Our project presents an Automated Smart Pet Door designed for pet owners who want to provide their pets with a safe and convenient way to enter and exit the house. The pet door uses a camera system and integration of RFID technology - a dog tag proximity sensor to recognize authorized pets and prevent unwanted access. We have also developed a user-friendly mobile application that allows users to control the pet door and monitor their pets remotely. 

Team Members

Our project predicts profitable source-sink relations for Congestion Revenue Rights (CRR) auctions within the ERCOT Energy market, utilizing machine learning and diverse data sources. The software, developed with Python and Next.js, integrates natural language processing and historical data to assist users in informed CRR bidding decisions, impacting resource entities' strategies and potentially affecting consumer prices and market profitability.

Team Members

Augmented Reality Street View (ARSV) is a mobile application that swiftly provides consumer-focused information about nearby businesses. Utilizing AR technology, the app will overlay visual information panels onto the device's camera screen when aimed at an establishment, offering details, descriptions, and reviews. This approach intends to address the time-consuming nature of existing review apps by delivering immediate information about surrounding establishments, enhancing real-time decision-making for consumers.

Team Members

There can be many difficulties for students to find new organizations to join. The goal of this project is to create a web application to take information from all students at UT and provide custom recommendations to students based on their information entered. We are using a graph based recommendation engine to generate the recommendation for the student. All the information will be fed through the front-end web application.

Team Members

Anthony Do
David Johns
Daniel Lee
Jackson Paull
Chris Zhuang

The LidarVision 3D Scanner is a low-cost 3D scanner that can scan objects and generate point cloud models from them. We utilize two 2D lidars that are constantly streaming in scans of the object on the rotating platform to collect points. The scanner is then able to export a stl file for 3D printing purposes of your scan.

Team Members

Bobby Chiu
Hasif Shaikh
George Koussa
Nicholas Vadlamudi
Daniel Xie

The remote weather station is capable of analyzing weather patterns to predict and alert the user of upcoming allergy spikes. The remote weather station collects weather data through a transmitter with various sensors and sends that data to a receiver. Then a machine-learning algorithm uses the data to predict the allergen forecast for the day and notifies the user through a web app.

Team Members

Zahid Hossain

Ethan Hua

Arlette McClain

Kirsten Randolph

Larry Xue

Alvin Zhang

A big problem among college campuses is organizing recreational sports. Intramural games require costs, sign-up processes, and must be approved by the university. Club sports can be competitive and require a hefty time commitment. Many students resort to pick-up soccer, basketball, and football games, but must play with students of varied abilities, where a game is not guaranteed.

Our project is a Smart Mirror that superimposes output from a monitor onto a mirrors reflection. Using a Raspberry Pi that we connect to the monitor, we display a web application of our own design onto the mirror, which allows the user to interact with various modules that display real-time information(weather, news, etc).

Team Members

Andres Gallardo
Jake Giddens
James Park
Julian Wearden
Luke Young
Minseo Park

A Surface Mount Technology (SMT) component placement system, commonly called a pick-and-place machine, is a robotic machine that is used to place surface mount devices on a Printed Circuit Board (PCB) as per a circuit design. Although there are currently several pick-and-place machines that exist in the market for circuit assembly, all these machines are costly (around $5000 or more), bulky, and only available at the industrial level for professional use.

TuneMeIn, a social media app tailored for music enthusiasts, seamlessly integrates features from popular platforms like Last.fm, Spotify, and Reddit. This innovative app offers a unified experience by combining music tracking, personalized song recommendations, and robust social features. Users enjoy a holistic platform where they can connect with like-minded music lovers, share their favorite tunes, and gain insights into their listening habits.