A Learning-Theory Approach to Sensor Networks

  title={A Learning-Theory Approach to Sensor Networks},
  author={Slobodan N. Simic},
  journal={IEEE Pervasive Computing},
R ecent advances in microelectromechanical systems, computing, and communication technology have sparked the emergence of massively distributed, wireless sensor networks with potentially thousands of nodes. Each node can sense the environment, process the collected data, and communicate with its peers or to an external observer. A steady increase in these networks’ capabilities and decrease in the cost of producing them have made possible applications that seemed too expensive or unrealistic.1… CONTINUE READING
Highly Cited
This paper has 99 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 40 extracted citations

Locating the nodes: cooperative localization in wireless sensor networks

IEEE Signal Processing Magazine • 2005
View 15 Excerpts
Highly Influenced

Distributed regression over sensor networks: An support vector machine approach

2008 IEEE/RSJ International Conference on Intelligent Robots and Systems • 2008
View 3 Excerpts
Highly Influenced

Distributed probability density function estimation of environmental function from sensor network data

2013 International Conference on Signal Processing , Image Processing & Pattern Recognition • 2013

Joint detection and tracking of boundaries using cooperative mobile sensor networks

2013 IEEE International Conference on Robotics and Automation • 2013
View 1 Excerpt

Predictive Modeling of Time-Varying Environmental Information for Path Planning

2013 IEEE International Conference on Systems, Man, and Cybernetics • 2013
View 1 Excerpt

99 Citations

Citations per Year
Semantic Scholar estimates that this publication has 99 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 10 references

Similar Papers

Loading similar papers…