Project :: ECE 445 - Senior Design Laboratory

#	Title	Team Members	TA	Documents	Sponsor
32	Scrubbing CO2	Alan Cardiel Kinjal Dey Seunghwan Hong	David Null	design_document2.pdf final_paper3.pdf photo1.jpeg photo2.jpeg photo3.png presentation1.pptx proposal2.pdf video
	# Scrubbing CO2 Team Members: - Student 1 (acard6) - Student 2 (kinjald2) - Student 3 (sh34) # Problem Many areas of the world have little access or have a hard time reaching drinkable water but may be surrounded by plenty of salt water. Local water is a local problem and it needs a local solution that needs to be acted on since fresh water is a valuable resource. With an increase of CO2 levels in recent years more and more fresh water becomes tainted for places that have a hard time accessing fresh water. # Solution What we for our project propose along with Professor Jont Allen is that we turn the nearby salt water into fresh water and at the same time extract the CO2 and convert it into graphite. This can be achieved by starting with a small test size of cold water which we will use to emulate salt water and pumping it in quantities into a long and wide aquifer, which we call aquipures. The aqupures then transport the "seawater" to a secondary tank that emulates desert environment. On the way to the final destination of the aquipure the sunshine from our light source which will emulate the sun evaporates the water, converting into water vapor. To trap the water vapor the aquipures are covered by a thin sheet of plastic, transparent to the sun's light. The water in the aquipures is continuously vaporized into and aerosol (small sub-millimeter sized droplets, to greatly accelerate the evaporation, by increasing the water's surface. Each of these steps only take small amounts of electricity. Once the humidity is raised to close to 100%, the moist air is sucked down channels by a low vacuum, where it comes in contact with a chilled surface. The cooling of the surface could be done by our ocean water as it comes in from the sea, which is typically much colder than the air. The slightly warmed sea water would then be used to flush the concentrated brine, resulting from the removal of H2O and CO2 from the sea water. # Solution Components ## Heating and humidity (RC1610001) - using a small semiconductor enclosure heater to be able able to control the temperature and humidity of the system where the system is to simulate a desert environment. ## Flow rate sensor (Plastic flow meter # 828) - Measure the amount of water flowing into the system, and send out a warning signal if it exceeds a to-be-determined value ## Temperature sensor (BMP180) - Measure the temperature at the different point of the system to ensure that the different parts of the system are working as intended and properly simulate the conditions we need. ## Water enclosure and housing - Our project will have four different enclosures for our water to be in. First is a place to store the source "salt water" for our project, the second where the heating of the water and evaporation, the third id where the water is then cooled for precipitation, and the last is to store out outcome of the process. # Criterion For Success - To accurately detect and read out the current state of the model. As well as be able to desalinate over 50% of our input water into drinkable water

Featured Project

# Oxygen Delivery Robot

Team Members:

- Rutvik Sayankar (rutviks2)

- Aidan Dunican (dunican2)

- Nazar Kalyniouk (nazark2)

# Problem

Children's interstitial and diffuse lung disease (ChILD) is a collection of diseases or disorders. These diseases cause a thickening of the interstitium (the tissue that extends throughout the lungs) due to scarring, inflammation, or fluid buildup. This eventually affects a patient’s ability to breathe and distribute enough oxygen to the blood.

Numerous children experience the impact of this situation, requiring supplemental oxygen for their daily activities. It hampers the mobility and freedom of young infants, diminishing their growth and confidence. Moreover, parents face an increased burden, not only caring for their child but also having to be directly involved in managing the oxygen tank as their child moves around.

# Solution

Given the absence of relevant solutions in the current market, our project aims to ease the challenges faced by parents and provide the freedom for young children to explore their surroundings. As a proof of concept for an affordable solution, we propose a three-wheeled omnidirectional mobile robot capable of supporting filled oxygen tanks in the size range of M-2 to M-9, weighing 1 - 6kg (2.2 - 13.2 lbs) respectively (when full). Due to time constraints in the class and the objective to demonstrate the feasibility of a low-cost device, we plan to construct a robot at a ~50% scale of the proposed solution. Consequently, our robot will handle simulated weights/tanks with weights ranging from 0.5 - 3 kg (1.1 - 6.6 lbs).

The robot will have a three-wheeled omni-wheel drive train, incorporating two localization subsystems to ensure redundancy and enhance child safety. The first subsystem focuses on the drivetrain and chassis of the robot, while the second subsystem utilizes ultra-wideband (UWB) transceivers for triangulating the child's location relative to the robot in indoor environments. As for the final subsystem, we intend to use a camera connected to a Raspberry Pi and leverage OpenCV to improve directional accuracy in tracking the child.

As part of the design, we intend to create a PCB in the form of a Raspberry Pi hat, facilitating convenient access to information generated by our computer vision system. The PCB will incorporate essential components for motor control, with an STM microcontroller serving as the project's central processing unit. This microcontroller will manage the drivetrain, analyze UWB localization data, and execute corresponding actions based on the information obtained.

# Solution Components

## Subsystem 1: Drivetrain and Chassis

This subsystem encompasses the drive train for the 3 omni-wheel robot, featuring the use of 3 H-Bridges (L298N - each IC has two H-bridges therefore we plan to incorporate all the hardware such that we may switch to a 4 omni-wheel based drive train if need be) and 3 AndyMark 245 RPM 12V Gearmotors equipped with 2 Channel Encoders. The microcontroller will control the H-bridges. The 3 omni-wheel drive system facilitates zero-degree turning, simplifying the robot's design and reducing costs by minimizing the number of wheels. An omni-wheel is characterized by outer rollers that spin freely about axes in the plane of the wheel, enabling sideways sliding while the wheel propels forward or backward without slip. Alongside the drivetrain, the chassis will incorporate 3 HC-SR04 Ultrasonic sensors (or three bumper-style limit switches - like a Roomba), providing a redundant system to detect potential obstacles in the robot's path.

## Subsystem 2: UWB Localization

This subsystem suggests implementing a module based on the DW1000 Ultra-Wideband (UWB) transceiver IC, similar to the technology found in Apple AirTags. We opt for UWB over Bluetooth due to its significantly superior accuracy, attributed to UWB's precise distance-based approach using time-of-flight (ToF) rather than meer signal strength as in Bluetooth.

This project will require three transceiver ICs, with two acting as "anchors" fixed on the robot. The distance to the third transceiver (referred to as the "tag") will always be calculated relative to the anchors. With the transceivers we are currently considering, at full transmit power, they have to be at least 18" apart to report the range. At minimum power, they work when they are at least 10 inches. For the "tag," we plan to create a compact PCB containing the transceiver, a small coin battery, and other essential components to ensure proper transceiver operation. This device can be attached to a child's shirt using Velcro.

## Subsystem 3: Computer Vision

This subsystem involves using the OpenCV library on a Raspberry Pi equipped with a camera. By employing pre-trained models, we aim to enhance the reliability and directional accuracy of tracking a young child. The plan is to perform all camera-related processing on the Raspberry Pi and subsequently translate the information into a directional command for the robot if necessary. Given that most common STM chips feature I2C buses, we plan to communicate between the Raspberry Pi and our microcontroller through this bus.

## Division of Work:

Given that we already have a 3 omni wheel robot, it is a little bit smaller than our 50% scale but it allows us to immediately begin work on UWB localization and computer vision until a new iteration can be made. Simultaneously, we'll reconfigure the drive train to ensure compatibility with the additional systems we plan to implement, and the ability to move the desired weight. To streamline the process, we'll allocate specific tasks to individual group members – one focusing on UWB, another on Computer Vision, and the third on the drivetrain. This division of work will allow parallel progress on the different aspects of the project.

# Criterion For Success

Omni-wheel drivetrain that can drive in a specified direction.

Close-range object detection system working (can detect objects inside the path of travel).

UWB Localization down to an accuracy of < 1m.

## Current considerations

We are currently in discussion with Greg at the machine shop about switching to a four-wheeled omni-wheel drivetrain due to the increased weight capacity and integrity of the chassis. To address the safety concerns of this particular project, we are planning to implement the following safety measures:

- Limit robot max speed to <5 MPH

- Using Empty Tanks/ simulated weights. At NO point ever will we be working with compressed oxygen. Our goal is just to prove that we can build a robot that can follow a small human.

- We are planning to work extensively to design the base of the robot to be bottom-heavy & wide to prevent the tipping hazard.