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. |