1. Deborah Estrin http://cens.ucla.edu/Estrinhttp://cens.ucla.edu/Estrin destrin@cs.ucla.edudestrin@cs.ucla.edu Work summarized here is largely that of students, staff, and other faculty at CENS We gratefully acknowledge the support of our sponsors, including the National Science Foundation, Intel Corporation, Sun Inc., Crossbow Inc., and the participating campuses. Center for Embedded Networked Sensing Update, October 2004

2. 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 Contaminant TransportEcosystems, Biocomplexity Marine Microorganisms Seismic Structure Response

3. IT Challenges: Software and Algorithms Key Constraints: Energy awareness and conservation Scaling and adaptation to variable resources and stimuli Autonomous, disconnected operation Complexity of Distributed systems Technologies: EmStar TinyOS Habitat investigation, e.g NIMS (Networked Info- Mechanical Systems) Seismic detection, analysis arrays, e.g. CENS Seismic Array NIMS Seismic Target Apps: Technology Research: Self configuring systems for autonomy in dynamic, irregular environments In Network Collaborative signal processing and Event Detection for Scaling in time and space Exploiting System Ecology, Infrastructure, Mobility Multi-mode, multi-scale data fusion for tasking and interpretation

4. CENS Research Organization Road Map

5. CENS Science Application System Drivers Biology/Biocomplexity(Hamilton, Rundel) –Robust, extensible microclimate monitoring –Image and acoustic sensing –Infrastructure based mobility Contaminant Transport (Harmon) –Three dimensional soil monitoring –Error resiliency at node and system level –Data assimilation, model development Seismic monitoring(Davis, Wallace) –Wide area, high bandwidth wireless arrays –Reliable data delivery –Time synchronization Marine microorganisms (Caron, Requicha, Sukhatme) –Aquatic operation –Micro-organism identification –Sensor driven biological sample collection

6. Inference in optical domain –CMOS technology: Low power ( capture < 40mA) –Cyclops is not imager but rather a sensor –Small picture size: Target below 256*256 Example Applications –Color estimation: Monitor triggering, Agriculture, Motion detection, Security –Low power, long term image archival: phonology Platform –Atmega128 8bit RISC PROCESSOR –512 KByte of Flash for local File system –512 KByte RAM Enough room for heavier computation Software and algorithm innovations –in-network processing of images for event detection –Limited resources, but in limited context Embedded Mote-based Imaging (Cycl o ps) Mohammad Rahimi

7. Identify and locate inter-specie and intra- specie of birds Use acoustical array to perform SNR enhancement for identification and localization Trigger imagers and human observers with solar-powered or short-term deployments Direction-of-arrival (DOA) algorithm used to calculate bearing crossings to locate bird(s) – Acoustic array based on Stargates, 802.11, Emstar software – Near-optimal Approximate Maximum- Likelihood based algorithm Sensor Arrays for Acoustic Monitoring of Bird Behavior and Diversity

8. System Ecology Including Mobility Spatially distributed static nodes Allows simultaneous sampling across study volume (dense in time, but possibly sparse in space) Limited energy and sampling rate Articulated Nodes Provide greater functionality for sensors, communications Nodes with infrastructure-based mobility: Networked Info-Mechanical Systems (NIMS) Sensor diversity: location, type, duration Allows dense sampling across transect (dense spatially, but possibly sparse in time) Adaptive provision of resources (sensors, energy, communication) Enable adaptive, fidelity-driven, 3-D sampling and sample collection

9. ENS Vision will depend upon Heterogeneous systems and In-network processing Several classes of systems: –Mote herds: Scale –Collaborative processing arrays: Sampling rate –Networked Info-Mechanical Systems: Autonomy Achieve longevity/autonomy, scalability, functionality with: –heterogeneous systems –in-network processing, triggering, actuation Algorithm/Software challenges –Characterizing and adapting to sensing uncertainty –Achieving error resiliency, integrity –Establishing statistical and information-theoretic foundations for adaptive sampling, fusion –Developing programming abstractions, Common services, tools lifetime/autonomy scale Collaborative processing arrays (imaging, acoustics) Infrastructure- based mobility (NIMS) sampling rate Mote Clusters

10. Event Detection Localization & Time Synchronization Calibration Programming Model In Network Processing Needed: Reusable, Modular, Flexible, Well-characterized Services/Tools : Routing and Reliable transport Time synchronization, Localization, Calibration, Energy Harvesting In Network Processing: Triggering, Tasking, Fault detection, Sample Collection Programming abstractions, tools Development, simulation, testing, debugging Routing and Transport Application-Driven (not Application-Specific) Common system services

11. National Ecological Observatory Network (NEON) NEON “NEON will transform ecological research by enabling studies on major environmental challenges at regional to continental scales. Scientists and engineers will use NEON to conduct real-time ecological studies spanning all levels of biological organization and temporal and geographical scales. Biogeochemical cycles Biodiversity & ecosystem functioning Climate change Freshwater resources (especially linkage to land) Infectious diseases Land use change Land use change and Material flux or processing

12. CLEANER: California regional effort A multiscale approach - San Joaquin River Basin: Water quality observation and forecasting--Sierra snowpack to San Franciso Bay Academics: UC Merced, UCLA, UCD, UCR, Caltech Govt Agencies: LLNL, LBNL, USBR, USGS, NPS, CA DWR

13. Key Accomplishments Multi-disciplinary research objectives –Cross-disciplinary teams deploying real systems--Impossible without STC infrastructure –Investigation of fundamental questions across our domains –New areas of investigation: Statistics, Data fusion (Hansen) Programming languages (Kohler) ELSI-ipercs effort (Cuff) Internal Organization: –Diversity and Education area growth –UC Merced partnership (Harmon) –NIMS Project Education –Very successful undergraduate summer research program –7-12 inquiry pilot testing –Gender-Diversity program Community/External visibility –Co-Founded and hosted ACM Sensys 2004 –Co-Founded ACM Transactions on Sensor Networks –Hosting IPSN 2005 –Soils workshop, JR Spring 2004 –Active in NEON, CLEANER planning –Advisory to NSF CISE, ENG, ERE, and NRC panels –Pottie-Kaiser, Cambridge Univ Press, Spring 2005 Technology development –Emstar continued maturity –Stargate platform support –Nitrate Sensor, LC development –NIMS Lab system Testbed deployment –NIMS prototype:Wind River and JR –Factor building data capture –JR CMS, Phenology, ESS –Contaminant deployment--Palmdale –Marine lab facility –Marine field experiments-3-mike

14. Principles of Embedded Networked Systems Design Gregory J. Pottie and William J. Kaiser Electrical Engineering Department University of California, Los Angeles Cambridge University Press Spring, 2005 Preprints in use at Yale, UMass Amherst, UCLA EE, UCLA CS

15. Broad Relevance to Global Issues Security Global Climate Change Precision Agriculture Theatre, Film, Television Coral Reef Global Seismic Grids/Facilities High Integrity Systems Adaptive Sampling NIMS Tools Embedded Imaging Programming Public Health Water Quality Early Warning, Crisis Response

16. Strong Institutional Support New CENS Building – Spring 2005 Generous Matching funds from VCR and HS-SEAS Active encouragement and support of multi-disciplinary, campus-wide activities HS-SEAS loan for building shell (6000 square feet) Currently seeking donor for shell and furnishings Excellent naming opportunity

17. Roadmap for the day 9:30-10:15 Keynote: Dr. Vinton Cerf, MCI 10:15-10:30 Break 10:30-11:30 Robotics and Actuation@CENS (Caron, Sukhatme) –Networked Info-Mechanical Systems (Kaiser) –Adaptive Sampling (Hansen) –Marine Robotics (Caron, Sukhatme) –Actuation and Communication (Browne) 11:30-12:00 Embedded sensing in the public sphere (Burke, Cuff) –Theater Film Television authoring systems and application testbed plans (Burke) –Public Sphere/Ethics (Cuff) 12:00-1:30 Lunch and Poster/Demo Sessions 1:30-3:00 Toolkits@CENS (Guy, Kohler) –Wide area, high datarate, wireless (Davis) –Emstar development tools (Girod) –Sensors for environmental monitoring (Harmon) –GUI and Data management for ecosystem monitoring (Wimbrow) –Mote clusters, Extensible Sensing System for ecosystem monitoring (Stathopoulos) –Programming tools (Kohler) 3:00-4:00 Multi-scale Integration (Hamilton, Kaiser) –Multi-scale Sampling (Pottie) –Scaling Challenges in Ecology (Rundel) –Microclimate and Ecophysiology (Graham) –Microbial and Root Ecology (Allen) –NIMS and Multi-scale Experiments (Kaiser) 4:00-5:00 Data Integrity (Harmon, Srivastava) –Error resilient sensor technology (Harmon) –In situ calibration (Potkonjak) –Integrity (Srivastava)

18. Keynote Speaker: Vinton Cerf Sr. VP of Technology and Strategy, MCI –Previously Senior VP of Architecture and Technology One of the fathers of the Internet (suggesting perhaps we need a better metaphor…) –Co-designer of TCP/IP, Internet architecture (DARPA 1976-82) Numerous awards –1997 co-recipient of US National Medal of Technology –NAE Marconi, Draper awards; IEEE Bell, Kobayashi, Sigcomm, … MS, PhD, UCLA Computer Science Department.