Team Leader John Sedig Communications / Documentation Kevin Nennig Webmaster / Software Design Matt Graves Hardware / Electrical Design Josh Mandich Software.

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Presentation transcript:

Team Leader John Sedig Communications / Documentation Kevin Nennig Webmaster / Software Design Matt Graves Hardware / Electrical Design Josh Mandich Software Design Alex Wesenberg Team Advisor Arun Somani

o Many bicyclists are injured due to car related accidents on the road each year. o If a bicyclist could be warned of rear approaching vehicles, this could greatly reduce number of bicyclist involved in accidents. o Primary Goal - To design and develop a low cost vehicle alert accessory for cyclists

o The device must communicate via the ANT+ protocol to an Edge 500 Garmin head unit o Must be able to detect cars going from speeds 10mph-70mph o Must detect vehicles within 100m behind the rear of the bicycle

o The device should be mounted under the bicycle seat o The device will reduce accidents for both cyclists and vehicles by promoting awareness of road conditions to the cyclist o The enclosure hosts the device and batteries behind the bicycle

o Mirror o Basic solution for viewing cars behind bicycle o Not aerodynamic o Requires user to orient correctly o Cerevellum Digital Bike Camera o Rear-facing digital video camera o Does not detect vehicles, only displays them o Allows user to record what is behind them o Useful for determining faults of vehicle accidents

Power

Edge 500 Head Unit ANT+ Transceiver 1000mAh 7.4 V Li-Po battery Beagleboard -XM Logitech WebCam

o BeagleBoard voltage input: 5V o Average current Draw : 700mA o Power Consumption : 3.5 W o Rechargeable and mobile system

o 1000mAh Lithium-ion polymer 2S 7.4V battery o Switching Voltage Regulator o Minimum 1.25 hour life cycle

o Went from 5M Aptina camera board to Logitech c310 o Emphasis changed later on in semester to focus on algorithms and car detection 5M MT9P031 Camera Board Logitech WebCam

o Previous o Sobel o Hough o PCA o Optical Flow

Averaged Image =

=

o Actual o Optical Flow o Haar Object Detection o HaarTraining

o Uses a precompiled cascade classifier o Scans the ROI for the object

o Communicate with ANT+ Transceiver over USB, using USB Serial LKM o Use of high Heart Rate signal due to lack of programming interface on the head unit

o Be able to successfully detect a car in our worst case (car going 70mph, detection distance of 100m) o Be able to detect each car at least once within this interval

o Cyclist Performance o Module o Platform o System o Requirements

o First Detection o Worst Case Detection Time o Algorithm Time Resolution Processed: 320x240 Frames Processed419 Detected And Notification Sent (number of frames)56 Optical FlowHaarTotal Frame Average227.5ms230.4ms459.8ms Median200ms 390ms Max570ms620ms1200ms Min170ms100ms300ms

o Reaction Time o ANT+ High Heart Rate Time o Total Time = 4.7 seconds < 5.07 seconds Average: 2.07

Total units sold80,000100,000120,000 Price $ Cost of Goods Sold $ Marginal Revenue $ Gross Revenue $ 1,200,000 $ 1,500,000 $ 1,800,000 o Gross margin : 33% o Does not account for increase in inventory, capital, staff, or marketing

o Know your team’s abilities o Bottlenecks in the development process o Ask the right questions