Category Archives: Conference paper submissions

This is a category for paper submissions for the R1 Annual Student Conference

RFID-based Backscattering for Wearable mIoT Sensors: A Feasibility Study Using a 5.8 GHz Cross-Polarized Patch Antenna, Raymond Jia, Tyler Lizzo, Annie Luo, Charles Lynch, Manos M. Tentzeris

 Title: RFID-based Backscattering for Wearable mIoT Sensors: A Feasibility Study Using a 5.8 GHz Cross-Polarized Patch Antenna

Authors:

Raymond Jia, Tyler Lizzo, Annie Luo, Charles Lynch, Manos M. Tentzeris

University affiliation: Georgia Institute of Technology
Department: Electrical and Computer Engineering

Abstract: 

Developments in the medical Internet of Things (mIoT) field have led to an increase in the need for wearable sensors with small energy and physical footprints. In this paper, RFID backscatter communication is introduced as an alternative wireless communication technique to existing WiFi and Bluetooth systems. RFID backscatter communication is known for its extreme low power consumption and small physical footprint, potentially ideal for long-term wearables. The feasibility of transmitting data via backscatter communication is investigated through analysis of data bit-error rates at varying transmission rates and distances while power consumption is compared to known consumption values of WiFi and Bluetooth to verify the energy advantage of the system.

Submitted by: Raymond Jia
Major: Computer Engineering
Degree being pursued: BS
Type of student: Senior

Mindcontrol, Bingfang (Cornelia) Chen

 Title: Mindcontrol

Authors:

Bingfang (Cornelia) Chen

University affiliation: Cuny-New York City College of Technology
Department: Computer Engineering Technology

Abstract: 

With the development of science and technology, many current research projects are focused on combining the fields of biology and computer technology to change people’s “misfortune” and improve and facilitate their lives. The focus of this research project is to design a controller to control an output device by using brain waves with the goal of creating an assistive technology device for people with physical disabilities.

In the current phase of the research project, background research is done to learn to use the Electroencephalogram (EEG) measurements of brain waves to control an electromechanical device such as a DC motor. A modified Mindflex game controller is connected to Arduino and brain activity data is passed on to Processing code running on a PC in order to track and record brain wave patterns. 

The electrical activity of the brain will be used to control the electrical toy. We try to automatically connect between master Bluetooth and slave Bluetooth without Arduino.

Future work in this research project will focus on using the mind controller as an assistive technology device to help a person with a physical disability carry out some mobility tasks. 

Submitted by: Bingfang (Cornelia) Chen
Major: Computer Engineering and Electrical Engineering Technology
Degree being pursued: BS
Type of student: Senior

Cancer Colony Identification VIA Digital Image Processing, Barry Dunn, Gavin Mantica, Jessica Jensen, Joshua Kruzan, Juliette Caffrey

 Title: Cancer Colony Identification VIA Digital Image Processing

Authors:

Barry Dunn, Gavin Mantica, Jessica Jensen, Joshua Kruzan, Juliette Caffrey

University affiliation: Roger Williams University
Department: School of Engineering, Computing and Construction Management

Abstract: 

In an effort to provide a standardized method of quantification for researchers to develop treatments for lung cancer, which is the most lethal form of cancer, a numerical analysis method was created for preclinical use, in which it will accurately and affordably quantify the presence of cancer colonies on mouse lungs in an automated fashion. Using digital image processing, two different algorithms were developed to examine whole lungs and their cross sections. Once samples of the cancerous samples are obtained and photographed; the algorithm would be utilized. It starts by pixelating the photos and converting them to grayscale, before applying filters and other threshold driven image processing techniques, in order to present quantitative analysis on the presence of cancer colonies. The principal result of this project is to have created a method that has less error and can be completed faster than those that currently exist.

Submitted by: Barry Dunn
Major: Engineering
Degree being pursued: BS
Type of student: Senior

Jin Z, Shao Y, So M: A MultiSensor Data Fusion Approach For Simultaneous Localization And Mapping

Title: A MultiSensor Data Fusion Approach For Simultaneous Localization And Mapping

Authors: Jin Z, Shao Y, So M

University affiliation: The Cooper Union for the Advancement of Science and Art
Department: Electrical Engineering

Abstract: Simultaneous localization and mapping (SLAM) has been an emerging research topic in the fields of robotics, autonomous driving, and unmanned aerial vehicles over the last 30 years. Unfortunately, SLAM research is generally inaccessible for student researchers due to expensive hardware and painful software setup. By introducing a loosely coupled, modular multi-sensor data fusion architecture, we present an autonomous driving research platform that can be adapted to computing platforms with various computational constraints and serve multiple applications and educational purposes. Our goal is to create an easily accessible SLAM module with cost-friendly hardware dependencies and minimal software setup for SLAM researchers, teachers, and learners.

Submitted by: Zhekai Jin
Major: Electrical Engineering
Degree being pursued: BS
Type of student: Senior