This project consisted of designing and improving the efficiency of 3-phase inverter and filter at extreme high temperatures. The temperature range was up to 25-1500 C. A simulation was generated for the inverter using PSIM software. A DC input of 24[V] was used as a source and a 3-phase motor was used as a load. The design plan consisted of using a DC source followed by a filter, which was needed to filter out harmonics. The filter was tested on a hot-plate with temperature ranging from 25-150°C. The filter was then connected to a microcontroller which controlled the inverter switches. A 3-phase motor was used as a load.
Smart Shoe I
For our senior design project, we are creating a shoe that performs gait analysis at the feet of a patient and provides critical data for physical therapists. We apply our knowledge in electrical engineering to help geriatric patients in physical therapy. We have contacted Physical Therapists and electronics professionals that we believe can better assist us moving in the right direction. With this project we expect to develop a cheaper solution to gait analysis that can be used in the health care community.
The PhysioShoe will be a cost effective, portable, and easy to use gait analysis system that offers realtime data capturing. This tool will be mainly used by physical therapists to help their patients get rehabilitated. We will be analyzing the basic parameters of the foot used in gait analysis such as pressure contour, step length, and foot angle. Our team is a group of experienced individuals who are highly motivated to create PhysioShoe to help the people of our community.
Larva Sonic Boat
The purpose of this study is to create an autonomous boat that can navigate bodies of water and exterminate mosquito larvae using acoustic larvicide. New Mountain InnovationsTM developed a Larvasonic© transducer that kills mosquito larvae by generating sound waves ranging between 18 - 30 kHz, the resonant frequency range for mosquito larvae, that rupture their dorsal tracheal trunks. This results in either instant death, or deformations after hatching. The Larvasonic device is mounted beneath a boat, equipped with two one-directional motors, to create a user-friendly method of controlling the boat and exterminating larvae.
The boat is able to localize itself within the boundaries of a generated map, avoid obstacles, and follow a path using sensors such as Lidar and GPS. The sensor data is processed using ROS (Robotics Operating Software), passed into a ground control software to define a set of GPS waypoints for the boat to follow, and sent to a Pixhawk 2 flight controller to steer the boat. The boat can also be operated via remote control and switched into autonomous mode once the user has approached the intended path.
IEEE Robotics Competition I
We will be building and programming a robot that is capable of scoring highly in this year’s IEEE Robotics Competition gameplay. The strategy that we will be using is a small quick robot that will deliver tokens one at a time. We will implement a line following algorithm to navigate the game board autonomously during rounds. This project is important because it will have lasting effects on the University of Houston in the form of higher prestige for placing among the top three winners. We as a team possess the skill set needed for this project.
IEEE Robotics Competition II
By competing in the IEEE R5 robotics competition, our team was granted the opportunity to represent the University of Houston as a top tier school. The competition required our team to design a robot to face challenges in navigation, mobility, and dexterity with a high level of success. Our team’s 3d-printed robot featured a storage carousel and computer vision algorithms to face the challenges at hand.
Beyond achieving 6th place (out of 35 teams), our robot became the center of attention at the competition, being the only robot to compete using computer vision. Additionally, our successful carousel design commanded the attention of the spectators and established a renowned for the aptitude of students from the Cullen College of Engineering.
EEG Monitoring Headset for Post-Concussion and TBI Related Events Prevention
The prevalent role that electroencephalography (EEG) plays in characterizing, diagnosing, and studying neurological disorders is consistent by the medical and academic communities alike, owing to its accurate real-time monitoring of brain activity and relative low-cost. Other industries have leveraged the Internet of Things (IOT) technology to meet growing demands by which a lateral distribution of smart devices/sensors are enabled to report more data to an end-user than previously possible. This project employs a combination of these two ideas to obtain a telemetric medicine model in which a custom-built “smart headset” detects the wearer’s EEG signal and wirelessly uploads the data to central repository. This system’s Arduino-powered gateway enables the use of remote EEG monitoring. The simple design of the headset does not require the need of a trained technician or neurologist to apply gel electrodes, and the wireless technology allows data to transmitted if the gateway is connected to an internet network.
Smart Shoe II
Project Stride aims to provide a means for caretakers to have peace of mind while offering users freedom in the form of a location reporting shoe that is completely sustained on the excess kinetic energy a human generates by walking. Our smart shoe is an innovative solution to an ongoing problem of people going missing and the costs involved in finding them. A person suffering from memory loss or a child gone missing can induce stress on to loved ones who are working their hardest to find these individuals.
Our device functions by using the voltage generating properties of piezoceramics and converting this energy to usable energy to the low powered electronic components placed inside our shoe. The microcontroller would record and transmit GPS locations with the user’s mobile phone through an android application and Bluetooth. This device will obtain the GPS values and allows users to view the route on Google maps using an android application. The shoe contains every module needed for location tracking, data transmission, and energy generation and storage.
The objective and purpose of this project is directed towards increasing the success and longevity of the Mars Rover on future NASA Missions to Mars. The intent of this objective is to build a Rover with greater mechanical functionality and adaptability to the challenges of operating in the Mars environment. The primary areas of development focus are with respect to LiDAR sensor data acquisition, modular chassis reorientation, and independent motor control.
The LiDAR-based Obstacle Detection System implements a modified LiDAR sensor to conduct 3-D mapping and coverage in the airless environment of Mars. The function of this sub-system is to retrieve and interpolate sensor values in order to successfully maneuver the rover within its immediate surroundings and to circumvent obstacles on its path. This sensor has been physically modified to acquire data in the 3-D plane. We have accomplished data acquisition through a Raspberry Pi 3 in conjunction with appropriate LiDAR Sensor ROS packages.
This realized model employs a reorientation mechanism by utilizing motors at the axles to better maneuver over elevated obstacles, and benefits from a greater degree of articulation over irregular surfaces. These auxiliary motors are attached at three terminating points on the chassis to appropriately reconfigure the Mars Rover in a rollover situation. The Rover can currently communicate through a phone application by employing a Bluetooth module to remotely accomplish forward or reverse motion.
Deep Space Multi-CubeSat Telecommunication
With NASA’s focus on Mars exploration, there have been concerns about the use of Cube Satellite, or CubeSat, technology. CubeSats are an inexpensive, lightweight, and powerful technology; however, they have never been used in deep space telecommunication and have a limited lifespan. Both, are problems hindering NASA’s mission to further explore Mars using the CubeSat technology.
Our team is determined to improve the performance of the CubeSat’s current systems by implementing a redundancy system that allows the satellite to power back on without external efforts as well as creating an inexpensive & self-sustaining telecommunication system to communicate from Mars (deep space) to Earth Mission Control. For the purposes of this project, a self-sustaining system will be defined as a system capable of identifying its power needs and running protocols to attain a minimum three-year lifespan. This telecommunication system will be modeled using three CubeSat systems: Alpha-Master, Beta-Master, and Beta, as well as one additional telecommunication system to function as mission control.
Due to constraints, our product will be a small-scale prototype meant to provide a foundation for future CubeSat applications. The prototype will provide system power and telecommunication standards and applications that can be translated to a full-scale product.
In the NASA Swarmathon competition, a group of robots, called Swarmies, searches for and collects April tagged cubes in a set space. The project started with NASA’s base code to program the Swarmies and identified many methods that would allow them to gain an informational advantage. This project implemented the sharing of information so that data collected from other Swarmies can be utilized. The pickup rate of the April tag cubes was also improved by modifying the base code from the problems encountered by adding a pause clock cycle. Finally, a breadth-first search algorithm is used in order to advance through the arena so that any empty area would not be visited again.
VolleyBoast: Long-Range Personnel and Equipment Tracker
This project is aimed at large industries that require their asset to be transferred from one area to the next in varying conditions. The device will not require users to have extensive technology knowledge other than understanding how to use a computer. At the end of the year, the device is to be able to periodically read data from its sensors and relay information back to headquarters wirelessly over long ranges with low power consumption and an extended up-time of around 1 month. Throughout the project, we’ve used technologies such as modern BUS protocols largely used with arrays of sensors with a main processor and touching on how to design a PCB with commonly used software in the industry while being able to meet deadlines.
Ignition Lock (iLock)
Our project is a thermal camera-based ignition interlock which aims to reduce the likelihood of driving crashes related to drunk driving by preventing a car from starting if the driver is intoxicated. It is based on a study that certain areas of the face show difference in temperature after alcohol consumption. However, our team is unable to further observe its effects. Liability issues limits the use of alcohol in experiments especially in school projects. Therefore, our team’s focus shifted to finding other potential applications for thermal imaging. For instance, observing thermal changes induced by other means such as physical exercise and using the results as a trigger for an ignition interlock. At the end of the semester, our team aims to deliver a thermal camera-based ignition interlock which prevents a car from starting if signs of physical activity are detected from the driver’s face.
FASTR (Face and Speech Transcriber with Recognition)
FASTR is a personal mobile device that performs real-time face and speech recognition to identify and store important information about persons of interest that the user of the device interacts with. FASTR takes pictures and parses speech to create profiles on people that it manages to identify. If the device recognizes somebody who already has a profile, it will output the profile’s information to the user instead of creating a new one.
Transmission Line Drone Reconnaissance
Team 14 is building an image processing software that, when used to process the data collected by a drone fitted with an infrared camera, will do the extensive initial inspection of power lines and output the location of lines that warrant further inspection by linemen.
The program will evaluate the heat signature of the line in the collected images as well as attempting to identify obstructions in the path of the line--outputting the images and location of images that have been flagged for inspection.
The current state of the project has a functioning web app that outputs a Google Drive folder containing the images that warranted human evaluation and a Google Sheet with filename, longitude, and latitude fields. Further work is necessary to properly identify obstructions.