Fiber-optic based point of care genetic testing device

Point-of-Care DNA tests have grown in importance throughout recent years. Incorporation of devices in patient beside treatment requires fast turn-around times for results as well as economic feasibility. Spartan Bioscience, a local biotechnology company, has developed a technology that can detect abnormalities in a person’s DNA. In an effort to develop next generation technology, Spartan Bioscience has collaborated with several faculties at Carleton to develop a platform that will have improved performance.

Intelligent Tracking Infrastructures Using Wireless Networks with Vision-Audio Monitoring Capabilities

Wireless technologies offer new opportunities in the field of telecommunications and computer networks. Wireless sensor networks are a new technology that has emerged after the great technological progress in the development of smart sensors and powerful processors. The city of Trois-Rivieres is currently in the heart of a project to develop a smart public lighting system subject to motion detection. The system will be equipped with vision-audio capabilities for public safety.

Cloud based hybrid low-cost appliance control and monitoring system

The proposed research project “Cloud based hybrid low-cost appliance control and monitor system” is an appliance automation system consisting of an arrangement of different channels of communication. The main idea behind the proposed work is to provide a real time control and monitoring for industrial appliances located in workplaces where internet accessibility is not immediate. The focus of this project is to record the important parameters of operation for an electric motor and then provide data driven smart recommendations to help improve the efficiency of an electric motor.

Big Data Research for Open Source Applications

Big data is a collection of data sets so large and complex that it becomes difficult to process using onhand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization. In this internship, we analyze a real-world big data set(s) to make sensible inferences by taking into account a selected range of criteria. A number of methods and algorithms are investigated, evaluated and evolved to advance the development of specialized tools and processes.

Embedded Low Power Signal Processing for Passive Acoustic Monitoring

This project will attempt to explore the solution space around a number of key issues related to passive underwater acoustic monitoring. Namely the mitigation of acoustic flow noise in turbulent environments, digital compression techniques for underwater acoustic data and the implementation of real time signal processing algorithms related to the detection of marine mammals on ultra low power processors.

Terahertz Time Domain System to Characterize Performance of Terahertz Quantum Cascade Laser Sources

In this project, we plan to address the specific application and problem that TeTechS Inc is facing at this stage of its product development of photoconductive antennas, which is using its photoconductive antennas for characterizing performance of quantum cascade lasers (QCL) in time-domain measurement setup by demonstrating the capability of its proprietary terahertz sensor technology to be used by researchers in University to characterize QCL and in industry for building terahertz spectrometers with high signal and bandwidth.

Capacity Planning and Optimization of WiMAX for Smart Grid, Part 2

Smart grid (SG) aims at modernizing the current power grid which can better manage the electricity through the grid and react to the system faults quicker. To realize this goal, many sensors are attached to different points of the power grid infrastructure. These sensors collect data and can be used for controlling, protecting, and monitoring the status of the grid by receiving comands from the utility control center. Hence, a two-way communication infrastructure seen to be required for smart grid realization.

Textile Sensor Development for an EMG muscle activity monitoring system

GestureLogic is building a product that optimizes athletic performance. The product is a wearable sensory network that monitors muscle activity. The goal of this research is to take this inherently complex muscle data that is acquired by the sensory network and translate it to useful biometrics for the consumer with the help of intelligent algorithms. The algorithms will help intuitively visualize important metrics such as strength of muscle contractions, heart rate and fatigue. The benefit to the partner organization is twofold.

Development of a system for the automatic recognition and classification of normal and abnormal cells in human blood samples

Automation of medical diagnosis/detection process is very important in terms of enhancing diagnostic accuracy, increasing throughput, reducing cost, and training new staff. Our current goal is to go from the proof of concept stage (automatic recognition and classification of human blood images) to a complete working optimized prototype and to start testing it in an actual clinical lab environment with help from CLS. The prototype design will take into account user friendliness, high throughput, robustness, integration with existing lab work flow and reasonable cost.

Anti-islanding detection for renewable energy systems in distribution system

Integration of renewable energy systems into grid is an effective solution to the electric energy shortage and environmental pollution. A number of technical challenges may arise with increased grid-connected renewable energy systems. One of the most important issues is how to achieve the islanding protection. Many anti-islanding detection methods have been reported for single renewable energy systems in the last decades. In practice, however, the multi-unit systems are distributed in different feeders. Consequently, all of the existing methods might fail in this case.