Innovative Projects Realized

Exploring Social Spaces in Tower Living

As towers get bigger and bigger they form their own structure and systems, which have become a monoculture and an old paradigm. Exploring Social Spaces in Tower Living reimagines the skyscraper as a connected, imaginative and resilient entity in its community. We seek to understand what kinds of programs and spaces bring people together. We ask: How can we make our tower shared spaces be more responsive to today’s social needs?

We propose a three-part study that looks at contemporary towers, built or in a planning process, in Europe, Asia and North America. We will collect, analyze and present data of 50 projects on a comparable ground using highly graphic communication tools.

Firstly, we will conduct a precedent study of projects that are mixed-use and have a focus on innovative shared amenities. We will compare the mix of amenities and programming and their placement within the tower. A presentation to Matchpoint will narrow down the 50 projects to 4-8 projects which we will investigate further in the next stage.

Secondly, 4-8 projects will inform three schematic proposals focusing on diverse amenities that could form part of a final design.

Development and launch of a rules-based engine for medical billing software

In collaboration with our Chief Technical Officer and our Advisory team, the intern will help develop and launch the rules-based engine that optimizes and validates diagnosis and billing codes. This work will involve review of various documents, including but not limited to billing reference guides, the provincial health insurance plan schedule of benefits (e.g., OHIP Schedule of Benefits), extraction of specific information (e.g., submission criteria, keywords, payment conditions) from these documents, and the devleopment of a database codifying this information for inclusion in our software.

We are aiming to launch our billing solution at various academic health family health teams in Ontario beginning June 2022. Completion of the tasks associated with this innovation project will play a critical role in helping us meet this goal.

Labrador Well Decommissioning

SCG Industries is a Saint John, N.B. based environmental remediation company which has done work all over North America and in the Caribbean during the last 30 years. The company uses advanced penetrative site characterization tools to delineate the extent of subsurface contamination, then builds and deploys, or simply deploys remediation equipment and teams to undertake the remediation. In this instance, the client, Department of National Defence, has hired SCG to decommission ~3000 wells at the air base in Goose Bay that were originally established to assess and remediate the site of petroleum contaminants, mostly jet fuel which had been spilled during operations and had subsequently been absorbed into the ground. In order to execute the contract, specialized tools have to be developed to be deployed within each well to cut off the pipe approximately 1 metre below the surface. This project will study the use of the tool in a live trial, and provide recommendations for modifications for use in other circumstances of different schedules of pile made from different materials.

Real-time AI-based Prediction Analysis of 5G network Quality of Service (QoS)

LatenceTech offers a cloud analytics and monetization solution for cellular networks with a special focus on ultra-low latency connectivity. Using SAAS and AI, our solution helps mobile operators, telecom vendors and advanced industries to track, predict and secure the new benefits of 5G cellular technology. Many new innovative services will require a very high and sustained connectivity to function properly and bring the intended benefits. Such new services are Teleoperations of Equipment, Connected autonomous vehicles, Telemedicine, most services using Virtual Reality, etc.
The project consists in performing continuous predictions of quality of service with a special focus on the response time (latency) of 5G cellular technology. Having the capability to detect trends and predict, in anticipation, significant variations in 5G Quality of Service, will allow the solution to send notifications and alarms to warn the innovative service that connectivity issues are about to be experienced and take appropriate action (such as getting into “safe mode”). Furthermore, this predictive information would allow customers (mobile operators) to take palliative and preventive measures to improve the quality of the 5G network.

Design et implémentation d’un outil AutoML

Afin de réduire le temps entre le développement d’un modèle d’apprentissage automatique et son déploiement, un gain substantiel peut être fait via l’exploration de caractéristiques similaires entre cas d’application afin de faciliter l’exploration des modèles les plus prometteurs et la sélection d’un modèle et sa configuration. Ce type d’outils entre dans la famille des AutoML où des étapes importantes du processus de développement de modèle sont automatisées lorsque possible. Dans le cadre de ce projet, l’objectif est de rendre l’outil performant spécifiquement dans les cas d’applications dans le domaine légal québécois.

Volatility forecasting from market and text data

Berkindale Analytics is a cloud-based company and wants to create a next-generation platform to provide both market data and packaged analytics to financial clients via direct download, interface, and dashboards accessible from a web portal.
The general objective of the project is the development of a cloud-based platform for the ingestion and normalization of financial data and the calculation of market analytics. In particular, the project revolves around the construction of a SAAS web platform with data provided by an existing partner. The platform ingests granular Canadian historical market data from all exchanges and alternative brokerage systems to aggregate data products, advanced metrics, and data mining tools for end users
In the specific context of this internship, the first intern will be responsible for developing statistical time series forecasting models, while the second intern will be responsible for developing natural language processing models to extract information relevant to forecast from corporate and macroeconomic announcements and social media text data.

Analyse de cycle de vie prospective pour l’écoconception d’un polymère biosourcé

Climicals développe une solution de conversion des sucres contenus dans des déchets alimentaires en molécules clés pour la chimie verte et la production de différents plastiques biosourcés. Climicals souhaite développer une solution à faible impact environnemental en s’assurant que son approvisionnement, ses procédés de conversion et ses débouchés induisent bel et bien une réduction d’impact environnemental. Les études d’analyse du cycle de vie (ACV) qui quantifient les impacts environnementaux potentiels des biopolymères ne sont pas unanimes sur leurs réels bénéfices environnementaux.

Pour appuyer Climicals dans sa démarche d’écoconception et de positionnement stratégique, une ACV comparant la production de biopolymère (PEF) issu de la solution Climicals avec la production du polymère fossile de référence (PET) sera réalisée. La technologie de conversion de Climicals n’a pas encore été démontré à grande échelle et les filières d’approvisionnement et de débouchés ne sont pas encore mises en place. Ainsi des développements méthodologiques en ACV seront nécessaires pour prendre en compte le caractère prospectif de l’étude (mise à l’échelle industrielle du procédé, intégration avec les marchés futurs).

Treatment of cyanobacteria by flotation

The AquaDaf® is a high speed clarifier for the treatment of surface water with algae. The objective of the project is to perform a laboratory study permitting the optimization of the treatment of cyanobacteria with Aquadaf and in particular to establish a protocol to compare the removal rates of cyanobacteria by flotation and to verify the capacity of the process flotation to avoid cyanobacteria lysis which would liberate toxin release. The project includes literature review on cyanobacteria removal by flotation, protocol establishment and laboratory result analysis and the preparation of a final report and presentation. The benefit to Degremont is that it would allow development of AquaDAF® as an eutrophication treatment method, that focuses on the problem at different phases.

Exploring Recommendations and Best Practices for a National School Food Policy for Canada

With the 2021 commitment to develop a National School Food Policy, Canada joins other G7 countries and much of the industrialized world in prioritizing the health, education and development of children, by ensuring they have access to healthy food at school every day. This research will investigate existing school food programs (SFPs) across Canada and the globe to identify best practices and lessons learned. These findings will inform recommendations for the national policy, made by Food Secure Canada’s Coalition for Health School Food (CHSF), as they engage with governments and communities across Canada. This research and the creation of compelling story vignettes will allow the CHSF to share valuable findings with their 190 members across the country, as provinces, territories, community organizations, and schools work to build and enhance SFPs that meet the needs of their local communities and are based on evidence of best practices.

Data-Driven Real-Time Wildfires Response (WFRT)

Annually wildfires result in considerable losses in British Columbia, in Canada, and in the world. The problem has been aggravated in recent years worldwide due to global warming. Wildfires affect the ecological balance of the planet and can have serious consequences for people, property, and critical infrastructures in the neighbourhood of the fire.

This project will develop a system to help Wildfire Responders to become more effective in managing single and multiple wildfires situations. This will be achieved by: a) Predicting in real-time how the fire advances minute by minute; b) Given the fire advance, the proposed responses, and the interdependencies with critical infrastructures, software-based what-if simulation scenarios will predict the consequences of possible response actions. Fire advance prediction will be based on fire propagation models derived from data collected in real-time by sensors and in historical data from previous fires. Rogers’ communication network, including 4G and 5G technologies will be used to collect the data in real time, and analyze these data.

Development of a digital system of MyCobot 280 Pi

Reinforcement learning has caught significant attention in the past decade with landmark successes including deep Q-net applied to video games and AlphaGo for the game of go. However, the gap is still wide when it comes to application to real world problems mainly due to high training cost. We propose to develop a digital model of a physical system for the purpose of training an autonomous agent. This way, reinforcement algorithms can be trained on the digital model at a fraction of cost. This project will focus on a specific system: MyCobot 280 Pi from elephantRobotics. The digital model will mimic the dynamics of the physical system, and the calibration of the digital model will be done by a reinforcement learning algorithm itself. This project will be a groundwork for subsequent investigation.

Generating internal threat intelligence feed as well as creating an incident response playbook

These days, there is growing concern about the security of confidential data in organizations. There is no doubt
that organizations with high-security measures will witness cyberattacks. Therefore, the question is how we can
prepare our infrastructure and cybersecurity team to deal with these challenges. The incidents response playbook
is a comprehensive plan which has been prepared with a clear understanding of the detection & analysis process,
team responsibility, and recovery plan. The Playbook will help the organization take urgent steps and action in
time to prevent deleterious effects on sensitive and confidential data and infrastructure. In addition, we need to
evaluate our infrastructure based on real threats. By feeding an appropriate threat intelligence into our current
security controls, we can ensure that our security measures have high performance in dealing with threat actors,
and if there are any bugs and gaps, we can find them before they bring about data breaches.