Deep Learning Techniques for Crop Monitoring

In this project, we will investigate using artificial intelligence to assist farmers and insurance companies by providing information about farms based on our daily observations. AIRM has developed monitoring stations (Crop Sentry) that are installed on multiple farms in Manitoba, allowing us to monitor the crop on a daily basis. Crop Sentry units used lidar […]

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Valorisation de polysaccharides d’algues pour la préparation d’extraits bioactifs à potentiel prébiotique

Au Québec, les algues brunes sont le groupe d’algues le plus abondant. Ces dernières sont principalement constituées de polysaccharides. Il a été démontré que les algues du Québec contiennent des polysaccharides et des polyphénols ayant des bénéfices sur la santé. Une manière de valoriser ces molécules d’intérêt serait de les extraire pour en faire des […]

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Dietary carbohydrates in feline health and disease

There is growing concern from cat owners and veterinarians regarding the dietary macronutrient compositions of commercial cat foods compared to the typical prey of a wild cat and whether this difference is a potential driver for the increased prevalence of obesity in cats. This has resulted in industry trends steering away from high carbohydrate inclusions […]

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Development of electrochemical multiplexed lateral flow rapid testing platforms for the detection and quantification of testosterone and progesterone in blood samples

This research aims at developing a rapid testosterone test kit using lateral flow assay technology, a technology used for example in routine pregnancy tests, but in a quantitative manner that can inform the user of the exact concentration of analyte in the blood sample. The quantification of the assay will be performed by integrating the […]

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3D Detection and Quantification of Weeds in Vegetable Crops Using Drone Imaging and a Digital Twin

Innoptech is building VegForecast™, a digital twin platform for vegetable fields that combines rapid drone flyovers with computer vision and 3D reconstruction to deliver field-level insights as maps and KPIs that support scouting, intervention planning, and in-season decision making. This internship aims to deliver a complete AI module for weeds by training a detection and […]

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Transformer une problématique écologique en ressource énergétique : la biométhanisation de plantes envahissantes, une approche durable pour le lac Osisko

La réhabilitation des systèmes lacustres urbains contaminés en climat froid se heurte à différentes contraintes, tant urbaines que climatiques. Le Lac Osisko est l’un d’eux : soumis à diverses pressions anthropiques, il présente des problèmes importants tels que l’eutrophisation, la contamination des eaux et des sédiments, ainsi que la prolifération d’espèces végétales envahissantes. Les stratégies […]

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Development of a Store-and-Forward Navigation System with Semantic Void Detection for Autonomous Construction Monitoring

Current methods for tracking construction progress rely on manual inspections, which are slow, inconsistent, and often dangerous. This research project aims to automate this process using an agile quadruped robot (a “robot dog”) developed by Noûs Technologies. The interns will create a smart navigation system that uses the building’s digital blueprints to guide the robot, […]

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Access to Health Care for Uninsured Migrants – Strategies for Community Advocacy

This project examines how uninsured migrant parents of babies born in Canada, and their supporters, navigate barriers to registering newborns for provincial health cards. “Uninsured migrants” refers to people who are ineligible for public insurance and lack private coverage or have insufficient coverage. Research shows that hospitals may refuse to register newborns when the mother […]

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ARCHAEOLOGY EXPERT SYSTEM

(1) Overview of the Research Problem Despite rapid advances in Large Language Models (LLMs), their deployment in professional knowledge-intensive sectors remains constrained by hallucinations and data gravity. LLMs frequently generate plausible but unsupported outputs when applied to specialized corpora, while organizations hold vast quantities of “dark data” embedded in unstructured PDF archives. In archaeology and […]

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Self-Improving Agents with test-time compute for FDA

Current artificial intelligence (AI) agents deployed in enterprise settings make static, one-shot decisions and cannot adapt as context changes or learn from the outcomes of past actions. This research addresses two limitations of enterprise AI agents: (i) the inability to dynamically adjust reasoning effort based on the uncertainty and stakes, and (ii) the inability to […]

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