The new TCU and UNTHSC School of Medicine is taking a progressive approach to curriculum for their students. The standard for medical clerkships, is for a medical student to focus on a practice, then move on to the next practice. This leaves a gap of time between learning and implementing a medical practice in the real world. The Longitudinal Integrated Clerkship (LIC) will engage students in a variety of medical practices in 2 week cycles, so students will constantly be maintaining their grasp on import skills and practices. It is our job to provide the scheduling application that will best match each student and doctor, at the best times.

Sheepdog Defense Group is a local Fort Worth self-defense company that is fully licensed by the State of Texas Private Securities Bureau to provide self-defense and weapons training to help other protect their communities. Their main goal is to provide training to church groups and private schools to help them from becoming targets for acts of violence. Sheepdog Defense Group also offers this self-defense and weapons training to the public so that they can protects them selves and their families. Sheepdog Defense Group is looking for a new website that will allow customers to sign-up for classes using an interactive calendar and access an online store to purchase Sheepdog merchandise. The site will allow the Sheepdog Guards to access all of the important information needed to protect their community as well as access their own information. The site will also allow the owner to manage a wide range of services regarding the business which he is currently doing all by hand.

As part of one of the engineering capstone projects, a calibration testing system was improved with the aid of computer vision. Computer vision was integrated into this project as a solution to a rotating pedestal calibration test that was previously performed by the naked eye. The main goal of this system was to detect and track a red 635 nm wavelength laser spot with offsets as small as 0.025 inches on a 10 x 10 inch grid accurately and precisely. Designing this system involved three major criteria: camera selection, data processing hardware, and algorithm performance.
The first criteria studied in the design process was the camera. The system required a camera that was compact in size, covered the entirety of the grid at less than 11 inches, and captured high quality images. Furthermore, two main data processing hardwares were explored: Raspberry Pi and a standard test laptop. The processing hardware criteria considered were speed, portability, and maintenance. Finally, RGB and houghcircles were the two algorithms used to detect the red laser dot. Testing was conducted to compare the algorithms based on their ability to detect the laser spot, precision in tracking, and repeatability. These design considerations guided the down selects for the final components used in this system.

The LabVIEW team for the Applied Avionics Inc. project focuses on fully integrating the programming of all electrical components with LabVIEW. The major requirements for this project include utilizing LabVIEW to display and capture data feedback, completely automate the testing process, and to read and send data directly to AAI’s database. By creating an actuation and extraction feedback machine that is fully LabVIEW controlled, a variety of switch body types were able to be accommodated and tested. The machine has been shown to decrease variability of results and improve the efficiency of AAI’s current process in all aspects required.

Cloud based services such as IBM Cloud and Amazon Web Services provides a new platform for data collection, storage and processing through the internet that enables environment monitoring via wireless sensor networks. In this project, we would like to develop a cloud-based low power monitoring and notification platform using AWS. Most existing notification platforms are provided as an expensive, closed system that do not allow flexibility and is often difficult to troubleshoot. These systems require special hardware (such as unique walkie-talkies) and upgrades are pushed back due to costs.
Our system will utilize AWS Lambda functions, a cloud database, and IOT buttons so that medical staff can receive and store real time patient vitals and notifications with a data forwarding device such as a smart phone, tablet, or computer. AWS solutions are low-cost and flexible, allowing the care centers to customize the functionality to their specific needs. These buttons do not require wired power supply and have a long-lasting battery.