U of T Technology & Startup Explorer

Bio-inspired microfluidic layers for switchable window shading.

This invention enables inverter interfaces of renewable energy sources to generate significantly larger active and reactive currents during LVRT conditions. The increase in the active and reactive powers reaches up to 100% and 15% of the maximum power generated by existing methods, respectively. This would make power systems substantially more resilient during disturbances, reducing the risk of grid instability and blackouts.

Logic for relays that can be used to significantly improve the cyber-resiliency of communication-assisted protection schemes.

This invention is a system that presents an original contribution in the form of a knowledge base implemented as an Web Ontology Language (OWL). This system also combines customized wayfinding and recommender systems to support this knowledge base and automate the communication process.

This invention builds around an online system/service that tries to leverage advancements in Building Information Models (BIM), energy-efficiency simulation tools and online social network analysis methods to enable a data-driven approach to building design, planning, construction and maintenance.

The technology uses a combination of sensor information, such as the accelerometer and gyroscope (e.g. from mobile phones or wearable inertial sensors), in addition to WiFi signal strength, to build a system that can achieve accurate location estimation technique for indoor environment.

Monte Carlo Lights is a novel ATSC approach that combines state-of-the-art reinforcement learning and Monte Carlo tree search to optimize traffic flow.

This opportunity is a portfolio of hardware and software techniques that seamlessly accelerate AI/ML applications, while saving on-chip and off-chip memory, bandwidth, and processing power. These compute and compression methods have been shown to deliver a 3x boost in processing speed with 2x-4x increase in storage capabilities (up to 10x for natural language processing).

A method and model for simulating general multi-phase network growth, inspired by the simplified, stepwise behaviours of a unicellular slime mould.

Machine-learning based methods to improve traffic flow through adaptive signal control.