A sensory grammar for inferring behaviors in sensor networks

TitleA sensory grammar for inferring behaviors in sensor networks
Publication TypeConference Papers
Year of Publication2006
AuthorsLymberopoulos D, Ogale AS, Savvides A, Aloimonos Y
Conference NameProceedings of the 5th international conference on Information processing in sensor networks
Date Published2006///
Conference LocationNashville, Tennessee, USA
ISBN Number1-59593-334-4
Keywordsalgorithms, behavior identification, human activity, human factors, pcfg, real-time and embedded systems, sensor grammars, sensor networks

The ability of a sensor network to parse out observable activities into a set of distinguishable actions is a powerful feature that can potentially enable many applications of sensor networks to everyday life situations. In this paper we introduce a framework that uses a hierarchy of Probabilistic Context Free Grammars (PCFGs) to perform such parsing. The power of the framework comes from the hierarchical organization of grammars that allows the use of simple local sensor measurements for reasoning about more macroscopic behaviors. Our presentation describes how to use a set of phonemes to construct grammars and how to achieve distributed operation using a messaging model. The proposed framework is flexible. It can be mapped to a network hierarchy or can be applied sequentially and across the network to infer behaviors as they unfold in space and time. We demonstrate this functionality by inferring simple motion patterns using a sequence of simple direction vectors obtained from our camera sensor network testbed.