Smartphone-based Measurement of Acceleration: Development of a Smartphone Application for Use in an Engineering Dynamics Course

Scott Bevill; Kelly Bevill

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Conference: 2015 ASEE Annual Conference & Exposition
Location: Seattle, Washington
Publication Date: June 14, 2015
Start Date: June 14, 2015
End Date: June 17, 2015
ISBN: 978-0-692-50180-1
ISSN: 2153-5965
Conference Session: Dynamics
Tagged Division: Mechanical Engineering
Page Count: 11
Page Numbers: 26.1377.1 - 26.1377.11
DOI: 10.18260/p.24714
Permanent URL: https://peer.asee.org/24714
Download Count: 793

Paper Authors

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Scott Bevill Colorado Mesa University

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Scott Bevill is an Assistant Professor of Mechanical Engineering at Colorado Mesa University in Grand Junction, CO. He completed his Ph.D. in Mechanical Engineering in 2009 at Stanford University.

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biography

Kelly Bevill Colorado Mesa University

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Kelly Bevill, P.E., is an Assistant Professor of Construction Management at Colorado Mesa University in Grand Junction, CO. She completed her M.S. in Environmental Engineering in 2005 at Cornell University.

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Abstract

Smartphone-Based Measurement of Acceleration: Development of a Smartphone Application for Use in an Engineering Dynamics CourseThere is an increasing trend towards use of smartphones as mobile computing devices, and engineeringeducation should stay abreast of this movement. The built-in sensing capabilities of most smartphoneslend themselves especially well to engineering mechanics classes (such as Dynamics) in which kinematicrelationships between position, velocity, acceleration, and time are taught. The purpose of this paper is todescribe the development and implementation of a smartphone application and laboratory exercise toallow students to use smartphones to collect kinematic data during a routine activity (such as driving anautomobile). The smartphone application, which obtains position and velocity data using a smartphone’sbuilt-in assisted-global positioning system (A-GPS) and three components of acceleration using the built-in accelerometer, is made available to students (Figure 1). Following data collection, the laboratoryexercise requires students to calculate and compare normal and tangential components of accelerationbased on each of the two recorded data sets. In addition to introducing students to applicationdevelopment, the laboratory described here also provides an opportunity for deeper learning aboutcomputational methods (such as numerical differentiation) and approaches to dealing with noise inexperimental data.A sample data set is provided to demonstrate the calculations required to compare acceleration valuesmeasured using the on-board accelerometer with acceleration values calculated from position and velocitydata collected using the on-board A-GPS (Figure 2). This laboratory was deployed in Fall 2013 andSpring 2014 semesters and, upon completion, a questionnaire was distributed to solicit student feedbackon the laboratory exercise. Feedback suggests that students enjoyed using a smartphone application in atechnical setting, appreciated collecting and analyzing data outside of an artificial laboratory setting, andfelt that the laboratory contributed positively to their understanding of acceleration calculations in thenormal-tangential coordinate system. The overall positive feedback supports the suitability of thislaboratory exercise for implementation in a sophomore-level engineering dynamics course. Further, thislaboratory exercise may be used as a strategy to address ABET student outcome (k), “an ability to use thetechniques, skills, and modern engineering tools necessary for engineering practice.”A copy of the laboratory handout and the Xcode project (source code for the smartphone application)used for the student laboratory exercise reported in this paper may be obtained by contacting the leadauthor.Figure 1: At left, application interface during data collection. At right, an email automatically composedby the application with logged data in CSV format. 1 Normal acceleration (m/s^2) 0.8 Accelerometer based GPS Based 0.6 0.4 0.2 0 0 10 20 30 40 50 Time (s)Figure 2: Normal acceleration calculations from accelerometer data (blue) and GPS-based positional data(red). The correlation coefficient between GPS-based and accelerometer-based normal acceleration valuesis r = 0.664. Similar calculations were performed for the tangential component of acceleration.

Citation
Format

Bevill, S., & Bevill, K. (2015, June), Smartphone-based Measurement of Acceleration: Development of a Smartphone Application for Use in an Engineering Dynamics Course Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24714

TY  - CPAPER
AB  -       Smartphone-Based Measurement of Acceleration: Development of a      Smartphone Application for Use in an Engineering Dynamics CourseThere is an increasing trend towards use of smartphones as mobile computing devices, and engineeringeducation should stay abreast of this movement. The built-in sensing capabilities of most smartphoneslend themselves especially well to engineering mechanics classes (such as Dynamics) in which kinematicrelationships between position, velocity, acceleration, and time are taught. The purpose of this paper is todescribe the development and implementation of a smartphone application and laboratory exercise toallow students to use smartphones to collect kinematic data during a routine activity (such as driving anautomobile). The smartphone application, which obtains position and velocity data using a smartphone’sbuilt-in assisted-global positioning system (A-GPS) and three components of acceleration using the built-in accelerometer, is made available to students (Figure 1). Following data collection, the laboratoryexercise requires students to calculate and compare normal and tangential components of accelerationbased on each of the two recorded data sets. In addition to introducing students to applicationdevelopment, the laboratory described here also provides an opportunity for deeper learning aboutcomputational methods (such as numerical differentiation) and approaches to dealing with noise inexperimental data.A sample data set is provided to demonstrate the calculations required to compare acceleration valuesmeasured using the on-board accelerometer with acceleration values calculated from position and velocitydata collected using the on-board A-GPS (Figure 2). This laboratory was deployed in Fall 2013 andSpring 2014 semesters and, upon completion, a questionnaire was distributed to solicit student feedbackon the laboratory exercise. Feedback suggests that students enjoyed using a smartphone application in atechnical setting, appreciated collecting and analyzing data outside of an artificial laboratory setting, andfelt that the laboratory contributed positively to their understanding of acceleration calculations in thenormal-tangential coordinate system. The overall positive feedback supports the suitability of thislaboratory exercise for implementation in a sophomore-level engineering dynamics course. Further, thislaboratory exercise may be used as a strategy to address ABET student outcome (k), “an ability to use thetechniques, skills, and modern engineering tools necessary for engineering practice.”A copy of the laboratory handout and the Xcode project (source code for the smartphone application)used for the student laboratory exercise reported in this paper may be obtained by contacting the leadauthor.Figure 1: At left, application interface during data collection. At right, an email automatically composedby the application with logged data in CSV format.                                  1   Normal acceleration (m/s^2)                                 0.8                                                                     Accelerometer based                                                                     GPS Based                                 0.6                                 0.4                                 0.2                                  0                                       0   10   20              30          40             50                                                     Time (s)Figure 2: Normal acceleration calculations from accelerometer data (blue) and GPS-based positional data(red). The correlation coefficient between GPS-based and accelerometer-based normal acceleration valuesis r = 0.664. Similar calculations were performed for the tangential component of acceleration.
AU  - Scott Bevill
AU  - Kelly Bevill
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Smartphone-based Measurement of Acceleration: Development of a Smartphone Application for Use in an Engineering Dynamics Course
UR  - https://peer.asee.org/24714
DO  - 10.18260/p.24714
ER  -