Innovative Projects 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

Biosurfactant Production from Seafood Processing Waste

This project aims at developing an innovative technology through the utilization of fish waste as substrates for biosurfactant production. Through the proposed approach, fish waste will be recovered into fishery peptone and being used as a nutrient substrate for the synthesis of biosurfactant products with promising market values. The outcomes of this project will directly provide the fishery industry a new model of fish waste reuse and management by “turning waste into valuable products”. It will also help reduce waste discharge and protect the environment. Last but not least, it creates revenues by producing high value-added products and consequently promote the sustainable development of fishery and seafood processing industries in Canada and beyond.

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Faculty Supervisor:

Baiyu (Helen) Zhang

Student:

Zhiwen Zhu

Partner:

Springboard Atlantic

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Technological advancements for data collection in animal research

The proposed research project is to program artificial intelligence, as produced by technology company EAIGLE, to monitor animals’ behaviour at the Toronto Zoo. The program will be capable of distinguishing where animals are in their enclosures, between individual animals, and which behaviours they are producing under different contexts. This technology will allow zoos, conservation areas, and researchers to monitor how animals interact with their enclosures and throughout the day, allowing for improved habitats and improved data collection for future experiments. Dr. Jenna Congdon will gain experience with an industrial partner in assisting with the production of technology that is the first of its kind, EAIGLE will be provided with the expertise required to program their proposed artificial intelligence, and the Toronto Zoo will receive the technology necessary to monitor their enclosures and individual animals to ensure for the well-being of their animals.

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Faculty Supervisor:

Suzanne MacDonald

Student:

Jenna Congdon

Partner:

EAIGLE Inc.

Discipline:

Psychology

Sector:

University:

York University

Program:

Assessment of the feasibility of manufacturing and marketing carvacrol-incorporated natural health products

Antibiotic therapy has been the primary approach for strep throat. Although various antibiotics, including penicillin, are effective, bacteriologic, and clinical treatment failures have been reported. Patients are more concerned about soothing the pain during the infection, and green/natural drug therapy with less or no adverse side effects are becoming popular. From preliminary studies and literature, carvacrol has been identified as a potential candidate for antibiotic therapy alternatives. Carvacrol, a bioactive found in several herbal plant extracts, show quick anti-bacterial activity against strep throat causing bacteria. However, it is still a need to understand the feasibility of using carvacrol in safer doses, stability under the manufacturing conditions and potential customer acceptability of carvacrol incorporated throat lozenge. The objectives of the project are to assess carvacrol’s feasibility incorporated dehydrated honey lozenge in manufacturing and marketing. Anti-bacterial activity of incorporated carvacrol in pre- and post-manufacturing will be investigated. Safety concerns, maximum incorporated doses and sensory factors will be assessed by literature search and consumer survey. These findings will help to explore the application of carvacrol as an effective and safe natural health product (dehydrated honey lozenge) in soothing painful inflammation in patients.

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Faculty Supervisor:

Vasantha Rupasinghe

Student:

Niluni Wijesundara

Partner:

Springboard Atlantic

Discipline:

Biology

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Development and market assessment of a reliable and efficacious anthocyanin-based healthy food ingredient

To date, there is a growing attention to the use of plant-food bioactives in disease prevention. Anthocyanin, a colorful plant pigment extracted from purple and blue color fruits and vegetables has been investigated broadly for its cancer preventive and immunity boosting properties. However, anthocyanin degrade during the conventional food processing conditions such as exposure to high temperature and light. Moreover, the benefits of anthocyanin could reduce due to gastric acid and gut enzymes. Therefore, the amount of anthocyanin ultimately absorbed to the body is very minimum and that amount is not able to produce the pronounced health benefits. To overcome above, we will develop anthocyanin-based food ingredient with a protective natural coating. As for the next step, the marketing feasibility of new anthocyanin-based food ingredient will be assessed through gaining consumer feed backs.

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Faculty Supervisor:

Vasantha Rupasinghe

Student:

K.V. Surangi Dharmawansa

Partner:

Springboard Atlantic

Discipline:

Food science

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Tunable, High Throughput UV Exposure Device

Ultraviolet-C (UV) light is able to damage cells and organic matter to make water, air, and high touch surfaces safe for the public. UV-C lamps render microorganisms harmless by damaging their cell structure and DNA. UV-C based water treatment has safely been used for decades by water utilities around the world. Recent developments in technology and research have allowed for an even wide application to clean surfaces, air, and water using UV light. This project proposes a device that will allow for researchers to collect UV data from their experiments much faster than current techniques allow. This device will also make the usage of UV lights more reliable by simplify the way that the turn on and off when shining on a sample. In summary, the proposed device will allow for the faster creation and development of UV-based technologies that keep the public safe.

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Faculty Supervisor:

Graham Gagnon

Student:

Sean MacIsaac

Partner:

Springboard Atlantic

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Point-of-care breath analyzer for early-stage disease diagnosis

As the third documented emergence of an animal-to-human coronavirus during the past two decades (Severe Acute Respiratory Syndrome in 2002, Middle East Respiratory Syndrome in 2012), the current pandemic and near-certainty of future epidemics demands intensified surveillance and proactive screening. Definitive therapy for novel Coronavirus Disease 2019 (COVID-19) is likely at least half a year away. Current standard-of-care diagnostic testing with real-time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) is resource intensive, costly and inaccurate. An alternative, high sensitivity, rapid and label-free technique for detecting and differentiating molecular structures, including viral strains, at the point-of-testing is urgently needed.
Herein, we develop a high sensitivity, rapid near-instantaneous, reagent-free point-of-care testing system for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). We propose to demonstrate the viability of rapid reagent-free detection of COVID-19 in exhaled breath condensate and allied samples (saliva and sputum) using ultra-sensitive nanophotonic structure which will be used as a sensing platform for multi-wavelength surface enhanced Raman scattering/spectroscopy, and further, translate this technology for widespread use in a range of public and health settings.

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Faculty Supervisor:

Nazir Kherani

Student:

Moein Shayegannia

Partner:

Springboard Atlantic

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Microfluidic Hydrogel-based Biomolecule Detection Through Novel Advection Transport

Healthcare requires the early and accurate detection of disease indicators, be they small biomolecules or viruses, which is vital for successful treatments, preventative medicine and disease prevention. Improving turnaround times for early and accurate detection will improve patient care, enable the mass screening of large populations during outbreaks and effectively reduce the diagnostic burden. We have developed a small-scale filter detection device to provide high sensitivity, while being inexpensive and portable for diagnostics at the point of care. Our device can be scaled to detect multiple biomolecules using established paradigms that are used in current standards of quantifications of proteins and other biomolecules in blood, for example, by antibody binding. Antibodies are highly specific and strong binders of unique molecule surfaces, and we have devised a novel way of implementing them for detection, using a secondary fluorescent reporter.

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Faculty Supervisor:

Dae Kun Hwang

Student:

Adrian T Nash

Partner:

Springboard Atlantic

Discipline:

Engineering - chemical / biological

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

Sustainable Development of Late-Life post-SAGD Reservoirs for Energy Recovery

What is left after late-life SAGD production is a large amount of valuable energy in the form of heat contained in the reservoirs. Instead of leaving behind the stored energy in a hot reservoir after many years of SAGD operation, considering energy recovery from post-SAGD reservoirs leads to lower carbon emissions by saving energy already injected in the reservoir rather than leaving it to avoid burning more natural gas; saving money for SAGD operators and helping to make operations more sustainable. The new life of extracting energy from post-SAGD reservoirs will extend the in-situ energy production profile improving the overall energy efficiency of SAGD life cycle supporting long-term sustainable energy development of in-situ SAGD operations.

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Faculty Supervisor:

Ian D Gates

Student:

Pachari Detpunyawat

Partner:

Springboard Atlantic

Discipline:

Engineering - chemical / biological

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Experimental and Analytical Study on Sustainable Sandwich Structures made from Recycled Plastic Core and PET FRP facing

The project seeks to discover the optimum design and commercialization strategy for newly developed sandwich structures derived from recycled plastic for the civil engineering sector. The sandwich structures are highly sustainable and could potentially consume large amounts of the rapidly produced plastic waste. The final sandwich product would have the potential to be used in various applications such as roof panels and exterior/interior walls of buildings. The project’s objectives will be met through experimental testing, analytical modelling, as well as participation in various business-development workshops and engagement with experts in the field.

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Faculty Supervisor:

Pedram Sadeghian

Student:

Raghad Kassab

Partner:

Springboard Atlantic

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

Dalhousie University

Program:

Accelerate

Automated Driver Drowsiness Control Technology Using Artificial Intelligence-based Decision Support System

The main purpose of this project is to develop the methodology to detect and predict driver drowsiness at the early stages using physical and physiological variables. A feasibility test is conducted to evaluate the accuracy and performance of the proposed methodology. The existing databases are leveraged to extract the required data. Signal processing, image processing, AI techniques and decision-making methods are utilized to analyze data for monitoring, detecting, predicting and controlling driver drowsiness. Finally, the ethics application is prepared and submitted to be applied for data collection in the future research experiments.
The other goal of this project is to perform the market research by collaborating with the L2M team. Approximately, 100 potential customers are interviewed to explore the customer pains and the probable solutions for addressing the existing problem concerning driver drowsiness. The collected interview data will then be analyzed to validate the defined hypothesis that leads to making decision whether the process of product development and deployment continued or not.

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Faculty Supervisor:

Birsen Donmez

Student:

Vahid Abolhasannejad

Partner:

Springboard Atlantic

Discipline:

Engineering - mechanical

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

A mobile soil-flushing and enhanced oxidation (MSFEOP) system for the remediation of petroleum brownfields

Petroleum contamination in soil and groundwater caused by the leakage of underground storage tank is one of the most frequently occurred incidents in North America. The cost of remediation can be significantly increased if the contamination was not treated in time or the site is far away from the waste management facility. a mobile soil-flushing and enhanced oxidation (MSFEOP) system is therefore developing for an accessible and affordable options for site remediation. This project is to develop simulation and optimization models for the system with lab-scale experiment data, and case studies of petroleum brownfields. Optimized solutions for site remediation will be generated in scenario based on the preference of potential customers. The outcomes would help validate the idea and commercialize the system.

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Faculty Supervisor:

Bing Chen

Student:

Bo Liu

Partner:

Springboard Atlantic

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

Memorial University of Newfoundland

Program:

Accelerate

Challenges of integrating machine learning in rock engineering design

There is an increasing interest in applications of machine learning to solve mining and geotechnical problems; this is made easier thanks to user-friendly and open source machine learning codes and improved computational power. The benefit of incorporating machine learning in rock engineering design are apparent, including the reduction in the time required to sort and characterize field data and the capability to find mathematical correlations between complex sets of input data. However, there are challenges to be investigated, including the use of qualitative data. This project investigates the readiness of the technical community to integrate machine learning in rock engineering design at this time. To fully realize the potential and benefits of machine learning tools, the technical community must be willing to accept a paradigm shift in the data collection process and, if required, abandon or improve on empirical systems that are considered ‘industry standards’ by virtue of being commonly accepted despite acknowledging their limitations.

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Faculty Supervisor:

Davide Elmo

Student:

Beverly Yang

Partner:

Golder Associates

Discipline:

Engineering

Sector:

University:

University of British Columbia

Program:

Accelerate

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