@book{JRC35112,
	editor = {},
	address = {Washington (United States of America)},
	year = {2006},
	author = {Lombardi P and Cantoni V and Lombardi L},
	isbn = {},
	abstract = {The way of collecting sensor data will face a revolution when the newly developing technology of distributed sensor networks becomes fully functional and widely available. Smart sensors will acquire full interconnection capabilities with similar devices, so that run-time data aggregation, parallel computing, and distributed hypothesis formation will become reality with off-the-shelf components and sensor boards. This revolution started around ten years ago, and now hardware and network are converging on the first convincing solutions. Exploring and exploiting this paradigm are a renovated challenge for the pattern recognition and data mining community. This paper attempts a survey on state-of-the-art of wireless sensor technology, with an eye on data-related problems and technological limits. Although the possibilities seem promising, the today limited computational resources of individual nodes hamper the elaboration of data with recent, computationally-intensive algorithms. New software paradigms must be developed, both creating new techniques or adapting, for network computing, old algorithms of earlier ages of computing.
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		},
	title = {Challenges for Data Mining in Distributed Sensor Networks},
	url = {},
	volume = {},
	number = {},
	journal = {},
	pages = {1000-1007},
	issn = {},
	publisher = {IEEE Computer Society},
	doi = {}
}