Project

# Title Team Members TA Documents Sponsor
100 Drone-Mounted GPR System
 Anna Sako
Elijah Sutton
James Tang
 Lukas Dumasius design_document1.pdf
final_paper1.pdf
photo1
photo2.png
presentation1.pdf
video
# Title

Team Members:
- Elijah Sutton (esutton3)
- James Tang (jhtang2)
- Anna Sako (sako2)

# Problem

According to the Department of Energy a simple change in habits can effect fuel economy by 10%-40% which translates to $0.38-$1.53/gallon saved! https://www.energy.gov/energysaver/driving-more-efficiently Although many drivers are concerned with fuel efficiency and eco-friendly driving, it is often difficult to understand the specific impact of driving habits on emissions. Especially in older vehicles, actionable driving feedback is limited and counter-intuitive.

# Solution

My idea is a small OBDII compatible module that can be retrofit into nearly any vehicle that collects driving data such as throttle, RPM, and speed. This data then be used to infer other data such as transmission state and braking. Collectively this data can be fed live into a lightweight ML model that classifies different driving styles and mistakes before relaying the data to the driver via a distraction-free LED display (RGB strip). The driver can then use this feedback to adjust their driving habits in an intuitive way and achieve the emissions savings that are possible.

# Solution Components

## Subsystem 1

The first subsystem of the design is a PCB that is powered by and interfaces with the OBDII port in a car. This board would use the 12V chassis power stepped down with a buck. It would also use a CAN transceiver to communicate with the ECM of the car to collect data. The MCU on the board would control all communications enough and host a lightweight ML model.

## Subsystem 2

The second subsystem is a distraction-free intuitive LED display that provides the driver with feedback. It needs to be convenient enough to add to the dash of any car, discrete enough to not be distracting, and intuitive enough to give the driver actionable information. This piece of the device defines the entire user experience and is a potential source of danger if it becomes distracting; it is very important to be designed with lots of thought.

## Subsystem 3

The last subsystem is all software. After the MCU collects the data, it needs to process it in order to inform the display. We will start with a threshold / rule-based algorithm that classifies the drivers habits and provides feedback. This will then be developed into a lightweight ML model where improvements can be made.

# Criterion For Success

In order to be effective, this project will collect driving data via OBDII port, control the LED display, and be a self contained power system. At the highest level, this project will be deemed successful if we can improve the vehicles reported fuel-economy for a given trip based on feedback from the device.

GYMplement

Srinija Kakumanu, Justin Naal, Danny Rymut

Featured Project

**Problem:** When working out at home, without a trainer, it’s hard to maintain good form. Working out without good form over time can lead to injury and strain.

**Solution:** A mat to use during at-home workouts that will give feedback on your form while you're performing a variety of bodyweight exercises (multiple pushup variations, squats, lunges,) by analyzing pressure distributions and placement.

**Solution Components:**

**Subsystem 1: Mat**

- This will be built using Velostat.

- The mat will receive pressure inputs from the user.

- Velostat is able to measure pressure because it is a piezoresistive material and the more it is compressed the lower the resistance becomes. By tracking pressure distribution it will be able to analyze certain aspects of the form and provide feedback.

- Additionally, it can assist in tracking reps for certain exercises.

- The mat would also use an ultrasonic range sensor. This would be used to track reps for exercises, such as pushups and squats, where the pressure placement on the mat may not change making it difficult for the pressure sensors to track.

- The mat will not be big enough to put both feet and hands on it. Instead when you are doing pushups you would just be putting your hands on it

**Subsystem 2: Power**

- Use a portable battery back to power the mat and data transmitter subsystems.

**Subsystem 3: Data transmitter**

- Information collected from the pressure sensors in the mat will be sent to the mobile app via Bluetooth. The data will be sent to the user’s phone so that we can help the user see if the exercise is being performed safely and correctly.

**Subsystem 4: Mobile App**

- When the user first gets the mat they will be asked to perform all the supported exercises and put it their height and weight in order to calibrate the mat.

- This is where the user would build their circuit of exercises and see feedback on their performance.

- How pressure will indicate good/bad form: in the case of squats, there would be two nonzero pressure readings and if the readings are not identical then we know the user is putting too much weight on one side. This indicates bad form. We will use similar comparisons for other moves

- The most important functions of this subsystem are to store the calibration data, give the user the ability to look at their performances, build out exercise circuits and set/get reminders to work out

**Criterion for Success**

- User Interface is clear and easy to use.

- Be able to accurately and consistently track the repetitions of each exercise.

- Sensors provide data that is detailed/accurate enough to create beneficial feedback for the user

**Challenges**

- Designing a circuit using velostat will be challenging because there are limited resources available that provide instruction on how to use it.

- We must also design a custom PCB that is able to store the sensor readings and transmit the data to the phone.