Project

# Title Team Members TA Documents Sponsor
20 A mm-Wave Breath Monitoring System for Smart Vehicle Applications
 Bowen Song
He Chen
Kangning Li
Keyu Lu
 Xuyang Bai design_document1.pdf
final_paper2.pdf
proposal1.pdf
 Shurun Tan
# TEAM MEMBERS:
Kangning Li (kl32@illinois.edu 3190110100),

He Chen (hechen4@illinois.edu 3190110853).

Bowen Song (bowen15@illinois.edu 3190110710).

Keyu Lu (keyulu2@illinois.edu 3190110390).

# A MMWAVE BREATH MONITORING SYSTEM FOR SMART VEHICLE APPLICATIONS
# PROBLEM:
With the development of the intelligent automobile industry, radar technology has been applied to automobiles. Common radar applications include optical radar, laser radar, and millimeter wave radar. At present, the technology of outside vehicle radar is highly developed, such as using laser radar to measure distance. But we're focusing more on radar applications inside the car.

Nowadays, many traffic accidents are caused by drivers' fatigue driving. How to detect drivers' breathing state quickly and accurately has become a hot topic. At the same time, the children left in the car is also a problem that urgently needs to be solved. Therefore, we hope to rely on radar technology to realize the breath detection of drivers and children in the car.

# SOLUTION OVERVIEW:
The method we are going to apply is using the millimeter wave sensor to detect the situation inside the car. By processing the data from the radar, we want to achieve breath detection. We choose to use 60G millimeter wave sensor for its harmless to human and it’s allowed to use in China. For signal processing, we can use artificial intelligence or statistical approach. This is partly dependent on how much data we can collect. We plan to finish radar signal processing and self-detection technology in complex and diverse environments. The detections for children of different ages, people under different shielding materials and different postures are our future goals.

# SOLUTION COMPONENTS:
TI-60GHz mmWave Radar Development board: IWR6843ISK-ODS Hardware link and data collection.

A sensor to work on Millimeter wave radar range detection and micro-doppler detection technology.

An algorithm to do radar signal processing and self-detection technology in complex and diverse environments.

An interface to connect the computer software and radar sensor.

AI algorithm or Statistics method which is used to adjust the software and work on the data processing.

# CRITERION FOR SUCCESS:
We expect to produce a vehicle-mounted mmWave radar that will have the following properties:

Reliability: It can work well under variety of environments, including children for different ages, people under different shielding materials, people with different postures, environment with more than one people, people during walking, people during fitness, etc.

Security: It won’t cause any kind of damage to people under any circumstances.

Easy to use: The mmWave Radar system should produce obvious information which is easy for user to get and understand.

Accuracy: The mmWave radar system should produce result with high accuracy, avoid incorrect result caused by various environment distraction.

Efficiency: The speed for our system to produce the information should be fast, which means it should collect the environment and produce in time feedback efficiently.

# DISTRIBUTION OF WORK:
EE Kangning Li, Keyu Lu, He Chen:

Exploit the radar sensor to obtain the data during the lab. Develop and implement the periodic linearly-increasing frequency chirps (known as Frequency-Modulated Continuous Wave (FMCW)). Design the lab steps and organize the structures of the lab. Control the lab environment to meet the standards.

ECE Bowen Song:

Use the signal data to do the signal processing and improve the detection precision. Implement and test the processing system for different targets.

3D Scanner

Peiyuan Liu, Jiayi Luo, Yifei Song, Chenchen Yu

Featured Project

# Team Members

Yifei Song (yifeis7)

Peiyuan Liu (peiyuan6)

Jiayi Luo (jiayi13)

Chenchen Yu (cy32)

# 3D Scanner

# Problem

Our problem is how to design an algorithm that uses a mobile phone to take multiple angle photos and generate 3D models from multiple 2D images taken at various positions. At the same time, we will design a mechanical rotating device that allows the mobile phone to rotate 360 degrees and move up and down on the bracket.

# Solution Overview

Our solution for reconstructing a 3D topology of an object is to build a mechanical rotating device and develop an image processing algorithm. The mechanical rotating device contains a reliable holder that can steadily hold a phone of a regular size, and an electrical motor, which is fixed in the center of the whole system and can rotate the holder 360 degrees at a constant angular velocity.

# Solution Components

## Image processing algorithms

- This algorithm should be capable of performing feature detection which is essential for image processing. It should be able to accurately identify and extract relevant features of an object from multiple 2D images, including edges, corners, and key points.

- This algorithm should be designed to minimize the memory requirement and energy consumption, because mobile phones have limited memory and battery.

## Mechanical rotating system

Phone holder that can adjust its size and orientation to hold a phone steadily

Base of the holder with wheels that allows the holder to move smoothly on a surface

Electrical motor for rotating the holder at a constant angular velocity

Central platform to place the object

The remote-control device can be used to control the position of the central platform. Different types of motors and mechanisms can be used for up and down, such as the stepper motors, servo motors, DC motors, and AC motors.

# Criterion for Success

- Accuracy: The app should be able to produce a 3D model that is as accurate as possible to the real object, with minimal distortion, errors or noise.

- Speed: The app should be able to capture and process the 3D data quickly, without requiring too much time or processing power from the user's device.

- Output quality: The app should be able to produce high-quality 3D models that can be easily exported and used in other software applications or workflows.

- Compatibility: Any regular phone can be placed and fixed on the phone holder with a certain angle and does not come loose

- Flexibility: The holder with a phone must be able to rotate 360 degrees smoothly without violent tremble at a constant angular velocity

# Distribution of Work

Yifei Song

Design a mobile app and deploy a modeling algorithm to it that enables image acquisition and 3D modeling output on mobile devices.

Peiyuan Liu:

Design an algorithm for modeling 3D models from multiple view 2D images.

Jiayi Luo:

Design the remote-control device. Using the electrical motors to control the central platform of the mechanical rotating system.

Chenchen Yu:

Design the mechanical part. Build, test and improve the mechanical rotating system to make sure the whole device works together.