Project

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

Bracelet Aid for deaf people/hard of hearing

Aarushi Biswas, Yash Gupta, Anit Kapoor

Bracelet Aid for deaf people/hard of hearing

Featured Project

# PROJECT TITLE: Bracelet Aid for deaf people/hard of hearing

# TEAM MEMBERS:

- Aarushi Biswas (abiswas7)

- Anit Kapoor (anityak3)

- Yash Gupta (yashg3)

# PROBLEM

We are constantly hearing sounds around us that notify us of events occurring, such as doorbells, fire alarms, phone calls, alarms, or vehicle horns. These sounds are not enough to catch the attention of a d/Deaf person and sometimes can be serious (emergency/fire alarms) and would require the instant attention of the person. In addition, there are several other small sounds produced by devices in our everyday lives such as washing machines, stoves, microwaves, ovens, etc. that cannot be identified by d/Deaf people unless they are observing these machines constantly.

Many people in the d/Deaf community combat some of these problems such as the doorbell by installing devices that will cause the light in a room to flicker. However, these devices are generally not installed in all rooms and will also obviously not be able to notify people if they are asleep. Another common solution is purchasing devices like smartwatches that can interact with their mobile phones to notify them of their surroundings, however, these smartwatches are usually expensive, do not fulfill all their needs, and require nightly charging cycles that diminish their usefulness in the face of the aforementioned issues.

# SOLUTION

A low-cost bracelet aid with the ability to convert sounds into haptic feedback in the form of vibrations will be able to give d/Deaf people the independence of recognizing notification sounds around them. The bracelet will recognize some of these sounds and create different vibration patterns to catch the attention of the wearer as well as inform them of the cause of the notification. Additionally, there will be a visual component to the bracelet in the form of an OLED display which will provide visual cues in the form of emojis. The bracelet will also have buttons for the purpose of stopping the vibration and showing the battery on the OLED.

For instance, when the doorbell rings, the bracelet will pick up the doorbell sound after filtering out any other unnecessary background noise. On recognizing the doorbell sound, the bracelet will vibrate with the pattern associated with the sound in question which might be something like alternating between strong vibrations and pauses. The OLED display will also additionally show a house emoji to denote that the house doorbell is ringing.

# SOLUTION COMPONENTS

Based on this solution we have identified that we need the following components:

- INMP441 (Microphone Component)

- Brushed ERM (Vibration Motor)

- Powerboost 1000 (Power subsystem)

- 1000 mAh LiPo battery x 2 (hot swappable)

- SSD1306 (OLED display)

## SUBSYSTEM 1 → SOUND DETECTION SUBSYSTEM

This subsystem will consist of a microphone and will be responsible for picking up sounds from the environment and conducting a real-time FFT on them. After this, we will filter out lower frequencies and use a frequency-matching algorithm to infer if a pre-programmed sound was picked up by the microphone. This inference will be outputted to the main control unit in real-time.

## SUBSYSTEM 2 → VIBRATION SUBSYSTEM

This subsystem will be responsible for vibrating the bracelet on the wearer’s wrist. Using the vibration motor mentioned above, we should have a frequency range of 30Hz~500Hz, which should allow for the generation of a variety of distinguishable patterns. This subsystem will be responsible for the generation of the patterns and control of the motor, as well as prompting the Display subsystem to visualize the type of notification detected.

## SUBSYSTEM 3 → DISPLAY SUBSYSTEM

The Display subsystem will act as a set of visual cues in addition to the vibrations, as well as a visual feedback system for user interactions. This system should not draw a lot of power as it will be active only when prompted by user interaction or by a recognized sound. Both of these scenarios are relatively uncommon over the course of a day, which means that the average power draw for our device should still remain low.

## SUBSYSTEM 4 → USER INTERACTION SUBSYSTEM

This subsystem is responsible for the interaction of the user with the bracelet. This subsystem will include a set of buttons for tasks such as checking the charge left on the battery or turning off a notification. Checking the charge will also display the charge on the OLED display thus interacting and controlling the display subsystem as well.

## SUBSYSTEM 5 → POWER SUBSYSTEM

This subsystem is responsible for powering the device. One of our success criteria is that we want long battery life and low downtime. In order to achieve this we will be using a power boost circuit in conjunction with two rechargeable 1000 mAh batteries. While one is charging the other can be used so the user doesn’t have to go without the device for more than a few seconds at a time. We are expecting our device to use anywhere from 20-50mA which would mean we get an effective use time of more than a day. The power boost circuit and LiPo battery’s JST connector allow the user to secure and quick battery swaps as well.

# CRITERION FOR SUCCESS

- The bracelet should accurately identify only the crucial sounds in the wearer’s environment with each type of sound having a fixed unique vibration + LED pattern associated with it

- The vibration patterns should be distinctly recognizable by the wearer

- Should be relatively low cost

- Should have prolonged battery life (so the power should focus on only the use case of converting sound to vibration)

- Should have a small profile and a sleek form factor

Project Videos