These projects are at the midpoint of a two-semester sequence. They are not completed.
Prosthetic Hand with Neuromuscular Control (PHNC)
Sponsor: RH Systems
Student Team: Francisco Recio, Scarlett Head, Marco Alcantera,
Faculty Advisor: Dr. Wuxu Peng
This project will take the neuromuscular signals captured by the Myo armband, a gesture and motion control device, and produce a pulse-width modulation signal that can control a prosthetic arm. Our final product will be a robotic arm that acts as a prosthetic hand and has two degrees of motion, which includes the opening and closing of the hand gripper as well as a vertical movement of the arm. The PHNC will create an innovative solution to aid amputees in performing everyday tasks that were unable to be done as efficiently, if at all, and to provide people with hostile work environments with a safe alternative.
Olfactory Delivery System
Student Team: Rob Fernandez, Daniel Shafer, Ivan Juarez
Faculty Advisor: Dr. Larry Larson
The olfactory delivery system (ODS) is designed to dispense various aromatic sensations upon computer commands, including the intensity, threshold value, and blending of aromatic sensations. Nothing will be worn on the users face for the system to operate and the aromatic sensations will not linger for more than a few seconds. This design will be implemented through the use of an Intel Galileo Gen 2 development board for a microcontroller and the ODS will be presented as a proof of concept. There are many applications in which this system could be used such as by the astronauts themselves in space, a virtual reality system, and deodorization as well as others.
Sponsor: Hunt & Hunt Mechanical
Student Team: Yohannes Derso, Jaime Perez, Joshua Sorenson
Faculty Advisor: Dr. William Stapleton
This design project will create a more efficient method for detecting keyway location on perforating guns. Such guns are machined to strict tolerances, necessitating precise alignment of machined parts between process steps. The current detection and alignment methods are inefficient and time-consuming. By successfully demonstrating a more reliable method for locating the keyway, the process of alignment can be improved without replacing existing machinery. This design will use a microcontroller and digital image processing to positively identify the existence and location of a keyway on standard pipe sizes.
NXP Sun Tracker
Student Team: William Burdick, Hyunsook Kim, Eli Bazan, Anthony Lamme
Faculty Advisor: Dr. William Stapleton and Dr. Semih Aslan
The team will develop a prototype Remote Sun Altitude-Azimuth Tracker and demonstrate functionality using NXP development tools. The device will be able to detect the sun in the sky, calculate the altitude angle of the sun (angle from the horizon to the center of the sun) and calculate the azimuth angle (angle from due north to the center of the sun in the sky). The altitude-azimuth angles will be transmitted wirelessly via a local gateway to a cloud server using Thread wireless networking protocol. Data from the sensor will help maximize efficiency of a steerable solar array, by pointing the solar array towards the center of the sun.
Sponsor: Ingram School of Engineering
Student Team: Julie Bellefontaine, Yash Patel, Hector Valdez
Faculty Advisor: Dr. Rich Compeau
The Sensing Meat Analyzing Real Time Thermometer project aspires to increase the quality of the user’s cooking experience by fusing real-time data processing and the connectivity of the Internet of Things (IOT). The data will be observed through a user-friendly Android environment, which will create a new cooking experience through the design and development of a predictive and wireless Android application. The design will be implemented using a thermocouple, microprocessor, and Bluetooth chip to seamlessly allow users to monitor their food with a projected time of completion. This feature will reduce the time the user would originally spend monitoring their meal and allow them complete other tasks around the home, minimizing unknown wait times.
Smart Irrigation System
Student Team: David Talley, Eltayib Bahar, John Carroll, Lynn Vu
Faculty Advisor: Dr. William Stapleton
This project involves the design and prototype construction of a residential irrigation system capable of minimizing water loss from leaks. Using MEMS microphone sensors, the system will monitor the flow of water through irrigation lines to determine if a leak from a broken pipe or sprinkler head is present. When a leak is detected, a controlled valve will shut off water to the irrigation system, preventing further loss. The smart Irrigation System will also notify the homeowner when a leak has been detected so they can begin repairing the damaged component.
Remote Stream Flow Sensor
Student Team: Samuel Cain, Sheyi Adeyemi, Aaron Hunt
Faculty Sponsor: Dr. William Stapleton
The Remote Stream Flow Sensor is a project that will demonstrate the ability to determine the water velocity of a stream and transmit the data wirelessly. This project could potentially be used to alert communities in flood danger zones. The system will measure the flowrate of a particular stream from 0 to 10 feet per second in real time. The team will use a pitot tube – pressure sensor combo to measure the water velocity. The team will also use a NXP development platform process and transmit the data to a local cloud.