Project

# Title Team Members TA Documents Sponsor
45 Programmable Ferrofluid Display
Bradley Anderson
Hao Jen Chien
Thomas Coyle
Luke Wendt appendix0.zip
design_document0.pdf
design_document0.pdf
final_paper0.pdf
photo0.jpg
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presentation0.pptx
proposal0.pdf
video0.mp4
video0.m4v
For our project, our team would like to build a lower cost programmable ferrofluid display than is currently available. We would be building upon the work of the team which worked on a similar project last semester in order to make a more feature-filled device.
The previous group project used an array of permanent magnets which moved by electromagnets along tubes to manipulate the magnetic fluid. Instead, we propose to build a device with at least a 5x5 grid of permanent magnets attached to small servos.
We would also like to add a layer of IR sensors in an array between the magnets and the fluid. We can then use these sensors to return information about fluid distribution within the display. This will allow software controlling the display to more accurately maneuver the ferrofluid.
All of the magnets and sensors would be wired into a microcontroller, which will have an IO port for control from a computer. The microcontroller will provide an API for the computer to interact with the display, which will include functions for enabling/disabling individual magnets and returning a 2-dimensional array of the IR sensor values.
Ultimately, the project should cost approximately $300 to $400. For a 5x5 magnet display, we will need 25 magnets, servos, and IR sensors to interact with the ferrofluid. We will also need a watertight enclosure for the display, as well ferrofluid and a PCB and microcontroller to manage the servos and sensors. The servos should be the bulk of the cost. Comparatively, the sensors, other electronics, magnets, ferrofluid, and enclosure will be relatively inexpensive. We will be sure to acquire non-toxic ferrofluid for the project to minimize the risk of accidental poisoning.

BusPlan

Aashish Kapur, Connor Lake, Scott Liu

BusPlan

Featured Project

# People

Scott Liu - sliu125

Connor Lake - crlake2

Aashish Kapur - askapur2

# Problem

Buses are scheduled inefficiently. Traditionally buses are scheduled in 10-30 minute intervals with no regard the the actual load of people at any given stop at a given time. This results in some buses being packed, and others empty.

# Solution Overview

Introducing the _BusPlan_: A network of smart detectors that actively survey the amount of people waiting at a bus stop to determine the ideal amount of buses at any given time and location.

To technically achieve this, the device will use a wifi chip to listen for probe requests from nearby wifi-devices (we assume to be closely correlated with the number of people). It will use a radio chip to mesh network with other nearby devices at other bus stops. For power the device will use a solar cell and Li-Ion battery.

With the existing mesh network, we also are considering hosting wifi at each deployed location. This might include media, advertisements, localized wifi (restricted to bus stops), weather forecasts, and much more.

# Solution Components

## Wifi Chip

- esp8266 to wake periodically and listen for wifi probe requests.

## Radio chip

- NRF24L01 chip to connect to nearby devices and send/receive data.

## Microcontroller

- Microcontroller (Atmel atmega328) to control the RF chip and the wifi chip. It also manages the caching and sending of data. After further research we may not need this microcontroller. We will attempt to use just the ens86606 chip and if we cannot successfully use the SPI interface, we will use the atmega as a middleman.

## Power Subsystem

- Solar panel that will convert solar power to electrical power

- Power regulator chip in charge of taking the power from the solar panel and charging a small battery with it

- Small Li-Ion battery to act as a buffer for shady moments and rainy days

## Software and Server

- Backend api to receive and store data in mongodb or mysql database

- Data visualization frontend

- Machine learning predictions (using LSTM model)

# Criteria for Success

- Successfully collect an accurate measurement of number of people at bus stops

- Use data to determine optimized bus deployment schedules.

- Use data to provide useful visualizations.

# Ethics and Safety

It is important to take into consideration the privacy aspect of users when collecting unique device tokens. We will make sure to follow the existing ethics guidelines established by IEEE and ACM.

There are several potential issues that might arise under very specific conditions: High temperature and harsh environment factors may make the Li-Ion batteries explode. Rainy or moist environments may lead to short-circuiting of the device.

We plan to address all these issues upon our project proposal.

# Competitors

https://www.accuware.com/products/locate-wifi-devices/

Accuware currently has a device that helps locate wifi devices. However our devices will be tailored for bus stops and the data will be formatted in a the most productive ways from the perspective of bus companies.