation and registration for spine navigation systems

Spine surgery often requires real-time X-ray images to guide surgical tools safely around delicate structures. However, using X-rays continuously during long operations can expose both patients and medical staff to unnecessary radiation. One way to reduce this risk is to use saved X-ray images for navigation rather than continuous exposure; however, this requires precise tool tracking to ensure accurate guidance. ClaroNav Kolahi Inc. (CKI) is a Canadian company that develops surgical navigation systems, including a spine navigation platform that can operate from a saved X-ray image. In this project, the intern will help design a method that uses small reference markers placed on the X-ray machine and visible to a camera-based tracking system, along with artificial intelligence–based image analysis to automatically link the position of surgical tools in real time with that saved image. This ensures navigation remains accurate even if the patient moves or if the image is rotated or scaled. For CKI, this innovation will make their navigation system more reliable and compatible with a wider range of hospitals, while also reducing radiation risks for patients and surgical teams.

TRLUP – AI-Powered Drones for Infrastructure and Industrial Inspection

Aeronovous delivers AI-powered drone inspection solutions for infrastructure, industrial equipment, and wind turbines, with this internship specifically focused on wind turbine applications. The traditional inspection industry relies on costly and inefficient manual methods—rope-access technicians, prolonged turbine outages, and highly variable reports influenced by crew experience and weather conditions—creating significant safety risks, operational downtime, and inconsistent defect detection. Even when drones are deployed, human operators must manually review thousands of images to identify defects, a tedious and error-prone process that can allow critical issues to go unnoticed, leading to equipment degradation and expensive failures. Aeronovous differentiates itself through automated defect detection powered by computer vision, deploying a drone workflow that captures standardized imagery of turbine blades, towers, hubs, and nacelles, then automatically detects, measures, and tracks defects, reducing days of manual analysis to hours of automated processing and enabling operators to schedule repairs with minimized downtime, cost, and risk. Currently in a pre-commercial stage, the core technology has been validated in simulation environments but awaits real-world validation with paying customers in operational settings. To achieve commercialization, the company must establish reliable sensor integration, develop repeatable capture protocols for tall structures, generate labeled datasets tailored to client needs, train models meeting accuracy benchmarks under field conditions, and ensure compliance with Transport Canada regulations and site safety procedures—all while demonstrating measurable return on investment to secure early adopters for pilot programs. This project directly tackles these commercialization barriers through market validation and customer discovery, defining turbine inspection requirements and safety protocols, standardizing image capture workflows using the RGB FPV drone platform, establishing infrastructure for data storage and labeling, training and benchmarking defect-detection models, developing standard operating procedures and ROI frameworks, and securing pilot agreements with prospective clients to validate the technology in live operational environments.

Colchester Food Network Evaluation

The Colchester Food Network (CFN) is a well-established community organization working to improve access to healthy food and build food skills across Colchester County. In 2024, CFN became one of Nova Scotia’s designated Collaborative Food Networks (CFNs), strengthening its commitment to dignity-based food access, inclusive community partnerships, and holistic, culturally responsive programming. With support from the provincial CFN program, CFN delivers a broad range of food-related activities—including a Client Choice Market, youth and adult cooking programs, meal kit distribution, community-led food pantries, and collaborative initiatives with schools, Indigenous communities, and local service organizations. Signature programs such as Kids’ Kitchen Adventures, Cooking on a Shoestring Budget, and Cooking with G-Ma and Friends reflect CFN’s values of accessibility, respect, and inclusion.
To ensure these programs are meeting local needs and to support learning and accountability, CFN will carry out a structured evaluation of its 2025–2026 programming. This evaluation will assess the reach, effectiveness, and community impact of CFN activities delivered between April 2025 and March 2026, while also fulfilling provincial requirements for annual reporting.
A research intern will be placed with CFN to support the design and implementation of a practical monitoring and evaluation system. This will include the development of tools such as participant tracking templates, post-program feedback forms, and interview or focus group guides for gathering community insights. The intern will help collect both quantitative data (e.g., number of participants, food distributed, pantry usage) and qualitative stories that capture the lived experience of program users, volunteers, and partners.
The evaluation will pay special attention to equity and inclusion, exploring how CFN’s programming reaches and supports groups facing higher food insecurity. Insights will be used to identify what’s working well, where improvements can be made, and how CFN can continue to respond to community priorities.

L2M – Novel Cryo-Microfluidic Device for Cell Cryopreservation

Developing a novel cryo-microfluidic device for ultra-rapid, cryoprotectant-free cell preservation. The project advances prototype design, testing, and market validation to improve biotechnology and regenerative medicine applications in Canada.

L2M-Digitalizing On-Demand Inventory with AddManuChain Platform: An Innovative Bridge between AI and Additive Manufacturing for Sustainable Industrial Operations

The project aims to prove and commercialize AddManuChain, a computerized inventory system that will deploy on-site 3D printing to print certified parts on location at the remote industrial sites, including offshore oil platforms, mining operations, and also in the maritime facility to eliminate the expensive effect of long downtimes incurred during part replacement. The project will build a strong business case to replace traditional rush-freight logistics with localized production capabilities that meet high standards in the industry by specific measures such as developing prototype workflows that reflect on certification requirements, conducting thorough stakeholder interviews, and undertaking intensive economic modelling. The new innovation is based on the established Canadian leadership in high-order manufacturing, thus making the country a leader in terms of the digital transformation of the industrial supply chains. The established research and development base, manufacturing experience, and continuous emphasis on innovation are the attributes of Canada that are the best foot forward in this innovation. With an advantage in the additive manufacturing and Industry 4.0 technologies, the project will also strengthen the reputation of Canada as a world manufacturing leader. The expected results are the increased resilience in the Canadian resource base, increased domestic advanced manufacturing capacity, significant benefits to the environment through less logistics emissions as well as competitive edge that Canada would get in the international market through innovative next-generation smart manufacturing solutions. As a result, this study has placed Canada at the forefront of trans formative design, production, and distribution of essential elements, thus creating new prospects to the Canadian business on both fronts, as well as mitigating viable challenges faced by remote processes of industrial activities.

L2M – VirtualSLP

VirtualSLP is an AI-powered platform transforming care for patients with neurologic speech disorders. Conditions such as ALS often cause bulbar impairments—loss of speech, swallowing, and facial expression—that devastate quality of life. Yet clinicians, particularly speech-language pathologists (SLPs), face overwhelming barriers: caseloads as high as 600 patients per year, only 15–20 minutes per visit, and no standardized, easy-to-use tools. As a result, care is inconsistent, delayed, and less effective than it could be.

The need for better solutions is clear. Our team, led by Dr. Yana Yunusova, has decades of experience at the intersection of research and clinical practice. Communities of Practice uniting 200+ SLPs in Canada and the U.S. further highlight the urgency and scale of the problem.

VirtualSLP addresses this gap with a web-based platform that integrates remote multimodal assessments and AI-driven insights. Patients complete validated assessments online, while the platform extracts 200+ acoustic and movement features to detect early signs of bulbar disease and classify severity. Upcoming modules will predict disease progression within a six-month window and deliver GenAI-powered, evidence-based recommendations, enabling personalized, efficient, and scalable care.

Backed by $3M in research funding, VirtualSLP is clinically validated and built with direct input from both patients and providers. With a $400M obtainable market and 70% of SLPs projected to adopt telehealth by 2030, it is positioned to become a game-changing solution that improves patient outcomes, streamlines clinician workflows, and scales across healthcare systems.

VirtualSLP: where AI meets patient-first neurological care.

L2M – Visum Neurotechnologies

The project aims to develop a non-invasive, dual-modality tool combining eye-tracking (ET) and functional near-infrared spectroscopy (fNIRS) to measure cognitive capacity and enable early detection of cognitive impairments in older adults. Using short-term memory tasks, it captures objective biomarkers (e.g., pupil size and prefrontal neural activity) to outperform the conventional tests in sensitivity and cultural neutrality.

L2M Novel Hybrid Scanless Confocal Fluorescence Microscopy System

Our project introduces a novel hybrid fluorescence microscopy system that merges the strengths of light-sheet and confocal microscopy while eliminating their key limitations. The system is fully scanless, removing the need for any motorized scanning devices—resulting in faster, simpler, and more reliable imaging. It also integrates a signal intensifier to detect weak fluorescence and a microfluidic channel for automated, high-throughput sample handling.

From an academic perspective, this technology enables rapid, high-resolution, and low-phototoxic imaging, ideal for studying cancer cells, microorganisms, and developing tissues. The combination of scanless confocality and light-sheet illumination allows continuous, non-invasive observation of cell behavior, division, and drug response in real time, even in samples with weak fluorescence signals.

From a business perspective, the platform offers a compact, affordable, and user-friendly alternative to existing expensive and complex microscopes. By combining speed, resolution, and automation in one system, it reduces costs, training time, and maintenance—providing strong return on investment for research and clinical users. With the global fluorescence imaging market expected to grow from USD 11 B to 20 B by 2030, this hybrid scanless microscopy system stands as both a scientific innovation and a high-potential commercial product for research, diagnostics, and drug discovery.

L2M Highly Efficient DC-DC Converters for Small Offshore Oil Rigs

Offshore oil rigs play a critical role in Canada’s energy industry, but they rely heavily on diesel generators that are expensive, polluting, and difficult to maintain in remote marine environments. This project explores the development of highly efficient DC–DC converters—advanced electronic devices that improve the way electricity is managed on offshore platforms. These converters make it possible to integrate renewable energy sources, such as solar and wind, with existing systems, helping to reduce fuel costs and greenhouse gas emissions.
The goal of this project is to design, test, and evaluate a converter prototype optimized for small offshore oil rigs. By focusing on efficiency, compact size, and durability in harsh marine conditions, the project will provide a practical solution to improve energy reliability and sustainability. The outcomes will benefit Canada by supporting cleaner energy use in offshore operations, reducing environmental impact, and advancing technologies that can also be applied to other remote and marine industries.