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Prof. Kristofer S.J. Pister’s team Berkeley Sensor and Actuator Center University of California, Berkeley
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Part II Workshop Hardware - Capabilities and Resources Dr. Anita Flynn
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3 Building on 20 Years of Sensor Research MEMS devices, sensors & microrobots since ’80s
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4 Building on 20 Years of Sensor Research Autonomous robots since ‘87
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5 Building on 20 Years of Sensor Research RF sensor network comms since ‘99
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6 Building on 20 Years of Sensor Research Recently: comms standards (IEEE802.15.4e) – Latest: Reference implementation for full stack (Watteyne) Open-source hardware & software in your kit Standards help industries grow Reference implementations help people port apps This workshop: networking your sensors
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7 Outline Wireless Sensor Networks Workshop Hardware Applications wsn.eecs.berkeley.edu
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8 Outline Wireless Sensor Networks Workshop Hardware Applications wsn.eecs.berkeley.edu
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9 Wireless Sensor Networks
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10 S. Oh et al, "Tracking and coordination of multiple agents using sensor networks: system design, algorithms and experiments," Proc. of the IEEE, 2007. S. Kim et al, “Health Monitoring of Civil Infrastructures Using Wireless Sensor Networks,” IPSN, Cambridge, MA, April 2007 A. Ledezci, http://www.isis.vanderbilt.edu/projects/countersniper J. Lees et al, “Reventador Volcano 2005: Eruptive Activity Inferred from Seismo-Acoustic Observation”, Jnl, of of Volcanology and Geothermal Research, 2007 Wireless Sensor Networks Sensor Networks for Security Structural Monitoring Sniper Localization Environmental Monitoring
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11 Building Automation Smart Grid Applications Industrial Automation Wireless Sensor Networks
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12 Outline Wireless Sensor Networks Workshop Hardware Applications wsn.eecs.berkeley.edu
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13 Wireless Motes Pister Group: numerous wireless sensor boards – Called them motes (short for “dust motes) – Used for various sensor research projects – Used for software development of protocol stacks – The latest: variety of 3-axis inertial sensors – Used in this workshop to demo OpenWSN stack – But OpenWSN can be ported to any processor wsn.eecs.berkeley.edu
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14 The General Inertial Navigation Assistant (GINA) Wireless mote with: – Two 3-axis accels – 3-axis gyroscope – 3-axis compass – 802.15.4 radio – 16-bit processor – Expansion headers GINA 1 January 2008 GINA 2.0 March 2009 GINA 2.1 July 2009 GINA 2.2 June 2010 http://warpwing.sourceforge.net/
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15 What’s In Your Kit? Open-source HW/SW Board layout files available online OpenWSN reference implementation, GPL-license (?) http://warpwing.sf.net http://wsn.eecs.berkeley.edu/workshop
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16 Sensitivity One 3-axis accelerometer for high rate (+- 8 G) coarse sensitivity noise density of 750 G/rtHz, bandwidth set to 1.8 kHz -> min resolvable acceleration: 32 mG Another 3-axis accelerometer for low rate (+- 2 G) but higher sensitivity noise density of 50 G/rtHz, bandwidth set to 40 Hz -> min resolvable acceleration: 0.32 mG
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17 Primary Design Considerations Low mass -> targeted for flying vehicles Plenty of actuator outputs Low power Low cost components Ease or low cost of manufacturing Not:
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18 Power Consumption
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19 Outline Wireless Sensor Networks Workshop Hardware Applications wsn.eecs.berkeley.edu
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20 Mini-Rocketry Put a 10 g micro satellite into low-earth orbit With a guidable rocket with cheap, off-the-shelf components To deploy a wireless sensor network
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21 Motion Capture
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22 Application to Mini-Robotics Coaxial Helicopter (UCB) Rotochure (GATech) Quadrotor (UMD) Crawler (UCB) Coaxial Helicopter (GATech)
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25 Gas/Water Flow Monitoring GINA board attached to stove’s flexible gas tubing X-axis acceleration is monitored at 300 Hz
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26 Respiration Heart Rate Basic Health Monitoring Acceleration data Collected from a GINA mote strapped onto the chest
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27 Footstep Localization d2d2 k(t)k(t) k(t+τ 1 ) k(t+ τ 2 ) d1d1 sensor node vibration source Waveform of a typical footstepEquivalent spectrum Where is someone walking? Use the time difference of arrival of the seismic wave generated by a footstep
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