Fourth Year Project
Current Project (2023-2024): Low-power photonics communication for a lunar rover PEEKbot
This capstone project involves the development of a low-powered photonic communication setup to be implemented on a 3D-printed lunar rover called PEEKbot. The students will design hardware components (electronics, photonics, PCB etc), and use software coding for the control circuit.
This project is for students who are interested in photonics and silicon photonics, and optical communication applications. Knowledge of software coding, hardware implementation, basic photonics, and optical communication would be an asset. This project would be appropriate for four to six students.
Previous Project (2021-2022, co-supervised with Prof. Leonard MacEachern): Machine Learning and Artificial Neural Networks for Accelerated Silicon Photonics Design
The goal of this project is to use artificial neural networks (ANNs) to accelerate the design of silicon photonics components. A silicon photonics structure will be parameterized and multiple versions of the structure will be simulated using a commericial finite difference time domain (FDTD) simulator (Lumerical). The performance of the parameterized structure will be evaluated so that for each set of input parameters there is a corresponding set of simulated output parameters. An artificial neural network will be trained using machine learning techniques and the simulated data. The resulting ANN will be used to accelerate the design flow of similar parameterized silicon photonics structures by avoiding many of the FDTD simulations. Part of the project will be to determine the energy savings and increased computational efficiency and speed of the ANN-based design flow compared to the conventional FDTD-based design methodology.
This project is for students who are interested in machine learning applications, photonics and silicon photonics, and neural network applications. Students should have some knowledge of Python (the project will use PyTorch). Knowledge of finite element simulations and Lumerical would be an advantage. This project would be appropriate for four to six students.
Previous Project (2020-2021): Boating Collision Warning and Identification
The Boating Collision Warning and Identification System will
be capable of detecting and identifying a range of different
objects underwater that could pose danger while boating.
Such objects include rocks, logs, and weeds. The system
would be able to distinguish between these objects and
give warning to the boater before the collision occurs. A
combination of hardware, software and AI would be needed
to create these results. Bathymetric LIDAR technology
would be used to give improved imagining results
underwater.
Previous Project (2019-2020): Demonstration of Secure High-Speed Communication using Li-Fi
The project is to showcase real-time internet access through a Li-Fi communication system, by demonstrating a proof of concept product. The objective for the project is to achieve bidirectional communication using LEDs and PDs as the transducers, ideally with multiple users being able to connect to the modem simultaneously.
Previous Project (2018-2019): Li-Fi Wireless Communication System For Image Transfer
Li-Fi stands for Light Fidelity. It is a technology for wireless communication between devices using light to transmit data and position using LEDs (either the visible or the infrared LEDs). Compared to the commonly used Wi-Fi wireless communication technology, the key technical difference is that Wi-Fi uses radio frequency to transmit data. Li-Fi has several advantages such as offering higher bandwidth and higher transmission speeds, and the ability to work in areas susceptible to electromagnetic interference (e.g. aircraft cabins, hospitals) and offering higher transmission speeds. One interesting aspect of Li-Fi is its application in shorter range/distance without any physical barriers, which offers a high level of security from hacking. The team will develop a Li-Fi prototype system that transmits image data (eg, a medical image) and present it to a computer platform. Minimum resolution of the transmitted image will be specified.
Previous Project (2017-2018): LiDAR in Harsh Weather Conditions
LIDAR has been demonstrated for it's powerful capability in generating high resolution maps for autonomous cars and airborne surveying. Due to the nature of the signal, LIDAR encounters particular difficulty in harsh weather conditions that scatter the signal. Autonomous cars are projected to present a large market for LIDAR, and unlike surveying, the atmospheric conditions for operation cannot be selected flexibly.
The aim of this project is to develop a full waveform LIDAR to increase both range and resolution in common harsh weather conditions, such as fog, rain, and snow. This presents a unique opportunity to use LIDAR continuously and reliably. The team will develop a LIDAR alongside novel algorithms for signal processing to extract relevant information and present it to the platform user.
Previous Project (2014-2015): Tricresyl Phosphate (TCP) and CO2 gas sensor
The objective of the project is to design and build a prototype photonic gas sensor for the detection of tricresyl phosphate (TCP) and carbon dioxide (CO2)
for use by commercial and small scale aircraft crew. The wearable device will allow for the monitoring of safe levels of both gases in the cabin air.
The sensor will be equipped with a Bluetooth transceiver to communicate between the sensor and a central alarm system.
Previous Project (2013-2014): Solar Powered Autonomous Blind System
The objective of this project is to construct an autonomous, off-the-grid blind system that is powered using
solar cells. Like traditional blinds, this system would reduce sunlight within a windowed space. This fully
automated and self-sustaining system would have the ability to be configured to desired user specifications.
Ideally, the blinds would be of a modular design, maintenance free and easy to install.
Previous Project (2012-2013): Multi-touch screen technology
A multi-touch screen is a display which can detect the presence and location of a touch or contact to a display
area by a finger or fingers. This technology was first demonstrated in the early 1980s, and has been becoming
commercially available. The main types of such technology include: resistive, capacitive, optical, dispersive
signal, and frustrated internal refraction (FTIR). This project will explore the touchscreen technology based on light-matter
interaction, and the student team will built a functioning multi-touch screen.
Previous Project (2011-2012): Silicon-based solar cells:
This project involves the design, fabrication and testing of silicon based solar cells. Students will
