Summary Alan S. Willsky SensorWeb MURI Review Meeting September 22, 2003.

Slides:



Advertisements
Similar presentations
Some Reflections on Augmented Cognition Eric Horvitz ISAT & Microsoft Research November 2000 Some Reflections on Augmented Cognition Eric Horvitz ISAT.
Advertisements

1 NEST New and emerging science and technology EUROPEAN COMMISSION - 6th Framework programme : Anticipating Scientific and Technological Needs.
Robot Sensor Networks. Introduction For the current sensor network the topography and stability of the environment is uncertain and of course time is.
1 Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor Networks Johnsen Kho, Long Tran-Thanh, Alex Rogers, Nicholas.
1 Sensor Networks and Networked Societies of Artifacts Jose Rolim University of Geneva.
Decentralized Data Fusion and Control in Active Sensor Networks Alexei Makarenko, Hugh Durrant-Whyte Christian Potthast.
1 SAFIRE Project DHS Update – July 15, 2009 Introductions  Update since last teleconference Demo Video - Fire Incident Command Board (FICB) SAFIRE Streams.
1 Graphical Models in Data Assimilation Problems Alexander Ihler UC Irvine Collaborators: Sergey Kirshner Andrew Robertson Padhraic Smyth.
Probabilistic Aggregation in Distributed Networks Ling Huang, Ben Zhao, Anthony Joseph and John Kubiatowicz {hling, ravenben, adj,
Compressed Sensing for Networked Information Processing Reza Malek-Madani, 311/ Computational Analysis Don Wagner, 311/ Resource Optimization Tristan Nguyen,
Summary and Closing Remarks Farrokh Najmabadi University of California San Diego Presentation to: ARIES Program Peer Review August 18, 2000 UC San Diego.
Location Estimation in Sensor Networks Moshe Mishali.
CS 599 Intelligent Embedded Systems1 Adaptive Protocols for Information Dissemination in Wireless Sensor Networks W.R.Heinzelman, J.kulik, H.Balakrishnan.
8/22/20061 Maintaining a Linked Network Chain Utilizing Decentralized Mobility Control AIAA GNC Conference & Exhibit Aug. 21, 2006 Cory Dixon and Eric.
Uncertainty Quantification and Visualization: Geo-Spatially Registered Terrains and Mobile Targets Suresh Lodha Computer Science, University of California,
A Decentralised Coordination Algorithm for Mobile Sensors School of Electronics and Computer Science University of Southampton {rs06r2, fmdf08r, acr,
Uncertainty Processing and Information Fusion for Visualization Pramod K. Varshney Electrical Engineering and Computer Science Dept. Syracuse University.
Collaborative Localization and Tracking in Wireless Sensor Networks Dr. Xinrong Li Department of Electrical Engineering University of North Texas
Optimal Placement and Selection of Camera Network Nodes for Target Localization A. O. Ercan, D. B. Yang, A. El Gamal and L. J. Guibas Stanford University.
Decentralised Coordination of Mobile Sensors School of Electronics and Computer Science University of Southampton Ruben Stranders,
1 Decentralized Jointly Sparse Optimization by Reweighted Lq Minimization Qing Ling Department of Automation University of Science and Technology of China.
Presented by: Chaitanya K. Sambhara Paper by: Maarten Ditzel, Caspar Lageweg, Johan Janssen, Arne Theil TNO Defence, Security and Safety, The Hague, The.
Activity 1: Multi-sensor based Navigation of Intelligent Wheelchairs Theo Theodoridis and Huosheng Hu University of Essex 27 January 2012 Ecole Centrale.
Multiple-access Communication in Networks A Geometric View W. Chen & S. Meyn Dept ECE & CSL University of Illinois.
Conference Paper by: Bikramjit Banerjee University of Southern Mississippi From the Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence.
Domestic Nuclear Detection Office (DNDO) NITRD Workshop What are the Biggest Opportunities in Networking Problem? Sept. 20, 2012 Timothy Ashenfelter, PhD.
An algorithm for dynamic spectrum allocation in shadowing environment and with communication constraints Konstantinos Koufos Helsinki University of Technology.
Tufts Wireless Laboratory School Of Engineering Tufts University “Network QoS Management in Cyber-Physical Systems” Nicole Ng 9/16/20151 by Feng Xia, Longhua.
NSF Critical Infrastructures Workshop Nov , 2006 Kannan Ramchandran University of California at Berkeley Current research interests related to workshop.
Michael Murphy, Huthasana Kalyanam, John Hess, Vance Faber, Boris Khattatov Fusion Numerics Inc. Overview of Current Research in Sensor Networks and Weather.
MURI: Integrated Fusion, Performance Prediction, and Sensor Management for Automatic Target Exploitation 1 Optimal, Robust Information Fusion in Uncertain.
Location Centric Distributed Computation and Signal Processing Parmesh Ramanathan University of Wisconsin, Madison Co-Investigators:A. Sayeed, K. K. Saluja,
Value of Information 1 st year review. UCLA 2012 Kickoff ARO MURI on Value-centered Information Theory for Adaptive Learning, Inference, Tracking, and.
Patch Based Mobile Sink Movement By Salman Saeed Khan Omar Oreifej.
1 st INFASA Symposium and Workshop Synthesis March 16 and 17, 2006 Bern, Switzerland As presented at the Symposium and Workshop by Dr. Fritz Häni, SHL.
1 NEST New and emerging science and technology EUROPEAN COMMISSION - 6th Framework programme : Anticipating Scientific and Technological Needs.
Distributed State-Estimation Using Quantized Measurement Data from Wireless Sensor Networks Li Chai with Bocheng Hu Professor College of.
1 SATWARE: A Semantic Middleware for Multi Sensor Applications Sharad Mehrotra.
MURI: Integrated Fusion, Performance Prediction, and Sensor Management for Automatic Target Exploitation 1 Dynamic Sensor Resource Management for ATE MURI.
Energy-Efficient Signal Processing and Communication Algorithms for Scalable Distributed Fusion.
Detection, Classification and Tracking in a Distributed Wireless Sensor Network Presenter: Hui Cao.
Approximate Dynamic Programming Methods for Resource Constrained Sensor Management John W. Fisher III, Jason L. Williams and Alan S. Willsky MIT CSAIL.
Communication Support for Location- Centric Collaborative Signal Processing in Sensor Networks Parmesh Ramanathan University of Wisconsin, Madison Acknowledgements:K.-C.
Problem Wensheng Zhang, Dr. Guohong Cao, and Dr. Tom La Porta Example: Battlefield Surveillance Challenges Small Sensing Range Limitations in sensor nodes.
High-integrity Sensor Networks Mani Srivastava UCLA.
Dr. Sudharman K. Jayaweera and Amila Kariyapperuma ECE Department University of New Mexico Ankur Sharma Department of ECE Indian Institute of Technology,
Multiuser Receiver Aware Multicast in CDMA-based Multihop Wireless Ad-hoc Networks Parmesh Ramanathan Department of ECE University of Wisconsin-Madison.
MURI Telecon, Update 7/26/2012 Summary, Part I:  Completed: proving and validating numerically optimality conditions for Distributed Optimal Control (DOC)
Analyzing wireless sensor network data under suppression and failure in transmission Alan E. Gelfand Institute of Statistics and Decision Sciences Duke.
QR Decomposition: Demonstration of Distributed Computing on Wireless Sensor Networks By Sherine Abdelhak, Soumik Ghosh, Rabi Chaudhuri, Magdy Bayoumi (A)
Workshop: Food, Energy and Water Nexus in Sustainable Cities Beijing October 20-21, 2015 Nada Marie Anid, Ph.D. Dean School of Engineering and Computing.
DISTIN: Distributed Inference and Optimization in WSNs A Message-Passing Perspective SCOM Team
SensorWeb Data Fusion in Large Arrays of Microsensors MURI Review Meeting Introduction/Overview Alan S. Willsky September 22, 2003.
Adaptive Tracking in Distributed Wireless Sensor Networks Lizhi Yang, Chuan Feng, Jerzy W. Rozenblit, Haiyan Qiao The University of Arizona Electrical.
1 Power to the Edge Agility Focus and Convergence Adapting C2 to the 21 st Century presented to the Focus, Agility and Convergence Team Inaugural Meeting.
Energy-Efficient Signal Processing and Communication Algorithms for Scalable Distributed Fusion.
Thrust IIB: Dynamic Task Allocation in Remote Multi-robot HRI Jon How (lead) Nick Roy MURI 8 Kickoff Meeting 2007.
Breakout Group 1 Summary NSF workshop on Bridging the Gap between Wireless Networking Technologies at the Physical Layer Aug
MIT Lincoln Laboratory Dynamic Declarative Networking Exploiting Declarative Knowledge To Enable Energy Efficient Collaborative Sensing Daniel J. Van Hook.
Kalman Filter and Data Streaming Presented By :- Ankur Jain Department of Computer Science 7/21/03.
Machine Reasoning and Learning Workshops III and IV Kickoff Wen Masters Office of Naval Research Code 311 (703)
Mohsen Riahi Manesh and Dr. Naima Kaabouch
SENSOR FUSION LAB RESEARCH ACTIVITIES PART I : DATA FUSION AND DISTRIBUTED SIGNAL PROCESSING IN SENSOR NETWORKS Sensor Fusion Lab, Department of Electrical.
MURI Annual Review Meeting Randy Moses November 3, 2008
Introduction to the ISO 9000 “Family” Quality Management Standards
≠ Particle-based Variational Inference for Continuous Systems
A Guide to the Sharing Information on Progress (SIP)
Information Sciences and Systems Lab
Closing Remarks.
Presentation transcript:

Summary Alan S. Willsky SensorWeb MURI Review Meeting September 22, 2003

An Update to the 2.5-Year Summary Last year’s review provided a complete picture of the state of this MURI Scientific achievement Fulfilling the intellectual agenda outlined in our proposal Achieving objectives of MURI programs Interdisciplinary and synergistic research Community leadership and influence Responsiveness to EAC/TAB and contributions to critical DoD S&T challenges The following is a brief update, based on what has been presented in the previous talks

Fulfilling the intellectual agenda outlined in our proposal We have maintained course along all three intellectual themes defined in our proposal Focus primarily on intellectual “long-poles” Maintaining relevance to and coverage of the RCA’s, We continue to have considerable success Major research results Recognition of our work by the broader community

A Sampling of Recent Accomplishments & Activities New, robust methods for source localization with sensor arrays New methods with enhanced robustness to noise and uncertainty Well-adapted to signal structures arising in applications of central interest to the Army but which previous methods have not addressed (e.g., multiband sources) Ongoing interaction with ARL to maintain and enhance relevance and impact of this work, e.g. Distributed sources Sources with harmonic structure

Sampling - II Fusion of heterogeneous sensors Robust information-theoretic methods for multisensor fusion New approaches for Estimating information measures Overcoming combinatorial explosion of data association Initiation of ARL collaboration via extended visit by Alex Ihler Multisensor association,fusion and exploitation Marriage of received signal strength work of Sadler/Pham and our NBP methods New information-theoretic approach to sensor management and querying in networked environments

Sampling - III Network-constrained fusion Exploitation of embedded tractable structures Embedded tree algorithms Extended message passing algorithms Tree-reweighting optimization Extension of particle filtering to networks Collaboration with CTA-funded research (Moses-OSU) on source and sensor localization Applications to distributed data association Investigation of performance/communication tradeoff Newly initiated formulation capturing simple proximity sensor models New approach using particle filters avoiding data association complexity completely

Sampling - IV Methods and guarantees for exploiting heterogeneous sensors Principles, methods, and guarantees for estimation, association and discrimination Collaborative use of fragmented data Dynamic, adaptive resource allocation with performance guarantees PAC-learning-based approach to bounds on number of information queries required to make decision/estimate with specified level of confidence Universal prediction approach to sequential resource allocation with application to energy management in wireless networks

Sampling - V Information transfer in wireless networks for distributed sensing and control Problems at the interface of sensing, inference, communication, and computation Results on harvesting statistics from sensor networks: relating fusion rate to network strategies Optimal use of energy-limited nodes in networks with fading channels

Sampling - VI Integrated approaches to communications- constrained fusion Intelligent querying of sensors for localization and tracking of targets Transitioned through SensIT program Continuing collaboration (through Dr. M Chu, now at PARC) Initiation of new effort in distributed fusion Blending concepts from decentralized detection and graphical models Anticipated collaboration with Prof. P. Varshney (involved in the Battlefield Visualization MURI) Already have uncovered major conceptual issues

Sampling - VII Recognition of our work continues New plenary and invited talks Numerous papers and theses We continue to strengthen our interactions with other research activities Decision-making under uncertainty MURI Battlefield visualization MURI Sensors CTA

Sampling - VIII We continue to respond conscientiously to the mission of MURI research Responsiveness to EAB/TAC comments See previous talks Continued and enhanced interactions with ARL (both directly and through collaborative research with those involved in CTAs)