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Panoptes: Low-Power, Scalable Video Sensor Networking Technologies

Panoptes: Low-Power, Scalable Video Sensor Networking Technologies. Wu-chi Feng, Ed Kaiser, Brian Code, Mike Shea, Wu-chang Feng, Louis Bavoil Department of Computer Science and Engineering OGI School of Science and Engineering at OHSU. Motivation. Sensor networking technologies are great

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Panoptes: Low-Power, Scalable Video Sensor Networking Technologies

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  1. Panoptes: Low-Power, Scalable Video Sensor Networking Technologies Wu-chi Feng, Ed Kaiser, Brian Code, Mike Shea, Wu-chang Feng, Louis Bavoil Department of Computer Science and Engineering OGI School of Science and Engineering at OHSU

  2. Motivation • Sensor networking technologies are great • Real-time in situ measurement of environments • Habitat monitoring (UCLA) • Columbia River forecasting (OGI) • REINAS Monterey Bay system (UC Santa Cruz) • Artic web cam (NOAA) • Video sensor networking technologies • Can add eyes to sensor data • Require significant computing and bandwidth resources beyond traditional sensor technologies

  3. Motivation • The applications • Environmental monitoring • Example: Video sensor every ¼ mile along the entire Oregon coast • Health care delivery • Example: Privacy ensuring elderly health care • Emergency response • Habitat monitoring • Surveillance and security • Robotics

  4. Motivation • Video sensor networking challenges • Low-power, power-aware video sensors • PoE applications • Environmental / autonomous deployment • Providing mechanisms that allow the sensor network to be tailored to specific applications • “Programmability” • Managing information implosion (N  1) • Buffering and adaptation • Making it easy to access both traditional scalar and video data within the sensor network

  5. The Panoptes Project at OGI • The goal: • Flexible, extensible middleware that supports massively scalable video-based sensor networks • Short term • Low-power, programmable, adaptable, video sensor for experimental testbed • Buffering and adaptation algorithms for sensor • Bringing together a large number of flows • Longer term • Integration of traditional low-power sensors with video sensors • Application-specific extensions

  6. The Rest of This Talk • The Panoptes platform • Hardware and software systems • Software architecture • Experimentation • A demonstration system • The Little Sister Sensor Networking Application • Conclusions and future work

  7. 206 MHz Intel StrongArm USB-based video 802.11 wireless Embedded Linux The Panoptes Platform • Picking a platform • Berkeley Motes • COTS web cameras • General embedded CPU platforms 320x240 video 22 fps software compressed ~5.5 Watts maximum

  8. The Panoptes Platform Video Sensor Architecture Compression IPP-based Currently: JPEG, Diff JPEG, Cond. Replenishment Buffering and Adaptation Supports disconnected or intermittent operation Priority mapping of streaming data elements Application-Specific Filtering Event-detection Time-elapsed images Computer vision Video 4 Linux Time Power Management

  9. Sensor streaming • Inverse multicast • Any data might be good • Some data unknown a priori • Buffering can be used Buffering and Adaptation • Sensor streaming is different than video streaming today • Live streaming • Late data useless • Data unknown a priori • Limited use of buffering in adaptation • Video-on-demand streaming • Just in time delivery • All data known a priori • Streaming can take advantage of known data • Buffering useful How long to keep data in the sensor buffer? How do you prioritized data between new/old?

  10. Experimentation • The USB bottleneck • Compression performance on Panoptes • Buffering and adaptation performance • Power measurements

  11. USB Capture Performance

  12. USB Capture Performance 6.9 Mbps

  13. USB Capture Performance 111 Mbps

  14. USB Capture Performance 27.6 Mbps

  15. Software Compression Performance

  16. Capture / Compression Performance

  17. Buffering and Adaptation

  18. Camera on/ net. connected All services running Camera on (capturing) CPU loop System Idle Standby Network connected Camera standby Power Consumption

  19. A Demonstration System • The Little Sister Sensor Networking Application Network Network Query Manager Stream Manager Camera Manager(s)

  20. Future Work • Python-based experimentation • Power management • Developing a smaller (more stable) platform • Finding suitable radio technology to match applications • Making the access to video sensor data more useful • Integration with traditional sensor technologies • TinyDB for video sensors

  21. Conclusions • Low-power video sensor networking technologies • Video sensor software design • Dynamically adaptable software architecture • Disconnected or intermittent operation • More information • www.cse.ogi.edu/sysl

  22. http://www.cse.ogi.edu/sysl More information?

  23. The Rest of This Talk • The Panoptes platform • Hardware and software systems • Software architecture • A demonstration system • The Little Sister Sensor Networking Application • Experimentation • System measurements • Buffering and adaptation • Power consumption • Conclusions and future work

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