1 / 15

Center for Embedded Networked Sensing Sustainable Large-Scale Sensor Networks

Center for Embedded Networked Sensing Sustainable Large-Scale Sensor Networks. Greg Pottie Deputy Director, CENS Professor, UCLA Electrical Engineering Dept.

schumaker
Download Presentation

Center for Embedded Networked Sensing Sustainable Large-Scale Sensor Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Center for Embedded Networked Sensing Sustainable Large-Scale Sensor Networks Greg Pottie Deputy Director, CENS Professor, UCLA Electrical Engineering Dept. We gratefully acknowledge the support of our sponsors, including the National Science Foundation, Intel Corporation, Sun Inc., Crossbow Inc., and the participating campuses.

  2. Mission Statement • To address scientific issues of national and global priority through pioneering research and education in Embedded Networked Sensing technology. • To develop and demonstrate architectural principles and methodologies for deeply embedded, massively distributed, sensor-rich distributed systems • To apply and disseminate these systems in support of scientific research critical to social and environmental concerns • To create meaningful inquiry-based science instruction using embedded networked sensing technology, for a diverse grade 7-12 population; and to disseminate education materials and technology through outreach and professional development networks

  3. Embedded Networked Sensing • Micro-sensors, on-board processing, wireless interfaces feasible at very small scale--can monitor phenomena “up close” • Enables spatially and temporally dense environmental monitoring Embedded Networked Sensing will reveal previously unobservable phenomena Ecosystems, Biocomplexity Contaminant Transport Marine Microorganisms Seismic Structure Response

  4. Development of New Embedded Sensors • CENS-compatible chemical-sensor technologies needed • soil/water quality monitoring, security, precision agriculture • Current chemical-sensor development • electrochemical nitrate sensors:potentiometric orchronocoulometry • MEMS liquid chromatography systems and mass spectrometers

  5. Nitrate Sensor Development Target molecule Fluid Contaminant Transport Group • Potentiometric nitrate sensor: Detection limits ppm • amperometric nitrate sensor: Detection limits ppb • LC-on-a-chip: separation and identification of ions • surface plasmon resonance: ultra-sensitive short term medium term long term

  6. Error Resilient Contaminant Monitoring Sensor network error resiliency in complex media (air-water-soil) • Working in the context of a real problem in Palmdale, CA • partnering with LA County Sanitation District • Real-time analysis instead of “logging” • model calibration, forecasting

  7. Wide Area Contaminant Transport Monitoring Larger scale, multimedia problems • Linking remote and in situ sensing over multiple scales • Complete watershed • Management, visualization, exploration of massive, heterogeneous data streams • NSF CLEANER Initiative

  8. Sensor-Coordinated Mobility Networked Info-Mechanical Systems (NIMS) • NIMS Architecture: Robotic, aerial access to full 3-D environment; enables • sample acquisition • self-awareness of obstacles • reconfiguration of sensors to calibrate and reduce model uncertainty • NIMS Infrastructure • Enables speed, efficiency • Provides energy transport for sustainable presence

  9. Infrastructure for Sustained Observations • Infrastructure enables sustained surveillance or study • Logistics are vastly simplified • Easy to install even in early generations • Continuous operation since late March

  10. Data Management Contaminant Transport Group • Multimedia, Multiscale problems (time and space) • Physical world can generate infinite data • Management, visualization, exploration of massive, heterogeneous data streams • Data integrity issues • Few standards and discipline/problem specific • We will develop data management tools that enable many different types of users to access the same basic data • Engineers, scientists, teachers, students • Extensibility for new applications, security technology

  11. New Directions Science Applications Security Precision Agriculture Global seismic Grids/facilities Tropical biology Theatre,Film,TV Coral reef Gaming Macro-Programming Adaptive Sampling RFIDs Bayesian Techniques High Integrity NIMS

  12. RoboGaming Graphic Projector Localization Camera • Real agent motion: beyond computer graphics • Play with autonomous robots and reconfigurable structures • Physical capabilities and constraints replace simulated effects • game more interesting Graphical play authoring tool PicoNIMS Terrain Control Energy Replenishment Autonomous Mobile agents Game Server Reconfigurable Terrain Distributed Audio Engine

  13. ENS: Revolutionary tool for basic science • Environmental science • Global warming, watershed management, effects of human activity on particular environments (including farms/forests) • Better public policy, improved farm/forest management, more efficient use of water resources • Contaminants monitoring • Air, soil, water; can bring physical samples to biochem analysis engines • Improved public health, potential for lower cost remediation • Earth Science • Study of seismic activity at multiple scales • Ground/structure interactions for improved building codes

  14. ENS: Broad set of applications • Interactive public spaces • Interactive games and other entertainment experiences • Automation of retail and many other service functions • Industrial • Automated tracking using RFID • Medical • Remote medical monitoring; better diagnosis, reduced cost • Security • Borders, urban areas, homes; automated surveillance raises large privacy concerns • Education/public awareness • Physical world as set of www sites; individuals with information resources of governments will have profound regulatory consequences

  15. Conclusions • Connection of physical world to computer networks will have profound societal consequences • Adding actuation enables remote control • Tools developed for basic science investigation will result not only in new science but support for other applications • Robustness, sustainability, data management, platform and software architecture issues are similar • Now is the time to consider regulatory regime • Changes to assure desired societal outcomes become increasingly expensive after systems are widely deployed

More Related