Dynamic Spatial Context Computation for Time-Varying Process Scenarios

Abstract

There are many real life processes whose smart control requires processing context information. Though the issue of processing varying context information has been addressed in the literature, domain independent solutions that can support reasoning and decision making according to time-varying
process scenarios in multiple application fields are scarce. This paper proposes a method for dynamic context computation concerning spatial and attributive information. Context is interpreted as a body of information dynamically created by a pattern of entities and relationships over a history of situations. Time is conceived as a causative force capable of changing situations, and acting on people and objects. The invariant and variant spatial information is captured by a two-dimensional spatial feature representation matrix. The time-dependent
changes in the context information are computed based on a dynamic context information management hyper-matrix. This humble but powerful representation lends itself to a quasi-real time computing and is able to provide information about foreseeable happenings over multiple situations. The paper uses the practical case of evacuation of a building in fire both as an explorative case for conceptualization of the functionality of the computational mechanism and as a demonstrative and testing application. Our intention is to use the dynamic context computation mechanism as a kernel component of a reasoning
platform for informing cyber physical systems.