Mobile Polarimetric Imaging System
There is still a large need for a compact and cost-effective imaging system that works in low light and other non-ideal lighting environments allowing for object identification. To address this, the team developed a mobile polarimetric camera system that is designed to be mounted on the back of a smartphone which uses cloud storage to do data analysis off-device .Altogether this forms a mobile polarimetric imaging system that is designed for non-ideal light environments.
Team Members:
Abdullrahman Alzahameel, Bandar Almutairi, Giovanni Choi, Khalid Alfaifi, Rajat Arora
Team Members:
Tyler Taveira, Raheeq Khan, Joaquin Armatage
RISC-V CPU on FPGA
Project Description: The goal of this project was to construct a functioning 32-bit CPU that meets RISCV instruction set architecture specifications. All hardware components were built in System Verilog and synthesized on a FPGA device. To demonstrate the CPU, a terminal application was written that allows the user to type commands.
Solar Powered Smart House
This is a brief demonstration of our capstone project for EEE489. In the video you will see Motion, PIR, Temp/Humidity, Button, RFID, Servo, and LCD modules. We will demonstrate how these sensors are integrated together along with how they are powered.
Team Members:
Jose Maria Rivera, Angel Valdes, Rockwell Wright, Nicholas Brabbs, Abdulla Albastaki
Team Members:
Trayson Rubio, Kati Shackelford, Phillip Northway, Steven Terry
The Smoothie Bot
The Smoothie Bot aims to provide a convenient and customizable meal option for people looking to improve their diet. The main goal of our machine is to enable a customer to order a personalized smoothie. The microcontroller will translate the customer's recipe into instructional code that dispenses precise amounts of ingredients into the blender.
Stereoscopic Computer Vision for 3D Quadcopter Control
Team Quadcopter (Team 21) has developed a stereoscopic solution for intuitive 3D quadcopter control. The team has created a novel Python script that tracks and controls a commercially available drone in 3D space. This project combines hardware with software and utilizes OpenCV, an open source computer vision library, as well as a Raspberry Pi and an Arduino.
Team Members:
Albert Camacho, Seungwan Hong, Zhixi Hou, Lisbet Maldonado, Sriram Rangaswami
Team Members:
Amanda Brooks, SiennaRae Walker, Zachary Plarr, Ashley Koss
Improvement Upon the Palo Verde Station Blackout Generators
Team Palo Verde Station researched various alternative energy systems for Palo Verde Generating Station to implement an update/replacement for their existing onsite station blackout generators. The team researched and compared lithium-ion batteries, sodium sulfur batteries, hydrogen fuel cells, microgrids and hydrogen turbines as the potential replacements. The team based its comparison of each option on essential engineering factors such as reliability, cost, siting requirements, and safety to determine the best replacement option.
Hardware Description Language (HDL) Library Project
Team HDL Library's project is an examination of one of DARPA's proposals to lower the cost of IC design—free and open-source hardware IP libraries. By creating a library of at least 50 unique modules, collecting synthesis data for each, and experimenting with multiple HDL coding styles, we have identified safe HDL coding practices and recommended implementations for multiple modules to achieve the best possible performance. Since these results are so dependent upon the module and synthesis tool, libraries that contain this information, such as our own, have the potential to save ASIC and FPGA engineers considerable time and money.
Team Members:
Justin Burris, Kyle Chilton, Ryan Yanero, Marques Noll
Team Members:
Anthony Chambers, Christopher Jett, Derek Nilsen, Donn Watson
Team Mini Arecibo Antenna
Team Mini Arecibo has created a scaled version of the Arecibo Antenna in Puerto Rico. This antenna utilizes a spherical reflector and unique moveable feed system for high gain and reduced cost. Through the use of electromagnetic simulation and computations, 3D design and printing, and stepper motor integration, the team has implemented a low cost, low power, prototype system.
RISC System on a Chip Capable of OS Boot
The goal of this project was to design a RISC-V SoC that is capable of booting the Linux kernel. This was accomplished by designing and implementing hardware on an FPGA. In addition, we used open-source software to perform the OS bringup.
Team Members:
Alex Shearer, Emily Atlee, Sean Keller, William Zinser
Team Members:
Cory Davis, Justin Oglesby, Ryan Rousseau, Brandon Testerman, Ryan Vos
Micro Hydroelectric Power System
Team Cache designed, built, and tested an at-home micro hydroelectric generation system. Our system has the capability of producing enough power to charge your cell phone or other USB powered devices with your standard water supply even with multiple variables in flow rate and pressure.
Alzheimer’s Neurotherapy Using Cycle-Controlled LED’s and Acoustic Signals
The goal of Team Neurotherapy's project was to expand on Dr. Tasi’s work out of MIT in order to create one complete testing apparatus with audio and visual frequency dependent components, to be given to a medical research team in order to run human clinical trials. These trials will determine if audio or audio and visual signals at 40 Hz will reduce the effects of Alzheimer's disease.
Team Members:
Kevin Bui, Kathryn Chamberlin, Jonathan Lam, John Mix III, and Rachel Scheller
Team Members:
Addison Sklar, Maxwell Young, Paul Lee, Tharon Stewart
Autonomous Rubbage Collector
An autonomous rubbage collecting rover. Utilizes OpenCV and TensorFlow for object recognition of cans and bottles.
Machine Learning Automatic Water Shutoff
The Smart Home Leak Detection System monitors home water usage, uses machine learning to identify leaks, notifies the user, and shuts off the water automatically or remotely according to the preferences of the user. Water usage data can been accessed from any device connected to the local network, trends can be identified, and water losses minimized--saving money, resources, and the environment!
Team Members:
Dillon Freund, Faris Jubran, Isaac Sneed, TJ Ethington
Team Members:
Matthew Morton, Trevor Kortman, Ali Alzayer, Chase Allen, Nersa Elya
LightCube
LightCube is a 1U CubeSat when deployed from ISS into LEO can be triggered via a radio transmission from the ground on Earth to trigger a flash visible to the naked eye in the night sky. Version 2 in 2020 implemented a gravity gradient stabilization system and overall updates to the payload circuit design addressing all safety concerns that were brought forth from NASA to the 2019 Version 1 proposal.
LiDAR Data Collection and Processing
The objective of this project was to fuse LiDAR and camera data to produce an annotated visual to be used to develop a method to integrate LiDAR into autonomous vehicles. Collection of LiDAR data and camera footage was completed and the data was fused together to create videos with object detection and LiDAR point overlays. These videos were provided to ASU’s center for Efficient Vehicles and Sustainable Transportation Systems, who will use them to train deep learning models to create automatic annotations on the videos in the future.
Team Members:
Aiyana Harr, Max Martin
Team Members:
Brian Thompson, Aaron Webb, Jean-Pierre Buckner, Kory Chavez
Red light Detecting Camera
Our project was to develop a system that would deter drivers from running red lights. The system will detect traffic signals and driver speed and provide visual and audible warnings if the vehicle is travelling too fast. It will also be portable and compatible with any vehicle. The team has succeeded in developing a prototype that can detect green, yellow, and red lights, vehicle speed, and produce warnings through speakers and an LED display. The prototype runs off the vehicle’s battery and fits on the dashboard.
GPS
Our project about GPS that focus traffic patterns. In addition, it analyze the movement of the vehicles. And how how much each vehicles have been stopped in some areas.
Team Members:
Hamad Alshehab, Hamad Almutairi, Michael Sullivan, Yusuf Adeshina
Team Members:
Jack Orchard, Jacob Smith, Leo Hsu, Charlesmagne Reyes, Peter Lam
Project Wrist Wake
Team Wrist Device has created a small wrist device to prevent the user from entering the first stage of NREM sleep. This device uses heart rate and gyroscopic data to calculate and determine if the user is beginning to enter the first stage of NREM sleep to then deploy physical and audible stimulus to wake the user.
Smart Dripper
Team Smart Dripper has developed a new variation of the drip irrigation system. This device is compatible with existing sprinkler systems and has the ability to control the watering frequency and duration of each individual plant, eliminating the need to dip up and readjust emitters when changing plant locations.
Team Members:
Laura Bingelyte, Matthew Whiddon, John Bale, Brian Nielsen
Team Members:
Cristian Vazquez, Jack Le, Javier Mancilla, Sungjoon Toyoda, Saeed Alyammahi
Electric Vehicle Origin-Destination Travel Patterns
The effectiveness of determining the most efficient route possible should be considered by the AV and EV industry. To solve this problem, the team has worked on optimizing the travel behaviors of AEVs by programming the vehicle to reach its destination in the most efficient route possible on those bases.
Cloneable Photogrammetry Booth
The Cloneable team has created a low cost photogrammetry booth for constructing 3D models of people and objects. This booth has seven cameras and rotates around the subject taking over 100 pictures. These pictures are then used to create a geometrically accurate representation of the subject.
Team Members:
Nicholas Wallick, Jonathan Woolbright, Emma Ryan, Santiago Tarango, Brandon Cook
Team Members:
Ted Beagle, Garrett Warren, Jordan Kahl, Alan Wirkus-Camacho
Direction Finding Using Machine Learning
The objective of this project was to optimize a machine learning model that can be used to determine the direction from a transmitter to a receiver. This objective was met by using a stationary WiFi router and a software defined radio to collect data and design a direction finding algorithm. This algorithm was utilized to predict the distance between the two devices which can then be used to determine the direction of the signal.
Traffic Analysis Using Computer Vision
This project explores using computer vision to analyze traffic camera footage and extract valuable statistics. More specifically, counting total and current vehicles, while making note of vehicle class, within regions of interest. Being able to quantify traffic flow and identify areas of heavy traffic, can provide insight to the department of transportation to make roads safer and more efficient. Join us, Gabe Portillo, Fabrizzio Escobar, and Michael Chacon as we demonstrate how this technology can be applied.
Team Members:
Gabe Portillo, Fabrizzio Escobar, Michael Chacon
Team Members:
Jeffrey Egbe, Daniel Estrada, Cody Fugate, Robert Tye Scott
LiquiSnitch
Team Water Sentinel created a self-contained water monitoring system which switches water filters automatically. The on-onboard micro-controller manipulates signals received from various peripheral sensors which are measuring water pressure, the turbidity of water, and water flow. Data is stored for analysis and the user is sent real time notifications as the micro-controller makes logical decisions to switch from one water filter to another by controlling a motorized water valve which is immediately connected to a relay to provide enough amperage.
Wildfire Sensor Array
The Wildfire Sensor Array team has designed proof of concept of a sensor array that is to be mounted on transmission line structures. The sensor array consists of various gas, particle, temperature, and wind sensors. Dependent on the outputs of the sensors, an alarm displays if a fire is detected.
Team Members:
Adam Cooper, Blake Tetlow, Clifton Waters, Josh Hammer, Mustafa Alalusi
Team Members:
Michael Buchholz, Kebba Kanuteh, Anthony Livernois, Thomas Long
Ultra-Low, Size Weight and Power Event Detection Device
The Ultra-Low Size, Weight and Power Event Detection Device (UL-SWAPEDD) measures the current, voltage, and frequency in power transmission lines within a microgrid. The UL-SWAPEDD takes measurements through an un-intrusive D-Dot and Hall effect sensor array, implements a team developed algorithm in an FPGA to detect anomalies, and transmits user defined events via Bluetooth to the end user. The device was manufactured with a team designed PCB and ultra-low power commercial-off-the-shelf components to reach the customer’s requirement for power consumption less than 10 mW.
Automated Pet Waste Removal Robot
Team Sküp has developed an automated pet waste removal system utilizing GPS navigation, artificial intelligence object recognition and an original robot design.
Team Members:
Christopher Dudley, Jacob Merten, Brian Lockard
Team Members:
Kin Tung Cheung, Anthony Donaldson, Richard Cheng, Richard Rigby, Richard Gerbino
MakeBlock Smart Robot
The development of Computer vision and robotics have grown rapidly and they have brought a lot of benefits to the world. Therefore, the team worked closely with Dr. Olin Hartin to create a vision-enabled robot. The robot is programed to search for it's surroundings and pick up an object automatically.
Solar Smart Home
Solar Smart Home was created to utilize renewable energy in the most efficient way to benefit both the homeowners and the environment. A solar-powered smart home management system will be designed and built to achieve the idea of an energy-efficient smart home where appliances can be monitored, and power can be derived from a sustainable resource and stored for later use.
Team Members:
Tuyen Nguyen | Alex Bo | Faisal Al-Jabari | Brandon Carrico | Britton Jones