The Avalanche Research Program at Simon Fraser University and Avalanche Canada are conducting a study to examine how winter backcountry recreationists, including backcountry skiers and snowboarders, mountain snowmobile riders and snow shoers, seek and use avalanche safety information. Avalanche Canada and Park Canada publish avalanche bulletins daily to provide backcountry users with information on avalanche hazard. The goal of the research is to examine whether recreationists use Avalanche Canadas information products as they are intended to be used.
The Nymi band is a unique wearable that authenticates the wearer using biometric data to provide continuous authenticated presence in smart environments. Nymi enables wireless user proximity & presence solutions, removing the need for physical interaction with IoT, mobile and computer applications for identification, non-repudiation, personalization and intent for any transactions. Similar to a lot of the current technology, the Nymi band only authenticates at the start, when the band is first worn.
Optical fiber Bragg gratings (FBG) have become ubiquitous in many products such as lasers, filters and sensors. However, typical commercial products are becoming more complex, ones that require highly competent operators since many parameters need to be fine-tuned during the writing of quality FBGs. A previous Mitacs project successfully addressed several challenges in the conception of a FBG writing system based on scanning tunable Phase-Mask Interferometer, marketed by PhotoNova as the BraggTune, using different UV lasers.
Distributed sensing is an advanced technology that enables real-time monitoring of variations along the entire length of a waveguide, and offers the possibility of sensing from a long distance. In the optics domain, distributed sensing based on optical fibers has been successfully demonstrated. However, the realization of distributed sensing in the terahertz domain is still at an embryonal stage.
The discipline of Vibrometery is wide and has many applications, vibrations are present in any mechanical system that involves moving components. So far, the main method to measure these vibrations has been the traditional accelerometer sensor, although it has its limitations and challenges.
Laser Doppler Vibrometers (LDV) were developed in order to address some of these limitations and they offer a non-contact measurement of vibrations by leveraging the Doppler shift effect.
There is a rapidly growing need for voice powered human-machine interaction modalities for varieties of devices. Despite enormous investment in research and development in this area by a number of companies, significant limitations remain which prevent the ubiquitous proliferation of speech recognition. These limitations include poor performance in the presence of noise, inability to handle variability in accents, and not reliably recognizing the speaker.
Measuring customer experiences has historically been based on analyzing traditional structured data, which mainly consists of surveying questions/answers as well as evaluating purchases and returns. However, using this type of inherently constrained data
alone misses the bigger consumer picture. Deeper insights can be derived from unstructured data such as videos of the customers at the store, where tremendous untapped insights exist. In fact, retailers are not just interested in what do customers buy, they also want to know how do customers shop.
Intelligent Transportation System (ITS) enables smart traffic management and provides various innovative services including better safety, more road information, etc., which has drawn a lot of attention. The development of next-generation ITS services and applications must depend on more accurate positioning information at decimeter to even centimeter-level. Such capabilities are crucial because all of the innovative applications are based on the precise positioning of land vehicles.
Manufacturing is a main component driving the successful economy in a society. In order to remain competitive in the global manufacturing market, product quality control is critical. High quality product not only expands the client base, but also enables just-in-time correction to reduce the cost wasted in defective products. The goal of this project is to develop an intelligent defect detection platform, which can be integrated with the existing production pipeline without major alteration or financial investment.
Manual performance, configuration and fault management of Cloud Data Centers is vulnerable to human intervention and therefore subject to human errors. One way to circumvent this problem is to use automation of the Cloud Data Center operations based on advanced technologies which may include Machine Intelligence.
As it is known in mobile industry applications/systems are being virtualized. Therefore some applications will require to run sometime in a central Data center and also closer to the user in order to meet certain characteristics.