1. SENSITIVITY AND FREQUENCY ANALYSIS FOR NANO-SCALED LIGHT SENSOR, ACCELEROMETER, AND TEMPERATURE SENSOR by Michael Fielkow 1

2. Hardware  Dongle  Nikon Coolpix S550  Holmes HASF99 Stand (Pedestal) Fan  Kelvinator refrigerator/freezer 2

3. Software  CamShot  Windows Movie Maker  Matlab Code: Data_Collect.m, Data_Plot.m, Data_Filter.m (provided by Professor A. Levi) data_processing1p7b_2.m (provided by Philip Seliger) alterations to Matlab code 3

4. Diagram of System Architecture USB Controller ADC MUX Temp. Sensor Accelerometer X y z Pressure Sensor Humidity Sensor Light Detector 10 b Dongle Port USB Controller Host I/O Port Matlab User Interface 4

5. Performance measurements: Light Sensor – Traffic Analysis  Examining changing light intensities due to the automobile headlights of passing traffic.  Includes time-stamped snapshots of video that corresponds with the light sensor’s data.  Original results are filtered to reduce noise due to ambient light sources.  Comparison of Real-Time Data results. 5

6. Measurement section one – traffic  Unfiltered time domain graph of light sensor data detecting traffic 6

7. Filtered time domain graph of light sensor data detecting traffic (moving average filter) A B C D EF 0:00:14 A 0:00:19 B 0:00:27 C 0:00:39 D0:00:42 E 7

8. Measurement section two - slow moving car pulling into driveway 0:00:100:00:110:00:120:00:130:00:14 8

9. Measurement section three – Real- Time detection of traffic 9

10. Measurement section three – Real- Time detection of traffic… 10

11. RESULTS : Performance measurements: Light Sensor – Traffic Analysis  Light Sensor is sufficient to measure nighttime traffic patterns (i.e. the passing of cars/headlights at night).  Real-Time Data gathered through data_processing1p7b_2.m is not as accurate as nonReal-Time data. Why? (needs further research) 11

12. #2 Performance measurements: Light Sensor and Accelerometer – Rotating Fan 12

13. Performance measurements: Light Sensor and Accelerometer – Rotating Fan  Measuring both acceleration and light sensor data when dongle is placed on a rotating fan.  Test Several Scenarios: fan off fan on “low” and stationary fan on “low” and rotating fan on “high” and stationary fan on “high” and rotating  Original results are filtered to reduce noise. attempt to eliminate fan vibrations.  Comparison of Real-Time Data results. 13

14. Measurement section one – fan off – acceleration Unfiltered Signal Filtered Signal (moving average) 14

15. Measurement section two – fan on “low” and stationary – acceleration 15

16. Measurement section three – fan on “low” and rotating – acceleration 16

17. Measurement section two (b) – fan on “low” and stationary – light 17

18. Measurement section three (b) – fan on “low” and rotating – light Clear sinusoidal signal 18

19. Measurement section four – fan on “high” and rotating – light  Clear sinusoidal signal at both “high” and “low” fan settings Low_Pass Moving Average Filter 19

20. Some slight sinusoidal motion can be seen when watching in Real-Time. Measurement section six – fan on “low” and rotating – light – Real-Time Data 20

21. RESULTS: Performance measurements: Light Sensor and Accelerometer – Rotating Fan  Accelerometer is insufficient to measure slow sinusoidal rotations such as the fan’s movement. Fan vibrations may be a cause of accelerometer error.  Light sensor successfully proves sinusoidal motion (directed at a single light source). Unaffected by “high” and “low” fan settings.  Real_Time light sensor data acurately reflects the sinusoidal motion found in previous experimentation. 21

22. Performance measurements: Temperature Sensor – Real- Time Data 22

23. Performance measurements: Temperature Sensor – Real-Time Data  Real-Time measuring of temperature in shifting environments.  3 environments: room temperature freezer refrigerator  Secondary test of dongle’s ability to sense when a freezer has been left open. 23

24. Measurement section one – room temperature vs. household freezer – decreasing temperature Steady room temperature shows a relatively non-fluctuating frequency filter graph. Becomes highly sporadic upon shift in ambient temperature and more periodic as rate of temperature change levels out. 24

25. Measurement section two – refrigerator vs. room temperature – increasing temperature Frequency filter graph shows shift from little fluctuation to strong amplitude change when sensor goes from steady cold to room temperature environment. 25

26. Measurement section three – open freezer 26

27. RESULTS: Performance measurements: Temperature Sensor – Real-Time Data  Clear and steady change in temperature was seen when dongle was placed in shifted environment.  Frequency filter graph could be used to identify significant changes in ambient temperature.  Temperature sensor could successfully be used to identify when a freezer door was left open. 27

28. Example of experimental error 28

29. THE END 29