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E-Days Projects Spring 2021


Electronic Circuit

Our senior design projects cover a wealth of fascinating engineering and science research. Each project features information about the research, a poster presentation, and a video.





Projects

5G NR

Project ID: 1

Students:

Will Brandt, Marshall Bruner, John Crowell, Foley Stokes
As the global sharing of data continues in an ever-growing trend, the need for technology capable of keeping up and providing faster rates of communication becomes an increasingly pressing matter. 5G is a new generation of mobile network technology capable of providing significantly faster data speeds. As almost all have experienced the often slow data speeds of the current 4g LTE communication system, it is obvious why we need greater data speeds for the countless applications involving mobile data. What separates 5G from the current 4g LTE technology is significant gains in both speed and bandwidth. While there are many technologies encompassed in implementing a 5G system, the most notable of which is the higher frequency of the signal. 5G will implement a millimeter wave which is a much higher frequency wave that presents its own unique challenges. These challenges include a more involved process for mixing baseband signals into and back out of the 1800 MHz n3 band.  
Department:
Electrical and Computer Engineering
Sponsors:
Steve Narcisso, Chuck Duey
Advisors:
V. Chandrasekar

Canine Exoskeleton

Project ID: 2

Students:

Kevin Alamo-Perez, Dominic Castillo, Joanna Dunne, Brooke Landoch, Bradley Rauch, Andrew Reese
Many large canine breeds suffer from degenerative myelopathy (DM). DM is a progressive disease that causes degeneration of the spinal cord and can lead to partial or total paralysis of the hind legs. To date there is no cure for the disease and no surgical intervention methods that can alleviate   symptoms. However, the use of a brace is one method that can help. To overcome the rehabilitation limitations for these canines, an electro-mechanical orthopedic brace system has been developed to assist with the recovery of injured or partially paralyzed   dogs.  The canine   exoskeleton team, in collaboration with the CSU Veterinary Teaching Hospital, has implemented solutions to current rehabilitation methods.  
Department:
Electrical and Computer Engineering
Advisors:
Anura Jayasumana

Control of a Petawatt Laser

Project ID: 3

Students:

Conner Carter, Arsalan Shah, Ryan Wessel
The science of high-power lasers has been a field of interest and has recently seen much growth over the past few years. Plasma generation, X-ray imaging and many other uses take advantage of the growth over the years and as the industry keeps growing, advances in many different fields will continue to blossom. Data acquisition is key and that is the focus of this project.
Department:
Electrical and Computer Engineering
Advisors:
Jorge Rocca

Critical Optical Components for Lasers

Project ID: 4

Students:

Malek Aleshekh, Cole Glaser, Hayden Miltersen, Kevin Novak, Bryan Sullivan
The aim of this project is to design and manufacture a compact, semi-portable, optical testbed to assess laser performance of optical thin film coatings, also known as the laser induced damage threshold (LIDT). The testbed will be integrated with motors to precisely control linear motion of critical optical components that allows automation of the sample testing via graphical user interface (GUI) on a computer. This interface will also record the fluence of the laser, the beam profile, and a magnified image of the test site.
Department:
Electrical and Computer Engineering
Advisors:
Carmen Menoni

CSU ATR

Project ID: 5

Students:

Colin Hice, Jason Kiehlbauch
The CSU Antenna Test Range or 'ATR' is a project that began in 2008 as a multi-disciplinary project which has since been worked on by multiple senior design teams. The ATR is nearing completion, and in its final form will be an automated antenna characterization system that will have both modeling and measurement capabilities for near and far fields from 7-18 GHz. The main instrument utilizes an anechoic chamber inside the Colorado State University Electromagnetics Lab. This system integrates disciplines from electromagnetic waves and radiation, computer science, control systems, power systems, and circuit theory.
Department:
Electrical and Computer Engineering
Advisors:
Branislav Notaros

CSU Brewery

Project ID: 6

Students:

Ian Danas, Teddy Klovstad
This project will focus mainly on the automation of the brewing systems inside of the RamSkeller brewery. There will be a focus on the improvement and continuation of previous years' work as well as work on new systems. The goal of the project for this semester is to automate the Mash Mixer process as well as help fix any physical systems that might be malfunctioning within the brewery. The team will be practicing creating the functional documents necessary to streamline and record how the automation needs to be done so we can then turn these documents into the sequence manager software that the brewery operates on.
Department:
Electrical and Computer Engineering
Sponsors:
Jeff Callaway, Olivera Notaros
Advisors:
Tony Maciejewski

Cybersecurity for Vehicles: Network Anomaly Detection

Project ID: 7

Students:

David Rohrbaugh, Andy Worcester
Unlike many Senior Design projects, the main result of the project is not physical. Rather, it is a machine learning model. Within the depths of Machine Learning, we implemented a Neural Network/Deep Learning algorithm that can accurately detect unusual behavior in the normal flow of information. The normal flow of information is communication between embedded system sensors in  vehicles through the CAN bus. When the flow of information is disrupted, there could be unusual information being detected, a failure in the system, or a direct cyber-attack on the system from the outside. We implemented an algorithm that achieves the performance necessary to be able to reliably detect attacks by finding this unusual behavior. We used Keras with TensorFlow in the Python programming language to implement this. After researching available options for our algorithm, designing an algorithm, and then training and testing against data, we were then able to see if it worked according to a set of standards as a part of the design process. We also researched related aspects of our project, for example, how it would be implemented practically.
Department:
Electrical and Computer Engineering
Advisors:
Sudeep Pasricha

ECE Outreach

Project ID: 8

Students:

Brandon Crisp
The ECE Outreach team strives to introduce students to electrical and computer engineering through educational demonstrations, workshops, and seminars. Of all of the engineering majors, ECE has sometimes been underrepresented, both in terms of incoming freshmen choosing the major, as well as high school students being aware of the major in general. This project strives to change this by introducing students to the exciting world of electrical and computer engineering. Outreach is split up into three sub teams, the Analog, the Digital/Programming, and the Math team. With each sub team focusing on developing exciting demonstrations and lesson plans related to each team. We then use these demonstrations and lesson plans in events and workshops to get students interested in ECE, as well as helping students within the ECE department.
Department:
Electrical and Computer Engineering
Advisors:
Olivera Notaros

ECE Student Projects Lab

Project ID: 9

Students:

Jimmy Craveiro, David Farnsworth, Cole Worth
The ECE B111 Projects lab is a place where students can go to work on their projects or independent studies. The Lab has a variety of resources such as 3D printers, CNC machine, Soldering stations, Hand tools and even a Laser cutter. The ECE senior design lab team is responsible for equipment maintenance and installation, student certification for equipment use, Lab resource management and overall lab improvement. The B111 lab team is dedicated to student safety and available to help or answer questions about the lab.
Department:
Electrical and Computer Engineering
Sponsors:
Olivera Notaros, John Seim
Advisors:
Edwin Chong

Electric Go-kart / Outreach

Project ID: 10

Students:

Sulimn Alturaif, Ashley Andringa, Patrick Donovan, Ian Johnson, Jake Kolb, Deagan Malloy
The Go Kart team is building a fully electrically driven kart from scratch. There are two subteams; ME and ECE. The ME side is crafting the chassis and assisting the ECE subteam in mounting all of the electronics necessary. The ECE side is creating the custom software and wiring all of the electrical components. The final product will used as a teaching tool for several different ECE concepts.
Department:
Electrical and Computer Engineering
Advisors:
Olivera Notaros

Energy Suitcase

Project ID: 11

Students:

Hunter Becvar, Kyle Cunningham, Joshua Ehr, Sean Williams
We live in a world that relies on electricity. Yet there are still so many impoverished and rural areas that don 't have a reliable source of power. Even in the United States, there are places that people struggle for this necessity including the Pine Ridge Reservation in South Dakota. Without access to electricity, extreme weather and emergencies can quickly become life-threatening. Trees, Water, & People, our local non-profit collaborator, is working to provide access to affordable, renewable power sources to this community. They have purchased an educational We Share Solar Suitcase from We Care Solar, which includes two small solar panels and DC charging ports. This is a very valuable device, however, it doesn 't produce enough power to run small appliances. The goal of this project is to create a portable suitcase that provides 150 Amp-hours to charge a laptop (~.05kWhr) , two phone chargers (~.006kWhr a phone), an LED light (~.005 kWhr), and an insulin refrigerator (~.005kWhr) for 24 hours. This suitcase will be powered by four solar panels. This suitcase has the ability to save lives, and make daily tasks a little easier for those without easy access to electricity.
Department:
Electrical and Computer Engineering
Sponsors:
Sebastian Africano, James Calabaza, Valerie Small
Advisors:
Jim Barnes

Exercise Bike

Project ID: 12

Students:

Assad Al Alawi, Jae Young Kim
Our project team has a strong desire to contribute to making a greener future by improving method of reusing of energy. In this project we plan to generate electricity by pedalling a bike and use electrical energy by attaching generator to the bike. Finally, we reuse this electrical energy in various ways for example powering grow box, charging smart phones, and displaying information on the screen.
Department:
Electrical and Computer Engineering
Sponsors:
Kimberly Cox-York
Advisors:
Ryan Kim

Extraction of Magnetic Material Properties

Project ID: 13

Students:

Dominic Molinari, Garrett Ross
The goal of this senior design project is to build a testbed with graphical user interface (GUI) to automate the measurement of effects in sample ferrimagnetic materials in deep saturation over a wide range of frequencies, and to characterize their magnetic characteristics using artificial intelligence algorithms. The impetus of this project is to improve on the IEEE standard, so more so than having application to many industries, it also serves as a possible educational tool.   For deep saturation measurements we will apply utility voltage (120 VCA) through an autotransformer. To test and account for coercivity (conceptually, a materials resistance to magnetization/demagnetization), we will use a grid simulator to set an arbitrary input signal and sweep over a range of frequencies (< 1Hz -50 kHz). We will verify the fitted magnetic characterization functions against high frequency measurements that we will collect using the testbed. Control of the testbed, display of raw and processed measurements, and fitted characteristics will be displayed through our GUI.
Department:
Electrical and Computer Engineering
Advisors:
Jim Cale

GATOR

Project ID: 14

Students:

Sam Escobar, Raul Ramirez
The GATOR Senior Design Project is involved with creating technology that can assist with physical rehabilitation. This year, the team is working on several devices that can fit onto a steering wheel and driver pedals. These devices will send physical information, such as pressure on the steering wheel, to a computer in real time. The hope is to be able to have early detection of Alzheimer's or dementia by detecting patterns from the information gathered by these devices.
Department:
Electrical and Computer Engineering
Sponsors:
Neha Lodha
Advisors:
Sudeep Pasricha

High Average Power Ultrafast Laser

Project ID: 15

Students:

Ryan Brunson, Iliya Risch, Ryan Sullivan
The project goal is to build a high power, ultrafast laser amplifier. This is achieved by focusing a 940 nm wavelength laser emitted from four 7.2 kW laser diode stack assemblies onto a crystal surface with a spot size of 15-25 mm. In order to achieve this goal many different items need to be designed, fabricated, and tested. The laser diode stacks operate at 160V with a max current of 200 Amps.
Department:
Electrical and Computer Engineering
Sponsors:
Jorge Rocca
Advisors:
Mario Maconi

Indoor Navigation Using Smartphones

Project ID: 16

Students:

Colin Jiang, Jack Lueck, Sam Wolyn
Indoor localization is a complicated problem with many possible solutions. Our project attempts to combine two approaches to achieve better accuracy. Dead reckoning is an approach that uses a gyroscope and accelerometer to predict a change in movement. While very useful on a short time scale dead reckoning loses its accuracy as error builds up. Wi-Fi fingerprinting is an approach that uses the existing wireless networks already set up in buildings. It attempts to predict where the user is based on different Wi-Fi signatures in different locations. Wi-Fi fingerprinting is less practical at short time scales due to its high power consumption. We aim to combine these two approaches to minimize their weaknesses and obtain higher indoor localization accuracy.
Department:
Electrical and Computer Engineering
Advisors:
Sudeep Pasricha

Low-Cost DNI Solar Sensor

Project ID: 17

Students:

Javier Acosta, Hashim Akbar, Brian Chan, Zachary Hollingsworth, Tanner Jones
This project is a third-year continuation of the DNI (Direct Normal Irradiance) Solar Integration project.   The project aims to deploy the four solar panels and test their efficiency utilizing the Keysight PA2203 4-channel Series Power Analyzer to measure various aspects of two, industrial grade 3-phase inverters located at the Powerhouse campus.   However, due to COVID-19, we have shifted our project from the Powerhouse to METEC CSU, an energy institute.   Various aspects of the solar array at METEC will be tested under different conditions.   Varying degrees of being blocked/covered, different tilt angles and cardinal orientations are some experiments the team plans to conduct.   Additionally, a Raspberry Pi will be utilized to collect data (voltage, current) periodically from the solar panels using Python.
Department:
Electrical and Computer Engineering
Sponsors:
Ken Christensen, Mike Hawes, Jerry Duggan
Advisors:
Peter Young

Machine Learning for Prediction

Project ID: 18

Students:

Iris He, Rui Tang
This is a project that combines electrical engineering and economics. We will use electrical engineering method to get economic data. We will use machine learning to identify data and use them to automatically make predictions. A large part of the project is to discuss different mathematical methods to build different models and use models to predict future economic data from past economic data. The team needs to implement models by computers programs such as MATLAB for data fitting. The team also needs to compare the accuracy of different models and apply their results to reality and discuss efficiency and feasibility.  
Department:
Electrical and Computer Engineering
Advisors:
Edwin Chong

MRI and Orthopedic Healing Diagnostics

Project ID: 19

Students:

Nathan Eads, Ross Mccaskey, Yipin Sun
Current MRI machines have a maximum field strength of 3 T. New MRI scanners are being designed for higher field strengths, resulting in better image resolution and operating speed. The current design of the internal RF coil will no longer be compatible with a higher field strength. Therefore, the RF coil needs to be redesigned to operate in ultra-high field MRI scanners. The first semester of this project was aimed at rebuilding and optimizing a novel RF coil design. We have replicated an new coil model using the simulation software HFSS, and have performed parametric analyses to optimize the design parameters. The new microstrip model has shown promising improvements in field strength, field uniformity, and inter-element coupling compared to the microstrip model.   In the Spring semester, we switched our interest to an 8 element array instead of 16. The next step will be to finalize an 8 element RF coil design in HFSS with Teflon support parts added onto the conductor strips. Based on the finalized HFSS design, we will physically build a prototype. Eventually the plan is to have a prototype constructed and tested to provide preliminary results of its performance characteristics.  
Department:
Electrical and Computer Engineering
Advisors:
Branislav Notaros

On-Device ML for Smartphones

Project ID: 20

Students:

Collin Peirce, Cole Riechert
Machine learning (ML) has grown in parallel with the "Big Data Age" as a ubiquitous tool in applications ranging from health to finance to scientific research and beyond. Here, we explore the applications of ML in education, motivated by the idea of a homework auto-grader. Handwritten recognition, sometimes called optical character recognition (OCR), has been a longstanding puzzle in ML. While significant advances have been made in numeric recognition, there are still a number of challenges when decoding handwritten alphabet characters, punctuation, and math symbols. As well as choosing an appropriate network model, ML computations also require considerable processing power. Currently, ML has advanced to the stage where such computations are feasible on desktops and even laptops. However, both industry and academia are introducing ML to smaller devices such as embedded systems and smartphones which are limited by their computational power and available energy consumption. In this project, we intend to explore   the challenges of ML applied to an example in education.
Department:
Electrical and Computer Engineering
Advisors:
Ryan Kim

Portable Micro Wind Turbine

Project ID: 21

Students:

Yahya Al Kindi, Mohammad Alajmi, Eric Ellis, Meghan McNulty
The Portable Wind Turbine project is a proof-of-concept for an affordable, convenient, and vehicle-mounted wind turbine for those who wish to reduce their carbon footprint and have a renewable source of power that 's always obtainable. Most RVs use propane to run generators and off-grid appliances which is harmful to the environment. The current market for renewable energy sources for RVs or small camping vehicles is mainly based in solar panels. This project is working to change that by creating a portable wind turbine mounted on the customer 's vehicle and ready to deploy when they are parked.
Department:
Electrical and Computer Engineering
Advisors:
Rockey Luo

Radar Calibration Using Drones

Project ID: 22

Students:

Mateo Lovato, Corby Thompson, John (Jack) Wilson
Radar calibration is important for reading measurements such as the direction, intensity and type (rain, snow, hail etc..) of precipitation accurately. Current methods for calibrating radars include mounting a fixed reflector on a building. Although simple, calibrating in this manner only allows the radar to be calibrated at a fixed elevation and azimuth. In order to provide more extensive calibration, this project is going to use a drone carrying a reflector to calibrate the radar, which will allow the radar to be calibrated in various elevations and azimuths. Having multiple data points for both elevation and azimuth will decrease uncertainty between the measured and actual data, resulting in an improved efficiency. The Radar Calibration Using Drones project will focus on improving the efficiency and cost of calibrating a ground radar.  
Department:
Electrical and Computer Engineering
Advisors:
V. Chandrasekar

Smart Glasses

Project ID: 23

Students:

Ruben Acosta, Zack Sharn
The Smart Glasses Project is about finding a suitable method to improve the quality of life of patients who suffer from macular degeneration. Through sensors and cameras that are equipped on wearable spatial computers, more commonly known as mixed reality goggles, we aim to reframe and allow a patient to see and do more activities without strain. Through glasses such as the Hololens and Magic Leap One, we intend to capture and move video being captured in real-time and move them around a user's field of view, as well as zoom and movement of that image. Accessibility is also important so in order to create a system that can communicate with most mixed reality goggles we aim to design an app to control all features via smartphones or tablets using Bluetooth.    
Department:
Electrical and Computer Engineering
Sponsors:
David Robinson, Chris Atib, Denny Moyer
Advisors:
Sudeep Pasricha

Snowflake Camera System

Project ID: 24

Students:

Lindsay Carver, Giuliana Seretti, Will Vikse
This design project is targeted at improving upon the 3D Snowflake Multi-Angle Sensing System (SMAS), making it the sixth continuation year. If able and taking proper precautions, the system will be implemented at the CSU MASCRAD Snow Field Site and will be used to capture high resolution images of snowflakes, and possibly rain drops during storms. The System will then generate 3D models of the precipitate, calculate fall speed, and categorize the precipitate into six different subspecies to improve computational electromagnetic scattering analysis, all in real time.
Department:
Electrical and Computer Engineering
Advisors:
Branislav Notaros

Telemedicine

Project ID: 25

Students:

Evan Arcand, Tanner Magee, Anfeng Peng
The telemedicine project relates to the approach for monitoring orthopedic fracture healing via direct electromagnetic coupling (DEC). We are developing a telemetric system in which the patient can perform data collection by a DEC system at their home and transmit the data to the health clinic for analyses in order to predict fracture healing outcomes. The device has been created to be portable while still providing the accuracy that is provided by health clinics. This telemedicine approach will allow for daily data collection and analysis in a practical, cost-effective manner, that is patient-friendly.
Department:
Electrical and Computer Engineering
Advisors:
Branislav Notaros

Well Plate

Project ID: 26

Students:

Ryan Barnes, Katie Brown, Najy Faour, Youming Liu, Kailee Mitsuyasu, Aaron Murphy, Ryan Way, Kaitie Wood
The Smart Well Plate project aims to create a well plate that can detect and quantify cell response to pharmaceuticals in real-time. A typical well plate is a rectangular matrix of wells, which are small chambers in which live cells can be placed for testing. New pharmaceuticals are tested in different concentrations within the separate wells, and, after an incubation period, the cell 's response to the drugs is observed. This project focuses on the design and testing of a device that would measure cell response and cellular metabolism in real-time during the incubation period. This is a multifaceted project which involves a team of graduate and undergraduate students of several engineering disciplines. Facets of this project include design and testing of an instrumentation board with power supply and controls, microfluidic electrode design and testing, development of software for a user interface, signal processing of microscopic images, design and testing of mechanical apparatus, and collaboration with several Colorado laboratories involved in cancer research and medical technology. This multidisciplinary approach to the design problem allows for significant collaboration between students studying biomedical, computer, and electrical engineering disciplines.
Department:
Electrical and Computer Engineering
Advisors:
Tom Chen

Wheat Stem Fly Sensor

Project ID: 27

Students:

Carl Cherne, Meg Hansen
The Wheat Stem Sawfly Detection team is working in collaboration with the Agricultural Biology Department at Colorado State University to design a device that will detect wheat stem sawfly larvae in wheat stems.   Wheat stem sawflies are insect pests that lay their eggs inside of wheat stems in Colorado.   The eggs hatch and become larvae that feed inside the stems.   In doing so, they destroy wheat crops across the plains of North America.   The larvae feed inside wheat stems before emerging as adults and spreading to adjacent fields.   There is no known method of detecting sawfly larvae at this time, so our goal this year is to research and test many different hypothetical methods of detecting this pest.   We have been testing three main hypotheses this semester, including testing how light passes through wheat stems, the complex impedances of wheat stems, and attempting to detect vibrations within wheat stems that come from larvae feeding in real time to detect the location of sawfly larvae in stems.
Department:
Electrical and Computer Engineering
Sponsors:
Darren Cockrell
Advisors:
Ali Pezeshki

Wireless Playground Assistant

Project ID: 28

Students:

Alvaro Molina
In today 's era, technology plays a vital component in how we go about our daily lives. However, some people don't have access to such benefits. In this project, we aim to help disabled children navigate through playgrounds safely. This task shall be completed by using wireless devices that will let the user know where the different playground attractions are located through the use of auditory cues.   This way the individual is able to navigate any playground while avoiding any obstacle he might find in the way.  
Department:
Electrical and Computer Engineering
Advisors:
Olivera Notaros

Wireless Signal Characterization

Project ID: 29

Students:

Nick Daly, Huanjia Liu
The Wireless Signal Characterization project seeks to develop a piece of software capable of modeling the signal propagation of electromagnetic radiation through different environments. This software will be capable of calculating the electric field, power, and phase quantities of a signal. These parameters are useful for the design of digital communication systems especially when complex structures in the environment are considered. An example of this would be the use of this software to find the optimum placement of antennas for maximum power transfer in a communication system. This simulation is accomplished by a technique known as the Shooting and Bouncing Rays technique (SBR). Previous teams were able to implement reflected rays and diffracted rays into the code. This year's focus will primarily be on implementing bistatic radar cross section measurement capabilities to the code base.
Department:
Electrical and Computer Engineering
Advisors:
Branislav Notaros