Fall 2018
1: EZ MEDS
The EZ MEDS device is manufactured to distribute liquid medicine with varying degrees of viscosities at precise amounts to automate the current overburden medical industry. By including a key feature that will notify the end-user of correct dosage time to administer their required medicine, it will reduce preparation time and minimize human error. The team’s objective is aimed towards designing and manufacturing a liquid medicine dispenser that will aid the understaffed and overworked nurses in nursing homes, hostels, and hospitals. Following the trends, EZ MEDS will implement an LCD touch screen to promote user-friendly applications, as well as microcontrollers to send and receive signals to pump up to four different types of medicines.
The EZ MEDS team consists of five team members divided into a software and hardware team. The software team consists of members Tu Huynh and Nhu Pham, and is responsible for developing the user-interface (UI), and controlling pump and motor functions. Dolly Lam, Tommy Au, and Cade Odom make up the hardware team, and are responsible for design, testing, documenting and manufacturing the physical hardware mount, three separate platforms, and the outer casing of the prototype. The team’s faculty advisor is Dr. Zhu, who assisted in the hardware development and manufacturing of EZ MEDS. The University of Houston’s College of Technology sponsored our project by providing each group with funds of two-hundred and fifty dollars each. The project advisor is Dr. Moges, who will be providing guidance and connections if needed.
2: Zippy Bot
The project idea proposed is a line tracking robot that would be able to restock items within a patient room inside hospitals or clinics. According to the National Center for Biotechnology Information, nurses are understaffed and there are about 6.9 patients per RN (registered nurse) on shift. The purpose of the robot would minimize the amount of time a nurse uses to gather materials and have nurses put more focus on patient interactions. The team is building a line tracking robot using microcontroller raspberry pi along with python coding language. The robot will be using two passive infrared modules to track the color of the line to follow a path when restocking materials. Additional features will include two ultrasonic sensors that will detect movement and will stop momentarily before continuing on the path. The purpose of the robot is to carry materials within a platform that will be dispensed into the patient’s room to restock materials within hospitals.
3: Substrate Made Simple
We decided to pursue this project because we believe there is a better, more sustainable way to feed the hungry around the world. Our solution would allow people in countries that lack fertile land to easily prepare the substrate, (a nutrient-rich mixture usually comprised of grains), automatically and efficiently with consistent quality for use in food or drink preparation. When the substrate is spawned with mushroom spores, it is used as nourishment for the mushroom. Our objective is to create a control system for the production of a consistent substrate that will be used to cultivate mushrooms. This will be done by monitoring and adjusting variables such as temperature control, pH balance, and rotation control.
Bioreactor technologies already exist in much larger scales with a corresponding increase in price, approaching $15,000 on the used market without control systems being incorporated into these systems. This high upfront cost prevents hobbyists and small scale farmers from gaining access to the benefits of large scale bioreactors. Manual substrate preparation is the most basic method for creating substrate, but both methods offer extremely low efficiency, often yielding very little viable substrate despite the effort required to produce it. By developing a self-contained system, we will be able to set up guidelines to build our system, which will allow for the mass production of our product. By giving researchers, farmers, brewers, and hobbyists access to an efficient and less costly way to produce substrate, we will essentially be accessing the root of several untapped markets.
4: SLIC Biolock
SLIC Biolock is designed to be the economical choice for low to middle-income families and small businesses to have a secured home system. The design is a fingerprint-based security system for doors, which provides the user a secured, quick, and easy method to access their home or office without the use of an actual key. Since the intent is to utilize a user’s fingerprints as the foundation of accessibility, this design eliminates the hindrance of carrying, forgetting or losing the physical key. The project objective also highlights security, efficiency, and feasibility aspects. The security feature of the design depends on the uniqueness of physical characteristics to verify and identify the person with accessibility to the property. Along with that, Biolock provides the user with efficiency by automatically relock the door after a short period of time. An Android application is included as a complementary aspect to improve feasibility by giving the user lock and unlock control through Bluetooth connectivity.
The SLIC Biolock team consists of two implementation teams for a total of 4 members. Si Nguyen Le and Isaac Gaona are in charge of the software development, while Cristian Guzman and Logan Morris are responsible for hardware implementation. The course project is being monitored by Dr. Mequanint Moges, an Assistant Chair and Associate Professor of Engineering Technology, and his teaching assistants every week to ensure deadlines and specifications are met. The faculty advisor for the team is Dr. Ricardo Lent, an Associate Professor of Engineering Technology who specialized in software programming and Android development. Dr. Lent provides assistance and guidance for the design, along with discussing weekly progress and any issues encountered.
5: Eldetect
Each year millions of seniors, those 64 and older, experience a fall. Less than half do not inform their doctor of the fall. For seniors, falling once doubles their chances of falling again. Today, many senior citizens chose to live alone, away from assisted living facilities. This poses a health risk to a majority of them as they are no longer as fit as they used to be. When researching current fall detectors on the market, most have a one-time cost average of around $50 and require a monthly subscription of $30-$50. The lower-end models, which run about $20, have only medical alert buttons. Seniors have to push a button for help, which does not automatically alert someone. Our goal is to create a fall detection device that will alert the caregiver automatically in the event the senior has become incapacitated. We plan to provide our device at a very low onetime cost and low monthly subscription fee to help ensure that everyone can afford one for their safety. Our fall detection device will detect a fall via an accelerometer and microcontroller. The data will be transmitted to the cloud via Wi-Fi and monitored to detect when a fall has occurred. When a fall is detected, a notification (email/text message) will be sent to the caregiver informing them of the fall.
With the baby boomer generation approaching their senior years and the state of our economy these days, a need for an affordable fall safety device is needed. And in time, once the data from the devices is collected and aggregated, it should be possible to find out if there are certain locations in which seniors are more susceptible to fall or if there is a certain time of day which is more fall prone.
6: Total Electron Content Analysis
This team’s project is the Total Electron Count (TEC), part of the multiple projects undertaken by the Undergraduate Student Instrumentation Program (USIP II). According to its NASA webpage, the Undergraduate Student Instrumentation Program is an Educational Flight Opportunity (EFO) to solicit U.S. university proposals to develop an Earth or space science payload that will fly on a NASA suborbital vehicle to promote interest and proficiency in STEM Education and to develop careers in the STEM-related fields.
Scattering effects can be seen by the signals sent to satellites within the ionosphere as a result of interactions with geomagnetic storms. To quantify this dispersive effect, scientists’ analyses demonstrate results that have shown the concentration of oscillating electrons is directly proportional to the amount of bias the signal from a point on earth to a GPS satellite witnesses.
This is called the Total Electron Content (TEC) of a specified path, measured in electrons per meters squared (e/m^2 ). This group’s goal is to use the knowledge and experiences from the TEC project and repurpose it for use in the market.
7: Smart Shoe System
It is our intention to create the new and improved in-shoe fitness tracker to aid in lessening the static lives of the ever-growing population of people who live in their chairs and promote a healthy active lifestyle. For our project, we looked into the attempts of in-shoe fitness trackers from major corporate companies, like Nike and Adidas, and how their products did not meet the user’s needs. We found that the basic design was barely functional or accurate, consequently having these products discontinued. Having been made with a simple accelerometer, the steps counted were very inaccurate. On the software side, their app couldn’t tell the user how far they have run even when coupled with the phone’s GPS. We plan on making a similar device that is capable of very accurately telling the user the exact number of steps taken with the use of a strain gauge that will measure the pressure exerted on it to be read as a step, unlike the accelerometer used in previous devices which measures with slight motion. Our device will communicate with mobile devices by either text or email, making it available to all phone models. To Create the Smart Shoe System, we split our team into two team’s software and hardware teams. The teams consist of Cody Nguyen and Daniela Olakpe in the software development, with Anthony Ruiz and Karl Stephens in the construction and design.
For the Smart Shoe System Project, Xiaojing Yuan, an associate professor at the University of Houston in the College of Technology was selected as the faculty advisor. We selected Professor Xiaojing Yuan as the faculty advisor due to the fact she was our previous sensor application professor and we assumed that she was the best choice because one of the main parts of our prototype is the use of sensors. She has offered us helpful insight on what type of strain gauge/ load cell we should implement in our project. Professor Yuan has also mentioned to us about having contacts with members of Nike’s technology department and has told us that she will try to help us get in contact with them to discuss possible sponsorships or the possibility of being our industry advisor. With that being said, we do not currently have any organizations or companies as sponsors for our Smart Shoe System, but we are working to gain sponsorships and other key contacts.