Innovations Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Novel healthcare focused videoconferencing system and Congenital Anomaly detection using Deep Learning

m-Health Solutions specializes in remote patient monitoring and cardiac diagnostics. Using leading-edge technologies. m-Health Solutions (MHS) offers a range of services for clients of all ages and are a leader in remote healthcare. The Centre for Mobile Innovation (CMI) at Sheridan College has collaborated with MHS and is in the process of developing a healthcare focused video conferencing system that offers a mobile-friendly means for patients to attend their appointments with physicians and healthcare providers online. Currently, MHS’s 100,000 patients need to make multiple trips to meet their healthcare providers which is inconvenient, increases the Carbon footprint and consumes substantial resources both from MHS and the patients. The proposed research project involves two main components: 1) enhance and refine the Mobile Client Portal we have developed in collaboration with MHS and deply it on an on-premise server at MHS with integration with MHS’s CRM using web services. Secure authentication will be accomplished by using Active Directory and SSL. Leading-edge web technologies will be used, namely: Jitsi Meet video conferencing platform, React, Java scripts, CSS, HTML; 2) Explore Data Science techniques to reveal insights in the large datasets MHS has on cardiac arrhythmias.

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Faculty Supervisor:

Ed Sykes;El Sayed Mahmoud

Student:

Jayce Merinchuk

Partner:

M-Health Solutions

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Sheridan College

Program:

Accelerate

The Representation of Visible Minorities, Indigenous Peoples and Women in Senior Leadership Positions in London, Ontario

The aim of the current project is to assess the level of representation of visible minorities, indigenous peoples, and women in leadership roles in the public and non-profit sectors in London. The current project also aims to conduct in-depth interviews with key stakeholders in London to determine if and what some of the organizations in the public and non-profit sector in London have done to improve the representation of visible minorities, indigenous peoples, and women over the last four years. The current project will benefit Pillar Nonprofit Network in that it will provide evidence regarding the level of diversity in leadership positions in the public and non-profit sector. The current project will also provide useful information about promising practices to increase diversity in these leadership positions. Overall, the current project will help to indirectly evaluate board recruitment strategies including the use of the OnBoard program in London.

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Faculty Supervisor:

Victoria Esses

Student:

Alina Sutter

Partner:

Pillar Nonprofit Network

Discipline:

Psychology

Sector:

Other services (except public administration)

University:

Western University

Program:

Accelerate

Work Improvement and Data Analytics for Industrial Steel Fabrication

Work improvement is critical for performance increase in business environments. It is used to identify bottlenecks and inefficiencies in the manufacturing and other production processes, and to improve work performance by removing non-value-added activities. To conduct work improvement, the Lean Manufacturing concept is often used along with the Value Stream Mapping (VSM), a tool for visualizing the production processes and productivity metrics. In this research project, Ocean Steel & Construction Ltd., out of Saint John, New Brunswick has partnered with the research team at the University of New Brunswick’s Off-site Construction Research Centre to study their production facility and improve their productivity. In this proposed study, four sub-objectives are defined: (1) use process mapping to document the steel fabrication processes and collect productivity data at each process (e.g. workstation); (2) conduct Exploratory Data Analysis (EDA) to summarize the productivity metrics for each process; (3) use regression modeling to develop predictive models for processing time, and correlation analysis to identify the impact factors of productivity; and (4) develop Value Stream Mapping (VSM) to improve the production processes and incorporate predictive models into the VSM approach. The intern will have a chance to interact with professionals and gain exposure to the construction industry.

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Faculty Supervisor:

Zhen Lei

Student:

Lucas Marshall

Partner:

Ocean Steel & Construction Ltd

Discipline:

Engineering - civil

Sector:

University:

University of New Brunswick

Program:

Accelerate

The Development of Anti-gingivitis Probiotics Derived From the Human Oral Microbiome

The human oral cavity contains over 700 different bacterial species. In healthy people, these bacteria are living in harmony and not likely to cause diseases. However, sometimes this bacterial balance is disturbed as the oral pathogenic bacteria start to overgrow causing many oral implications such as halitosis, sore throat, dental caries and gingivitis. A promising solution to tackle this microbial population destabilization is the use of beneficial microbes called probiotics. Previous investigations showed that the oral commensal Streptococcus salivarius is an excellent candidate for the development of new probiotic treatments. This bacterium is human friendly and is one of the first microorganisms to colonise the babies few hours after birth. S. salivarius can produce unique molecules which can be used as molecular missiles to attack pathogenic bacteria and restore the microbial balance to the oral cavity.

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Faculty Supervisor:

Michael Glogauer;Bernhard Ganss

Student:

Abdelahhad Barbour

Partner:

Ostia Sciences

Discipline:

Dentistry

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Ultrasound image analysis for identifying blood in an existing effusion in knee joint

Ultrasound, an inexpensive, accessible and portable device is gaining popularity in various disease diagnoses. In this project, we aim to analyze the ultrasound images generated for knee joint for diagnosing hemarthrosis (joint bleeding), a common clinical event in patients with severe hemophilia. We aim to analyze the images using machine learning and deep learning techniques. As the major challenge in this case is the scarcity of number of cases with hemophilia, we plan to use one-shot learning techniques, which use neural networks to learn the similarity features between images and need only few training images. The learned model will be deployed in 16 Bit software for diagnosing hemarthrosis in hemophilic patients.

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Faculty Supervisor:

Vassilios Tzerpos

Student:

Rajshree Daulatabad

Partner:

16 Bit Inc.

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

York University

Program:

Accelerate

Innovations in Marine Food Systems

Coastal communities in British Columbia are economic hubs and gateways to marine resources. The health of these communities’ depends on having sustainable food systems. How these communities’ access and eat local marine foods can be threatened by economic and environmental pressures – including the impact global climate change has on marine environments. In order to thrive, communities are innovating to ensure they can access and eat nourishing local food. The objective of this research is to better understand the role that innovations play in providing food security in local marine food systems in small coastal BC communities. We will be exploring how novel ideas, technologies, or systems come to be, and what combinations of actions, assets, and experience are leading to these innovations’ successes. By engaging with communities to explore the forefront of innovation in local marine food systems, we aim to generate knowledge that benefits other communities facing similar challenges

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Faculty Supervisor:

Ann Dale

Student:

Taylor Reidlinger

Partner:

Ecotrust Canada

Discipline:

Environmental sciences

Sector:

University:

Royal Roads University

Program:

Accelerate

Ex-vivo Device for Screening the Efficacy of COVID-19 Vaccines and Producing Antibodies

COVID-19 has significantly impacted the health of the global population. Although timely detection and isolation are important, vaccination is probably more effective in fighting against COVID-19. Our proposed ex-vivo can help the validation of the COVID-19 vaccine and produce antibodies for COVID-19. The benefit to the Canadian community and the industry partner is palpable.

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Faculty Supervisor:

Jie Chen

Student:

Pedro Duarte;Yiwei Feng

Partner:

Hidaca Inc.

Discipline:

Engineering - computer / electrical

Sector:

Information and cultural industries

University:

University of Alberta

Program:

Accelerate

Heavy Gauge Line Pipe Development with The Thermomechanical Processing Model Implementation

The project objective is to understand and apply the metallurgical fundamentals for the heavy gauge steel product development. The major tasks can be divided into two groups: (A) the precipitate investigation through conventional and advanced characterization techniques such as transmission electron microscopy (TEM) and (B) the implementation of thermomechanical processing models for the rolling schedule design, which demands rigorous validations against the rolling mill and/or product data. Our robust thermomechanical processing models will be integrated with the Integ model. A successful study of these fundamental issues will help our industrial partner (EVRAZ) understand the precipitation behavior and improve hot rolling schedule designs, facilitating the heavy gauge product development and then reducing the economic cost for oil and gas transportation, especially for regions in Northern Canada. It will also increase the international competence of EVRAZ for heavy gauge products.

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Faculty Supervisor:

Hatem Zurob

Student:

Shenglong Liang

Partner:

Evraz

Discipline:

Engineering

Sector:

University:

McMaster University

Program:

Accelerate

Mitigating Snowy Owl Aircraft Collisions by Relocation

To aid in active management of Snowy Owls and other raptors at airports, it is essential to understand the spatial distribution and movement behaviour of birds both on and off the airfield. The impact of airfields on birds may be particularly pronounced because airfields provide open, undeveloped land similar to early successional habitats that are perceived as high quality by many species. Airport collisions are a significant threat to Snowy Owls and humans, and preventative measures cost over $500 million dollars each in North America alone. By using tracking technology and GIS software, our project will quantify movement data and environmental factors influencing relocations of Snowy Owls from airport facilities. This research will improve our understanding of Snowy Owl relocation behaviour and provide critical data to improve relocation efforts and to minimize collisions between airplanes and Snowy Owls.

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Faculty Supervisor:

Kyle Elliott

Student:

Rebecca McCabe

Partner:

Falcon Environmental Services

Discipline:

Resources and environmental management

Sector:

Professional, scientific and technical services

University:

McGill University

Program:

Accelerate

Machine learning and the COVID Black Box: Safe monitoring of COVID-19 ICU beds, assessment centres, and surgeries

The project aims to optimize healthcare provider and patient safety and monitor PPE use, to optimize resource utilization during the COVID-19 pandemic. Assessment of surgical data from an operating room is a complex process that may require significant resources such as expert input and advanced technology. Automation brings a considerable opportunity to greatly reducing these significant resource requirements – e.g., using computer vision software to detect clinically relevant actions during surgery. With the data collected from operating room black box, the main aim is to analyze 1) hand hygiene, 2) adherence to personal protective equipment (PPE) protocols, 3) breaches in safety, and 4) system vulnerability in Ontario.

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Faculty Supervisor:

Animesh Garg

Student:

Priya Thakur

Partner:

Surgical Safety Technologies Inc

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Pricing model from econometric perspective and visualizing promotion cannibalization effect on promotion activities

Leveraging the entirety of point of sale and loyalty data collected across a category, as well as additional socio-economic and other supporting data sources, apply statistical modelling to identify the own-price elasticity of demand and cross-price elasticity of demand at regular and promoted price points across Unilever’s portfolio within that category. Subsequently measuring the promotional cannibalization of Unilever’s temporary price reduction activities across the market to assess the promotional events with the highest return on investment and revenue optimization potential.

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Faculty Supervisor:

Ricardas Zitikis

Student:

Lingzhi Chen

Partner:

Unilever Canada Inc

Discipline:

Statistics / Actuarial sciences

Sector:

University:

Western University

Program:

Accelerate

Developing a Remote Search Engine for Histopathology Scans

The wide-spread adoption of digital pathology has opened new horizons for histopathology. Artificial intelligence (AI) algorithms are able to operate on digitized slides to assist pathologists with different tasks. Whereas AI involving classification and segmentation methods have obvious benefits for image analysis, image search represents a fundamental shift in computational pathology. Image-based search for digitized pathology slides can provide pathologists with unprecedented access to the evidence embodied in already diagnosed and treated cases from the past. Huron Digital Pathology has developed and designed an image search system for histopathology images, called Yottixel. The proposed project is the enhancement of Yoittixel search algorithm by incorporating a novel approximate k-NN technique. The proposed method could enable up-to 10-fold speedup in searching and offer more efficient utilization of computational resources. These enhancements provide competitive advantage to Yottixel as a product, especially in hospitals and labs where computing infrastructure are not sufficient for hosting a sophisticated image search engine on-site. The ultimate goal of the research is to develop Yottixel into a robust and efficient search engine for digital histopathology archives. It has potential to be a screening tool to both speed up and improve the accuracy of cancer diagnoses by pathologists.

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Faculty Supervisor:

Hamid R Tizhoosh

Student:

Shivam Kalra

Partner:

Huron Digital Pathology

Discipline:

Engineering

Sector:

University:

University of Waterloo

Program:

Accelerate

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