Small, Lightweight Speed and Distance Sensorfor Skiers and Snowboarders

Michael BekkalaMichael Blair

Michael Carpenter Matthew Guibord

Abhinav ParvataneniDr. Shanker Balasubramaniam

Objective Introduction Design Requirements Proposed Solution Testing Results Conclusions and Accomplishments

Introduction Living by the numbers

Measuring and interpreting your performance has never been more valuable

Critical to gain a competitive edge Most devices are based on repetitive motion but

don’t apply to skiing or snowboarding Nike+ Bicycle speedometer

Goal: Build a speed and distance sensor for skiers and snowboarders

Design RequirementsOperable in Subzero Temperatures

Useable in winter apparel

Lightweight – Less than two pounds

Cost – less than $500

Battery Life greater than 2 hours

Accurately record speed and distance

Proposed Solution Integration of two major systems

Global Positioning System (GPS) Inertial Navigation System (INS)

Inertial Navigation System Comprised of accelerometers and gyroscopes

Accelerations Angular Velocities

Requires analog to digital conversion Careful calibration is required to achieve high

accurate readings Gives great short-term

accuracy, but errors growwith time.

Global Positioning System Gives position in terms of

longitude, latitude, and altitude

Determine distance, displacement and speed

NMEA 0183 communications standard

Long term reliability, butpoor short term accuracy.

Sampled at 1Hzhttp://en.wikipedia.org/wiki/Gps

Kalman Filtering Advanced sensor integration technique

Uses statistical error measurements to provide a better estimate

Accuracy improves with time Can use the estimate to regulate INS errors

User Interface Easily accessible menu displayed on LCD

Review Performance Average and Peak Speed (mph) Distance and Displacement (miles)

Color changing buttons Color of button changes depending on their use Intuitive color scheme aids usability (ie. Red

for Stop, Green for Go)

Menu Hierarchy

PC Interface Upload run data from device

Can be saved on your PC for performance tracking and reference

Points can be plotted in Google Earth

Visual representation ofdata using graphs

PC Interface Example

Successful Failure Reached beyond design requirements with an innovative

solution Unpredicted complexity of INS and Kalman filter

Hardware implemented, software not ready Invaluable knowledge gained through:

Research Trial and error

Despite proposed solution being a successful failure GPS solution that meets and exceeds design requirements Extensive user functionality

Store, retrieve, and manage data all on device or through a PC

Higher data sample rate for greater accuracy Rechargeable battery

Kalman Filter Divergence Difficult to

troubleshoot due to 1200+ lines of code

Unsuccessful in determining cause of divergence

Poor Initialization might be to blame

Confident that with more time, root cause could be determined

Testing Results Several Trials

Moving vehicle On foot Varying speeds and distances

Peak speed had significant error One bad sample results in erroneous reading

Average speed had reasonable accuracy based on number of data points

Results verified by digital speedometer and consumer GPS.

Conclusions and Accomplishments GPS Solution

Accurate average and peak speeds Distance accurate over a large span

Inaccurate over short spans and slow speeds

Robust Display Menu Allows easy access to data and configuration

options PC Interfacing

Plot a run on Google Earth with the click of a mouse Plot speed over time to visualize a run

Future Considerations Printed Circuit Board USB Compatibility Wireless headset communication via

Bluetooth Smaller form factor INS integrated through Kalman Filtering