Project Goal: Design and build a rover prototype that can autonomously navigate a wind farm to collect and extract data from wind turbine footage.

Wind farms are often situated in remote locations with turbines spread across a large land area. As the world shifts to renewable energy, demand for autonomous surveyor robots will grow to help monitor and improve efficiency of wind farms.

This rover, based on an electric all-terrain vehicle, includes a gimbal-mounted camera to record wind turbines, weather instrumentation to measure wind speed and direction, a GPS module attached to a Raspberry Pi 4 to generate a rover navigation, and a TFMini Plus LiDAR module for obstacle avoidance. The rover is powered by two 12V 50Ah lithium batteries, a monocrystalline 120-Watt solar panel and a solar charge controller. This equipment was assembled and integrated onto the ATV frame with software that allows the rover to traverse along a navigational way-point path to collect turbine video and weather conditions autonomously.

An external software package was created to process the collected footage to determine the rotational speed of the turbine’s blades. The processed data is used to monitor acceptable turbine performance and improve wind turbine efficiency.

Project Goal: Develop a process that produces continuously variable hardness of material during the 3D printing of a vibration isolator.

Printing plastic with continuously varying hardness has potential applications in the design of vibration isolators. Current designs involve rubber isolators and metal mounts, but the bonding seams between metal and rubber tend to separate after prolonged use, increasing the failure rate of the isolator. A new process makes it possible to create a single-piece vibration isolator that has a lower failure rate than those currently produced. Also, isolators printed with adjustable hardness allow for fine-tuning the isolator to be more effective at specific frequencies.

The printhead of the MakerGear M3-SE 3D was modified to include a three-inlet nozzle with one outlet and supporting hardware that allows simultaneous mixing of high-, medium- and low-hardness filaments. In the custom design, the filaments are fed into the hotend at different rates to vary the mixture, and therefore the hardness, of the extruded material. In the printing process, the user creates a G-code file using slicer software. The file is run through a custom post-processor, and then this code is sent to the printer. The custom G-code contains commands that change printed plastic hardness depending on print-head coordinates throughout the process.

The combination of the modified printer and the custom software enables printing parts with continuously variable plastic hardness.

Project Goal: Develop an easily transportable real-time optical tracking system to investigate suspicious vehicles at domestic critical infrastructure sites.

The Ground-Based Optical Target Tracking, or GOTT, an autonomous image processing tracking system, tracks a full-size vehicle moving approximately 28 kilometers per hour from 50 to 300 meters away. A camera mounted on a motion control tripod closes the loop around the camera image/target tracking algorithms. A pan-tilt motion control assembly, made of 6061 aluminum, is mounted directly to the tripod for image stabilization and target designation. After the image processing algorithms designate a target, a low-power green laser is used to designate the target for the system operator.

The object detection algorithm uses a neural network to locate a user-selected vehicle within the field of view. The target detection algorithm communicates with an optimized target tracking algorithm and sends commands to the pan/tilt assembly to keep the moving target in view. The camera is boresight-aligned and mounted directly under the laser designator. The pan-tilt assembly consists of a pulley and gear system that allows for more precise movements from the stepper motor.

Project Goal: Create a functioning lab mockup of the cryocooler and mounting system currently installed on the spectrograph LUCI instruments of the University of Arizona Large Binocular Telescope Observatory.

The Large Binocular Telescope Observatory, or LBTO, is affected by vibrations from the cryocoolers on the spectrograph LBT Utility Camera in Infrared instruments, or LUCI. A test bed consisting of a working analogue of the cryocooler and the surrounding spring system would help reveal possible improvements that can be made to reduce the vibrations.

The Vibration Mitigation System has several subsystems that imitate the conditions of the actual LUCI design by supporting a cryocooler with a spring holding system and mounting it to an optical breadboard that is connected to an artificial loading system. The current LBTO structure was slightly modified to fit the test device and to compensate for the lack of force caused from the vacuum of the LUCI instruments. The vibration spectrum of the mockup was measured and modified until it was as close to the spectrum of the cryocoolers in the LBTO as possible.

Experiments with this lab mockup can test improvements to the springs and cryocooler to reduce transmitted vibrations to the telescope.

Project Goal: Design gloves that measure and display the amount of mass a user is holding and provide time-under-tension calculations during exercise activities.

The Mass Gauntlet gloves allow users to assess their exercises when the force exerted may not be known, such as in assisted pull ups.

They display the real-time force a user is exerting in metric or English units. The gloves can also calculate and display the time-under-tension for each workout set. Embedded pressure sensors and wireless capabilities integrated into the gloves measure the total force exerted on them. Rechargeable batteries allow the gloves to be repeatedly reused.

Added calibration functions allow for improved accuracy and repeatability. The device has several preprogrammed capabilities that users select as desired.

Project Goal: Create and integrate an automated management system to support a greater production volume.

Ruda-Cardinal Inc. is increasing their mass production of custom optics projects. To handle this growing demand, they wanted to replace their manual system with a new automated process.

The Manufacturing Resource Planning system is primarily cloud-based, logging components of a product with process controls that prevent human error. Users can track serializations, locations and overall status of a product throughout its lifecycle. Scanning and manual functions update the information. An encoded template for each manufactured product creates documents that are curated to record product status, location and other necessary information.

Scanning technology tags inventory and its transportation hardware with unique barcodes. Items are cataloged by barcode or manual entry. A custom SharePoint site stores all relevant inventory and contractual data for each product and allows intercommunication through shared updates regarding product status.

Project Goal: Develop a portable, non-invasive skin-imaging system that captures at least 250 frames per second to observe physiological processes in a time frame varying from a few seconds to one minute.

The market lacks products that can track biomarkers, such as hemoglobin, hemosiderin and bilirubin, over long periods of time. Such a product will assist in biomedical research on skin-level processes and may lend itself to improving patient care if integrated into medical devices for non-invasive imaging of the skin.

The Rapid Optical Imaging of Low Frequency Physiologic Processes observes physiological processes that occur between one second and one minute, using 13 types of LEDs to illuminate tissue with specific wavelengths chosen to target particular biomarkers. A custom electronic design operates the LED array. A heat sink dissipates the heat from the power generated by the electronic system and safely prevents thermal damage. The ROIPP rapidly cycles through the 13 biomarker wavelengths, displays a live video feed and efficiently saves the images onto the user's computer.

With this device, the concentration and movement of multiple biomarkers within the human skin can be recorded simultaneously, allowing researchers to recognize patterns in activity.

Project Goal: Design a system that detects heart, breath and speech through sound, which is analyzed using natural language processing technology to aid doctors in diagnosing patients.

Subtle Sounds is a holistic system that takes in arbitrary sound data and computationally analyzes the signals with a natural language processing, or NLP, interface.

An electronic stethoscope collects heart and breath sound signals, and it transmits data to a computer via Bluetooth. Four large diaphragm cardioid condenser microphones, mounted on individual tripods strategically positioned to surround the patient, capture speech sound signals. Parselmouth, a Python library for Praat software, determines the acoustic properties of input signals, including harmonic-to-noise ratio, jitter, shimmer, short-time energy, energy entropy and zero-crossing rate. The software also creates reports that depict relevant data and tables that are useful for a doctor's diagnosis. The software-generated reports are saved in a small on-board database.

Newly written software compatible with Google's API NLP provides transcription of the patient consultation. The software runs on a PC mounted on a mobile cart. The cart also holds the microphones, mounts, cables and stethoscope when the system is disassembled. A doctor or medical professional can easily transport the system and set it up in five minutes or less.

Project Goal: Develop an image analysis tool to assist in the qualitative analysis of platelets and platelet activation.

Improvements in qualitative analysis of medical images, platelets in particular, are needed to reduce overhead and remove human bias, error and inefficiency.

Fractal Eyes V2.0 serves as a preliminary, neural-network-based platform that classifies platelets in different stages of activation, while it also extracts feature data for further analysis. Developed in Python, the tool captures the area of the platelet, the perimeter, color density differences, light intensity and approximate pixel length and width as it maps the image. A graphical user interface application loads platelet images, view feature data and access log data for image analysis and feature extraction subsystems.

This system will aid the University of Arizona Center for Accelerated Biomedical Innovation's current work on platelets and associated technologies, programs and goals. It serves as foundational work for expansion to other subjects of medical image analysis.

Project Goal: Improve the performance of current low-cost ventilators by designing a mechanical ventilator from readily available materials and implementing an advanced control system to adjust and monitor clinical data.

Healthcare professionals and medical facilities are overrun with an increasing number of COVID-19 patients who needed sophisticated, extremely costly mechanical ventilators. Makeshift, low-cost ventilators designed by engineers around the world did not meet the demand due to expense and the short supply of medical-grade components.

This design mitigates those issues by using everyday household materials, such as a ball for an air reservoir and a rolling toolbox as a mode of portability. An advanced control system monitors air flow and pressure to the patient during the breathing cycle, which can be read on the graphical display. The ventilator also features a two-arm design that operates as the squeezing mechanism to deliver air to the patient. A motor and a set of adjustable clinical parameters control the device.