Projets novateurs réalisés

Production Line Packaging Sensor Optimization

Automated production lines use in food, beverage and pharmaceutical manufacture can subject the product being produced and especially the product packaging to high levels of mechanical stress. These stresses can take many forms, be it impact, side pressure, vertical pressure, etc. Plant quality assurance engineers are constantly making adjustments to their automated systems to reduce these stresses to acceptable levels while increasing throughput. MASITEK’s sensor packages help identify these stresses, especially those that are potentially damaging. As consumers demand more environmentally friendly packaging, sizes of products decrease and speeds of automated handling systems increases it is important that the sensor packages be smaller, more sensitive and more accurate. This project will focus on increasing the sensitivity and repeatability of the sensor packages, significantly decreasing their size, and improving the radio link employed.

Homelessness Prevention at Covenant House Toronto

The proposed research project to be undertaken by the intern is concerning the use of preventative measures to combat youth homelessness and trafficking in Toronto through Covenant House Toronto. Youth homelessness and trafficking are on the rise and researching how prevention for this vulnerable population can be utilized has the potential to significantly reduce rates of youth homelessness and trafficking in Toronto. The project will use both quantitative and qualitative methods of analyzing existing Covenant House Toronto data on the youth that are experiencing or have experienced homelessness and/ or trafficking. The intern will be working towards completing a high-level report that implements the findings and trends from the data to generate recommendations on the next steps to undertake for a youth homelessness prevention strategic plan.

Developments of the data evaluation procedure at the FRS Ion Catcher

Modeling and simulation of a magnetic MEMS Container

Using deep learning methods to solve optimization problems

Control of Behavior in Shared Spaces

SUMAFly – SUstainability Modeling and Analysis of Future aircraft systems

Barcode Image Enhancement Using Deep Learning

The use of barcodes to store alphanumeric information has spread from supermarkets to department stores, the health industry and even on the back of our drivers’ license. Recent years have also seen demand to increase the density of information encoded in barcodes. A Drivers’ License has its personal data encoded in the barcode on the back of the document, and the data embedded is often used as part of an identification/verification process. However, the camera captured picture of the barcode is susceptible to quality degradation and even slight perturbances in the image quality of the barcode (e.g. out-of-focus blur, motion blur, non-optimal lighting) causes failures in its readability. In this project, we aim to use artificial intelligence techniques (specifically deep learning) to improve the quality of Drivers’ License 2D barcode captured with the mobile device cameras in a way that improves its readability for identification or verification purposes.

Antimicrobial Quality-Control of Innovative Space ? and Aviation relevant Insulation Materials

Striking a Perfect Water Balance in Polymer Electrolyte Fuel Cells

Autonomous Bathymetry Vehicle For Tailings Impound Surveys

This research project will be used to help mining operations and other industrial proponents where applicable, ensure the integrity of their tailings ponds, reduce the risk to human life/health, and meet government regulations by reducing cost and logistic barriers to conducting tailings volume surveys.
The goal is to verify that an autonomous vehicle can conduct what would ordinarily be a dangerous sonar survey of a tailings pond. This will be accomplished by creating such a vehicle from easily sourced materials with existing supply lines, testing in variety of situations to gain this knowledge. The vehicle will be constructed from a low draught hydro-jet propelled kayak. The intern will outfit the vehicle with effective yet low-cost nautical autopilot, GPS, fishfinder/aquatic rangefinder, and associated supporting computer and radio equipment to facilitate fully autonomous, and remote-controlled operation.
KMB Resources Group will benefit by gaining knowledge they may choose to employ in their operations.

Smart empathetic speaker based on real-time EEG-based music therapy

During COVID-19 outbreak, many people are suffering the negative emotions, causing anxiety, fear, and depression in daily life. To improve the individuals’ mental health, musical therapy will be employed due to its high value of treatment in the mental health field. In our project, a smart empathetic speaker based on real-time emotion recognition system will be developed. Through electroencephalography (EEG) measurement, the types of signals reflecting the listener’s emotion will be extracted. The deep learning method will be used to recognize the emotions of the user in real-time. By continuous and extensive deep learning process, the emotion recognition system is expected to become more intelligent, and a personalized database of popularly used songs in music therapy will be organized. Finally, the speaker can assign known music to a listener based on existing music therapy experience and adjust the music according to the feedback obtained from the brain signal sensors.