Paper Info
Title
An ambient intelligence architecture for extracting knowledge from distributed sensors
Abstract
Precisely monitoring the environmental conditions is an essential requirement for AmI projects, but the wealth of data generated by the sensing equipment may easily overwhelm the modules devoted to higher-level reasoning, clogging them with irrelevant details. The present work proposes a new approach to knowledge extraction from raw data that addresses this issue at different levels of abstraction. Wireless sensor networks are used as the pervasive sensory tool, and their computational capabilities are exploited to remotely perform preliminary data processing. A central intelligent unit subsequently extracts higher-level concepts represented in a geometrical space and carries on symbolic reasoning based on them. The same tiered architecture is replicated in order to provide further levels of abstraction.
Year
DOI
Venue
2009
10.1145/1655925.1655945
Int. Conf. Interaction Sciences
Keywords
Field
DocType
symbolic reasoning,different level,preliminary data processing,ambient intelligence architecture,computational capability,central intelligent unit,environmental condition,extracts higher-level concept,raw data,essential requirement,ami project,wireless sensor network,data processing,wireless sensor networks,knowledge extraction,ambient intelligence
Data mining,Architecture,Data processing,Symbolic reasoning,Abstraction,Computer science,Ambient intelligence,Knowledge management,Raw data,Knowledge extraction,Wireless sensor network,Distributed computing
Conference
Citations 
PageRank 
References 
7
0.56
10
Authors
4
Name
Order
Citations
PageRank
Alessandra De Paola114116.81
Salvatore Gaglio266088.41
Giuseppe Lo Re333841.26
Marco Ortolani420921.31