Enhanced Data Driven Decision Support

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Published Jun 30, 2018
Chris Rijsdijk Tiedo Tinga

Abstract

As items are increasingly being equipped with sensors, the applicability of data driven decision support may similarly grow. This paper surveys an endeavor to support decisions with sensor recordings that were not primarily installed to support decisions. To become meaningful decision support, these sensor recordings should enable better causal inferences because decisions should cause the future.

Data driven decision support is not evident as normative decision theory is known to suffer from validation issues. This work attempts to alleviate concerns about (i) the assessment of preference, about (ii) causal inferences from non-experimental data and about (iii) the assessment of the uncertainty about the prospective outcome of a decision. This work argues that sensor recordings may appear to be appreciable decision support by presenting some typical cases of human recorded events that were enriched with sensor recordings.

How to Cite

Rijsdijk, C., & Tinga, T. (2018). Enhanced Data Driven Decision Support. PHM Society European Conference, 4(1). https://doi.org/10.36001/phme.2018.v4i1.409
Abstract 908 | PDF Downloads 718

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Keywords

Causal inferences, Decision theory, Prognostics

Section
Technical Papers