Evaluating average causal effect using wireless sensor networks

TitleEvaluating average causal effect using wireless sensor networks
Publication TypeConference Proceedings
Year of Publication2004
AuthorsCoates, M. J., and I. Psaromiligkos
Conference NameIEEE ICASSP
Date Published05/2004
Conference LocationMontreal, QC, Canada

Sensor networks have exciting potential applications in agriculture and medicine, where after the application of treatment, it is beneficial not merely to track the response but to assess the causal impact of the treatment reception. We describe a distributed algorithm for the evaluation of the average causal effect of treatment reception upon response. Our procedure applies the expectation-maximization algorithm across a graphical model of the system, using local message-passing techniques. The key collaborative step in the algorithm is simple message aggregation and averaging, which we perform over a tree network topology. Finally, for completeness purposes, we describe a simple framework for the construction and maintenance of the tree topology that provides a robust mechanism for executing the algorithm using spread-spectrum or ultra-wideband communication.

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