UT Tyler Capstone Projects from Tyler and HEC ( 2021- 2022)

EE Capstone Projects for the Academic Year 2021 - 2022

• Project Title: Centralized Autonomous Agricultural Robot

    Team Members:

    Faculty Advisors:

    Campus: HEC

    Description: An automated agricultural system that can be used in greenhouses, gardens, and small-scale farms.

• Project Title: Human counting system using mmWave Radar

     Team Members:

     Faculty Advisors:

     Campus: HEC

     Description: A radar-sensor based human detection and counting system that prioritizes privacy and security.

• Project Title: Underwater Remotely Operated Vehicle (ROV)

     Team Members:

     Faculty Advisors:

     Campus: HEC

     Description: An underwater remotely operated vehicle that can remove trash from the floor, middle, and      surface level of a body of water.
(The project participated in the 2022 IEEE R5 Student Robotics competition)

• Project Title: Smart Industrial Fan Controller

     Team Members:

     Faculty Advisors:

     Campus: HEC

     Description: An IoT-based smart controller for inline industrial fans that can be used in vertical farming.

• Project Title: Vehicle Interchangeable Electronic Controller (VIEC) Network System

     Team Members:

     Faculty Advisors:

     Campus: HEC

     Description: A system that can maximize the functionality of the spacecraft by using a multitasking control system to achieve the long-duration mission goals.
(The project participated in the Texas Space Grant Consortium Design Challenge provided by NASA)

• Project Title: IoT Edge-Intelligent Wearable Sensor Array

   Team Members:   Timothy Bauer, Cody Conder, Lloyd Mcgrath, Martin Morales Alvarez, Sloke Shrestha

    Faculty Advisors: Dr. Premananda Indic and Dr. Prabha Sundaravadivel

    Campus: Tyler

     Description:    Mobile health monitoring is a rapidly evolving science that can shape the future of healthcare. Existing mobile health solutions, however, have underserved the disabled and technologically deficient communities. To better address these communities, edge computing, a new method of allocating processing and storage needs on edge devices, was utilized to mitigate the need for a cloud and phone to process and store data. To achieve simple and low-cost operation, the IoT-Based Edge-Intelligent Wearable Sensor Array makes use two devices: a sensing module and a processing module. What resulted is a low weight wristband and waistband, day-long battery life, and one minute response time for detected stress. This research shows how the physiological condition can be determined in mobile health without the need for a cloud or phone.

 

• Project Title: IoT pH Monitoring ​Leaf Patch

    Team Members: Carlos Galvan, Rudy Montiel, Jared Carter, Karl Lorenz

     Faculty Advisor: Dr. Shawana Tabassum

     Campus: Tyler

     Description: The goal for this project is to design and construct a 3D printed leaf patch that can detect the pH of the plant. The purpose for this device would be to monitor the health of the plant over time. The data collected by the patch is digitized and uploaded over Wi-Fi to an IoT application called Grafana

 

• Project Title: Osteoporosis Health Monitoring e-Textile Sensor
   Team Members: Joshua Butler, En’Tavias Curry, Alexandra Johnson, Alina Pereira, and Favour Thomas

    Faculty Advisors: Dr. Shawana Tabassum and Dr. Mukul Shirvaikar

    Campus: Tyler

    Description: The Osteoporosis health monitoring e-textile sensor serves the purpose of aiding patients affected by Osteoporosis, detecting user’s calcium levels through their sweat and scanning for the possibility of a fall .​ This device uses real-time monitoring of calcium levels in the user’s sweat and notifies the user of abnormal calcium levels through a visual, colored scale . Also, it allows for emergency contacts to be alerted if a fall occurs

• Project Title: The SAVVY Kit
  Team Members: Conrad Fjetland, Nathan McNamara, Devon Wade, Maxwell Ugbebor, and Efrain Tavera​

   Faculty Advisors: Dr. Jonsup Park

   Campus: Tyler

   Description: The SAVVY (Senor Acquisition and Verification/Validation Yield) Kit is a multi-sensor DAQ that is capable of storing sensor data internally and has internal power storage. Sponsored by Trane Technologies Inc., this project was designed to solve the issues with Trane's existing solutions for recording sensor data as the current solution require too much user input and an internet connection to log data in the cloud.