1) Work with UA engineering students on creation of a working prototype of a smart phone application for patients and their family to use in the inpatient hospital setting. 2) There are several “versions” of that app - one that is designed for patients and their families to interface with, a version of the app for physicians to use, and an intranet/desktop version to be utilized by hospital staff to provide the information and data to populate the different versions of the app. 3) The app will focus on identifying the different members of a patients care team such as doctors, nurses, therapists; the app will send alerts to patients so they know roughly when providers will be seeing them; the app will allow patients to store questions; the app will allow patients to store their lists of medications, allergies, list of medical problems 3) The goal is to test the prototype of the app on a floor of the hospital to gauge feedback from patients and determine the ability of the app to improve patient satisfaction scores. 4) Understand HIPPA compliance and how to protect patient information in the setting of a smart phone application will be an important part of this project. 5) Present results of the project at the end of year conference.

Battlebots is a worldwide organization that hosts an elimination style tournament for
robots to battle against each other. Teams implement a balance between mechanical,
electrical, and software Engineering principles to design, build, and test their robots.
Robots must comply with the rules provided by Battlebots, withstand a wide variety of
impacts from competitor weapons, and be able to compete in several rounds during a
competition. Another key aspect in the competition is offensively and defensively preparing
for many different combat styles and various levels of creativity in competitor robots'
movement, shape, and tactics. To validate the safety and capabilities of the robot, extensive
analysis into durability vs. weight will be explored in the design stage and thorough testing
and validation will be performed in a manner to mimic that of the competition field. The
final project goals will be to demonstrate the abilities of the robot, compete in the
BattleBots tournament, and lay the foundation for implementing a combat robotics club at
the University of Arizona.

The system should include all the infrastructure needed to record, display to
the driver and also stream to a computer of the car. The system should be modular so
more sensors can be implemented for future cars. The initial system should include
accelerometers, load cells, and GPS sensors. The data should be presented in a visual
format that would be easy to understand and help the team further develop the car. The
system should interface with a display on the dashboard or steering wheel of the car to
provide useful information to the driver to help improve driver awareness and
performance. The data will additionally be stored on the external computer.

1. System shall use the existing PM steps in SME training to create a virtual training for a single asset at Amazon's FCs
2. The system shall be able to communicate live with other AR/VR glasses simultaneously (group training)
3. The system shall have an AR/VR single asset re-constructed so that technicians can interact and see the job before preforming the job in the FC.
4. The system shall be safe and fall within Amazon's WHS standards
5. The system should be user friendly and require minimal steps to turn on and navigate to the training
6. The system may have a mode in which multiple glasses can interface with each other live.

1. System shall have a self contained energy storage as it travels throughout the facility.
2. System shall be able to identify mechanical anomalies in MHE (Material Handling Systems)
3. System shall be able to identify the location of the anomaly found while system is in use and record the data
4. The system shall have a data base where information is stored and referenced
5. The system should be able to use trend analysis with past data in pre-designated routs to determine if MHE systems are failing
6. The system shall fall within the physical parameters of a 'Tote" at Amazon and should not jam or damage MHE systems as it is in use

The Fourth Industrial Revolution is the idea that efficiency will be revolutionized by mass-data analytics fueling decisions made by AI. Large-area industries, such as agriculture, are racing to design a versatile drone capable of gathering this information. In this effort, ground based, hexapodal platforms have advantages over both flying drones and tracked/wheeled designs. These include the ability to mount heavier and more robust sensor packages, easy modification, longer loitering times, movement below and around foliage, and low impact on soil.

The AMS design uses off-the-shelf electronics, 3D printed parts and open-source software for simplicity, modularity and ease of modification. It includes a Raspberry Pi running the robot operating system, which has an abundant range of packages allowing for the easy integration of additional sensors, missions and parts. This current iteration uses lidar, or Light Detection and Ranging,=4ew31nd supersonic ranging devices, which provide robust obstacle detection and path planning. In addition, a GPS is used to define a roaming area for the robot, so this platform is ready to be adapted to large-area data gathering, especially within the agricultural sector.

Cardiovascular disease (CVD), the leading cause of death globally, results in over 19 million deaths annually, according to the American Heart Association. High blood pressure is directly linked to increased risk for CVD. While an abbreviated daily IMST regimen has been shown to significantly reduce systolic blood pressure, the exercises are difficult to perform effectively using current devices, which offer limited user feedback.

Our respiratory training system, ReTrain, is comprised of an ergonomic, handheld device containing a one-way breathing valve, pressure transducer and ESP32 microcontroller. It senses and transmits the user’s breathing pressure over a Bluetooth Low Energy interface to a paired smartphone application. The accompanying smartphone application monitors breathing pressure and provides live feedback. The device requires minimal user interaction, and the intuitive framework of the app enhances user experience. For standard training and calibration, a real-time waveform of the user’s pressure and current target level are displayed with an accuracy of 3.5%. Additionally, data from each session is stored on the user’s device and transmitted to a clinical program via Amazon Web Service.

The defense industry typically uses software-based applications to test missiles and other types of flying projectiles. But as technology advances, the software requires numerous updates. By introducing a web-based frontend, the development, testing and release cycles of the system will be faster. The design provides the ability for multiple contributors to automate the integration of code and updates for new software.

By using a systems engineering approach, the team created a user-friendly interface prioritizing safety, performance and user satisfaction. A single client-side application receives data from the launch vehicle sensors and engineers, while simultaneously sending data packets back to the sponsor servers on any occasion of user interaction. With a graphical user interface paired with a backend, data forwarding allows the code to be maintainable and put in a single package. This design is a foundation for the transition to web-based applications for the launch vehicles.

Roche’s BenchMark ULTRA staining instrument has a variety of internal conditions, and it controls multiple chemical and physical parameters of the tissue staining process. The residual fluid volume on a microscope slide must be known and controlled. Currently, a technician measures the volume using a Kimwipe and an analytical balance. The team designed an optical approach to measure the volume of residual fluid on the microscope slide with less user interaction than the existing method.

The new system captures side-view images of fluid on a microscope slide and processes the images, measuring the height of the fluid at different points. A Raspberry Pi microcontroller directs the image processing, and a machine learning algorithm is trained to estimate and display the fluid volume onto an LCD screen.

The team designed and manufactured a plastic housing for the camera module that integrates directly onto the slide drawer of the staining instrument. They also manufactured an external housing for the Raspberry Pi and its associated components. Designed for simplicity, this system will greatly reduce the amount of time spent measuring residual fluid volumes.

The BenchMark ULTRA, an automated tissue staining instrument used in the detection of diseases such as cancer, requires several fluid reagents to perform its analyses. Detecting and maintaining adequate bulk reagent levels currently requires technicians to manually log usage, a process which is burdensome, time consuming and subject to error.

The team developed a cart-mounted, contactless vision system to automatically sense reagent fluid levels. The vision system includes a high-quality camera connected to a Raspberry Pi. An LED strip is used in conjunction with induced light blockers on the custom designed cart to stabilize the environmental conditions and improve measurement accuracy. The Raspberry Pi processes the camera image using gamma correction and performs fluid level estimation using pixel intensity comparisons, resulting in detection of fluid levels within 5% of the true volume. The analysis results are displayed on the system graphical user interface and saved for later use. A rechargeable power supply allows for 30 minutes of uninterrupted use.