The University of Texas at Austin Department of Electrical and Computer Engineering (UT ECE) hosted the Spring 2014 Senior Design Open House on Monday, April 21, 2014. UT ECE undergraduate seniors presented demonstrations of their projects spanning two semesters of work.
Winners were announced at the UT ECE Graduation Banquet on Friday, April 25, 2014.
UT ECE is deeply appreciative of our industrial collaborators, whose expertise and support makes these projects successful and meaningful. Industry project sponsors for the Spring 2014 projects include Texas Instruments, Intel, Digiclaim, Cameron, Quorum Business Solutions, National Instruments, and Qualcomm.
Apple, Inc. generously donated Apple products such as MacBook Airs, iPad Minis, and iPod Touch devices as prizes for the top projects presented at the Open House.
Active Camouflaging for Broadband Scattering Reduction
Team Members: Blake De Garza, Eddie Ge, Jerry Lu, Michael Perez, Shireen Solima
Faculty Mentor: Andrea Alù
Apple Prize: MacBook Air
Description: Cloaking is a cutting edge topic in technology today. Many groups are involved, most using meta-materials, a method that misdirects an incoming wave or eliminates its reflection. This group took a different approach, and developed an original method that uses an array of powered antennas to reduce the electromagnetic shadow of an object. They designed, built, and demonstrated a proof-of-principle device accomplishing radio frequency cloaking of an object. It consists of a receiving module of antennas and phase detectors to capture a signal before it hits an object, a microcontroller and phase shifters to manipulate the signal, and a transmitting array of antennas to broadcast the signal on the other side of the object. This project required substantial expertise in electromagnetics, antenna design, embedded systems, and software engineering.
Android App for Creating Stereo Images, Depth Maps, and 3D Models
Team Members: Nilkanth (Neal) Babaria, Tyler Cox, Jordan Naumann, Arit (Tushar) Paul, Vikram Sripadam
Faculty Mentor: Al Bovik
Apple Prize: iPad Mini
Description: This team used an Android system and SDK to create a 3D Stereoscopic Camera App they call Michelangelo. It can take a stereo pair of pictures on the fly, capture and store both images, and then compute 3D depths from the images – right on a phone or tablet. The 3D depth information is then used to create a 3D model of what was photographed. This is done in color, right in the users hands. This team demonstrated highly efficient programming of a very complex project, and also developed a GUI making the system simple to use.
A Medical Device Identifier
Team Members: Bryan Brumm, Andrew Langley, Tyler Mock, Joshua Moore, Lauren Walkowski
Faculty Mentor: Jon Valvano
Apple Prize: iPod Touch
Description: This team developed a novel device capable of reading a patient’s pacemaker, which on a commercial scale could give doctors quick vital information in an emergency. The team mastered a broad set of disciplines, such as how pacemakers communicate, generating and sensing electromagnetic fields, power circuits, and low noise high accuracy sensing electronics. The project uses considerable digital signal processing implemented on a microcontroller.
Maximum Power Point Tracker
Team Members: Thanh Dang, Robert Desjardins, Philippe Dollo, Jordan Penza, Andrea Tosi, Shangheng Wu
Faculty Mentor: Gary Hallock
Industrial Mentor: Eric Dean, National Instruments
Description: This team developed from the ground up a compact power point tracker, optimized for use on a solar car. It makes use of the just released National Instruments myRIO controller, and a custom circuit board containing the power electronics and monitoring circuitry. Their work will replace expensive commercial trackers used in UT’s solar car.
Team Members: Prachi Gupta, Shreya Kumar, Yamit Lavi, Abhas Mishra, Siavash Zangeneh
Faculty Mentor: Bill Bard
Description: This team achieved 3-axis stability of an autonomous airborne vehicle using GPS and a magnetometer. Their plane can accurately fly between waypoints, using algorithms anticipating future fight direction. They also achieved coordinated turns using both aileron and rudder operation.