The hands-on learning and resources made available to engineering students at UC, Berkeley through the use of the MicroKit have resulted in some incredible projects. Here are just a select few examples from engineering students of previous semesters that demonstrate their outstanding work.
Fall 2020
ME 100 – Active Race Car Aerodynamics
ME 100 – Impact-Detecting Football Helmet
The idea behind our project is to collect data about the impact that football helmets sustain during gameplay to help predict and prevent concussions and brain damage. The MicroKit completely enabled us to develop our project idea, from its conception to the final prototype. We were inspired by the MicroKit’s broad functionality in our ME 100 labs. These labs taught us how to turn on LED’s, measure acceleration and rotational velocity, and send data over the Internet. While we chose to pursue a project that is meaningful to us, the capabilities provided by the MicroKit are powerful and dynamic enough to support projects in virtually any area of interest.
ME 100 – Food Use-By Date Tracker
Longevity is a fully integrated IoT application that reminds you of when your food is about to spoil using an Adafruit OLED Feather Wing, ESP32, and MQTT Communication Protocol. Longevity is convenient, extremely economical, and can be implemented in any home with ease. The user transmits the food data from their phone to the device. Once Longevity receives the information, it projects a received message onto the OLED screen and stores the information internally. After this data is received, there are three options. Option one will show the expiration range for the data that was sent to adafruit.io. Option two will list what kind of data we can store. Option three will display a reference list to the abbreviations that we’ve placed.
ME 100 – Elder Care Tracker
Accidents involving the elderly happen everyday around us. As a result, elderly are increasingly at risk, especially if their loved ones aren’t made aware. Our major stakeholders/users are families that are unable to care for their elderly on a daily basis. We used an ESP32 and an MPU9250 IMU to build a prototype that attempts to solve this problem. The Blynk Server(App) allows us to interface with smartphones, which we used to map the GPS data sequentially onto the Adafruit.io dashboard. When a fall occurs, it triggers the MPU9250 and sends a falling detection message to the Adafruit.io feed. Then IFTTT is used to send a warning email that a fall was detected.
