Detection of Mental Health Conditions from Textual Device Communication - Year two

Research into child safety applications using Artificial Intelligence (AI) methods is a new area of investigation. SafeToNet is continuing to develop AI monitoring tools together with a team of researchers at the University of Ottawa. These tools, when used over time, will take advantage of outgoing text-based communications from devices to detect the early onset and progression of developmental and mental health issues in youth.

High Performance Computing (HPC) of Full Waveform Inversion and Reverse Time Migration (FWI/RTM)

We will develop advanced software toolkits for seismic inversion and imaging. These method are called Full Waveform Inversion and Reverse Time Migration (FWIIRTM). The FWIIRTM will be used to obtain accurate 30 images and elastic properties of subsurface complex structures.

Analytics on 5G – Topology through PM correlation

As the 5G Network will be capable of being reconfigured and optimized on-the-fly, they will also be more automated, requiring less manual effort to provision resources and make the most efficient use of bandwidth. The Ciena Analytics as a Service is a suite of tools to assist network operator in pro-active discovery on their network operations. This project will look at integrating new advanced intrepretable Artificial Intelligence and Machine Learning techniques to tackle different challenging networking tasks (e.g. traffic prediction, anomaly detection, topology discovery, etc.).

Energy reduction in HVAC systems in a commercial building environment using data-driven approaches

The main goal of this project is to develop data-driven approaches to reduce energy consumption and cost when operating commercial building’s cooling systems. Indeed, according to recent studies the building sector is one of the largest energy-consuming entities (almost 40% of global energy consumption) and this consumption is predicted to increase by 50% by 2050. Thus, there is an urgent need to provide solutions to reduce energy consumption taking into account the importance to improve environmental sustainability and the increase of electricity prices.

Generalized framework for Prescriptive Machine Learning using IoT datastreams.

Internet of things (IoT) includes of multitude of sensors from a wide variety of applications. These sensors produce high volume and high velocity data. Recently there has been much interest in application of such technologies to improve energy management and agricultural practices. The sensors that are installed in the field transmit real time data regarding numerous environmental variables of interest. This data is then used to forecast a future state and to make a well informed business/operation decision according to an expected future state.

Investigating multi-task learning in semantic parsing

Current research in semantic parsing suffers from lack of annotated data, which is hard to acquire. In this project, we aim at tackling the problem of converting natural language utterances to SQL language (Text-to-SQL) on complex databases in a low-resource environment. More specifically, we focus on the research of how multi-task learning (MTL) can help in this task. We will first identify the related natural language processing (NLP) tasks that can contribute to improving the performance of semantic parsing.

Multi-agent reinforcement learning for decentralized UAV/UGV cooperative exploration

Over the last decade, artificial intelligence has flourished. From a research niche, it has been developed into a versatile tool, seemingly on route to bring automation into every aspect of human life. At the same time, robotics technology has also advanced significantly, and inexpensive multi-robot systems promise to accomplish all those tasks that require both physical parallelism and inherent fault tolerance—such as surveillance and extreme-environment exploration.

Multi-agent reinforcement learning for distributed edge caching

There is an exponential increase in the network traffic worldwide due to the growth of social networks, multimedia sharing web services, streaming of video-on-demand (VoD) contents. However, the bandwidth isn’t growing at the same rate as the demand, resulting in a loss of Quality of Service (QoS) and Quality of Experience (QoE) for the users. Distributed edge caching provides an effective mechanism for mitigating the bandwidth requirements of the growing traffic demands by trading off bandwidth with storage.

Progressive Cybernetics Decentralized Autonomous Organization (PCDAO)

Digitization of assets is becoming a dominant form of business operations today; the Internet of Things and increased connectedness to consumers and citizens alike is creating a decentralized virtual marketplace for digital services and assets. The potential for sharing technology assets is high due to digitization (the new way of referring to digital transformation).

Development of an Extensible Framework for Assessing Digital Health Innovation Hubs (DHI-HUB)

New information technologies are becoming an important part of the health care system. A priority both provincially and nationally is the establishment of an enhanced network of general practitioners using the latest information technologies to acquire, store and use patient information. This will involve deployment of person-centred digitally-enabled information technologies in a new structure known as Digital Health Innovation HUBs (DHI-HUBs). The hubs will provide an opportunity to test innovative health technologies in health care.

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