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ABSTRACT
Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena, coupled with demands for a high spatial sampling rate in three dimensions. For example, low distortion mapping of critical solar radiation properties in forest environments may require two-dimensional spatial sampling rates of greater than 10 samples/m2 over transects exceeding 1000 m2. Clearly, adequate sampling coverage of such a transect requires an impractically large number of sensing nodes. This paper describes a new approach where the deployment of a combination of autonomous-articulated and static sensor nodes enables sufficient spatiotemporal sampling densityo ver large transects to meet a general set of environmental mapping demands. To achieve this we have developed an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variabilityin environmental phenomena discovered bythe mobile sensors and to discrete events discovered byst atic sensors. We begin byde scribing the class of important driving applications, the statistical foundations for this new approach, and task allocation. We then describe our experimental implementation of adaptive, event aware, exploration algorithms, which exploit our wireless, articulated sensors operating with deterministic motion over large areas. Results of experimental measurements and the relationship among sampling methods, event arrival rate, and sampling performance are presented.
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Jason Campbell , Phillip B. Gibbons , Suman Nath , Padmanabhan Pillai , Srinivasan Seshan , Rahul Sukthankar, IrisNet: an internet-scale architecture for multimedia sensors, Proceedings of the 13th annual ACM international conference on Multimedia, November 06-11, 2005, Hilton, Singapore
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Lynette Laffea , Russ Monson , Richard Han , Ryan Manning , Ashly Glasser , Steve Oncley , Jielun Sun , Sean Burns , Steve Semmer , John Militzer, Comprehensive monitoring of CO2 sequestration in subalpine forest ecosystems and its relation to global warming, Proceedings of the 4th international conference on Embedded networked sensor systems, October 31-November 03, 2006, Boulder, Colorado, USA
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Dustin McIntire , Kei Ho , Bernie Yip , Amarjeet Singh , Winston Wu , William J. Kaiser, The low power energy aware processing (LEAP)embedded networked sensor system, Proceedings of the fifth international conference on Information processing in sensor networks, April 19-21, 2006, Nashville, Tennessee, USA
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Richard Pon , Maxim A. Batalin , Jason Gordon , Aman Kansal , Duo Liu , Mohammad Rahimi , Lisa Shirachi , Yan Yu , Mark Hansen , William J. Kaiser , Mani Srivastava , Gaurav Sukhatme , Deborah Estrin, Networked infomechanical systems: a mobile embedded networked sensor platform, Proceedings of the 4th international symposium on Information processing in sensor networks, April 24-27, 2005, Los Angeles, California
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Guoliang Xing , Tian Wang , Weijia Jia , Minming Li, Rendezvous design algorithms for wireless sensor networks with a mobile base station, Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing, May 26-30, 2008, Hong Kong, Hong Kong, China
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Liqian Luo , Qing Cao , Chengdu Huang , Lili Wang , Tarek F. Abdelzaher , John A. Stankovic , Michael Ward, Design, implementation, and evaluation of EnviroMic: A storage-centric audio sensor network, ACM Transactions on Sensor Networks (TOSN), v.5 n.3, p.1-35, May 2009
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INDEX TERMS
Primary Classification:
I.
Computing Methodologies
I.2
ARTIFICIAL INTELLIGENCE
I.2.9
Robotics
Subjects:
Sensors
Additional Classification:
C.
Computer Systems Organization
C.2
COMPUTER-COMMUNICATION NETWORKS
C.2.4
Distributed Systems
Subjects:
Distributed applications
C.3
SPECIAL-PURPOSE AND APPLICATION-BASED SYSTEMS
J.
Computer Applications
J.7
COMPUTERS IN OTHER SYSTEMS
Subjects:
Command and control;
Process control;
Real time
General Terms:
Algorithms,
Design,
Experimentation,
Management,
Measurement,
Performance,
Reliability
Keywords:
adaptive sampling,
distributed,
mobile robotics,
sensor network,
task allocation
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