Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 12 | Cycling Assist System with Rear Camera Detection |
Jacob Betz Jingdi Liu Trisha Yadav |
Jeff Chang | design_document1.pdf final_paper2.pdf final_paper1.pdf other1.pdf photo1.jpg photo2.jpg photo3.jpg presentation1.pdf proposal1.pdf video1.mp4 |
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| # Cycling Assist System with Rear Camera Detection Team Members: - Jacob Betz (jmbetz2) - Trisha Yadav (tyadav4) - Jingdi Liu (jingdil2) # Problem Many cyclists run into different dangerous situations while biking on the road. For example, a vehicle may be rapidly approaching in their blindspot, which could cause serious injuries. Another possible danger is the bike leaning too far to the left or right. We are hoping to create a detection system to help distracted drivers and riders from potential accidents. # Solution Our solution is to create a low power, user friendly system that can assist cyclists in all of the safety areas listed above. The system would monitor and detect approaching objects in the rear using a camera as well as inform the user if they are leaning too far in one direction. Our system will be competitive compared to other assistance systems in the market on cost and functionality aspects. # Solution Components List of Components: - 1080p USB Camera - MPU6050 6-axis IMU - Raspberry PI 4 (4GB) - Arduino Nano - Custom PCB - LED Indicator Lights Component Breakdown: - Rear Camera: On the rear of the bike, a camera will be used to monitor the rear of the cyclist. The camera feed will be used to show the cyclist a rear view on the dashboard and will be fed into OpenCV with object detection to detect vehicles, other bikes, etc. We will use a small 1080p USB camera and 3D printed enclosure to mount on the back of the bicycle seat. - Stability IMU: This sensor is a unique idea to monitor the cyclists roll stability on their bike. It would let the driver know if they were leaning too far in one direction. The IMU we have selected is the MPU6050 6-axis. The IMU will be located on the custom dashboard PCB. - Custom Dashboard: The driver would be notified using our dashboard. This dashboard, mounted near the handle bars, would have a 3.5 inch LCD display showing the cyclist its rear view from the camera feed. It would also include an array of LED indicator lights to warn the cyclist how close a vehicle, other cyclist or bus is to the driver from behind. Lastly, it would include a brightening LED that tells the driver how far it's leaning to the left or right using the IMU feed. The dashboard would include a Raspberry Pi 4 and Arduino Nano. The Raspberry Pi will be used for OpenCV object detection as well as driving the LCD display. The Arduino Nano will be used with the IMU I2C communication and light up the necessary LEDs. Both of these microcontrollers would connect to the custom PCB that holds the sensors, LED lights and attaches the display. The enclosure would be a 3D printed case that mounts to the bicycle handlebars. - Small Battery: A small battery will be needed to power the system. This battery will be located next to the dashboard, part of the same enclosure as the PCB. # Criterion For Success - Priced competitively with other bike sensors in the market - Device needs to be able to scan for approaching objects or vehicles, and effectively warn the cyclist of the approaching object on the user’s custom dashboard - Device needs to be able to inform the user that the bike is leaning too far in a certain direction through a brightening LED - The camera needs to be small enough and secured well to be able to stay attached to the bike, even in rough terrain - Camera and dashboard should be waterproof in order to ensure that the driver can utilize the device in different weather conditions |
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