Towards a Context-Aware and Adaptable Room System for Intelligent "Trusted" Office-Spaces in Smart Cities

Abstract

This visionary paper outlines a future intelligent building office space room system that seeks to ensure that the users of a rent able and/or shared office space do not perform actions that are likely to compromise IT security. We propose that a novel room agent leverages the emergent"smart" city paradigm so as to form an accurate a measure as possible of the trustworthiness of the human agents using the office space. Namely, by leveraging pervasive urban sensors embedded in a smart city built environment, data obtained by crowd sourcing as well as data gathered via Web 2.0. Human actions detected within the room itself and its immediate environs, together with the behavioural traces and patterns of a given individual embedded within a smart city context, can be used to calculate a measurable confidence trust level. We suggest that the use of a Linking Open (or object) Data (LOD) publishing approach can be used to integrate trust related distributed data in a collective and intelligent manner. Furthermore, we suggest the use of cloud diagram and tree map visualisation approaches to depict individual and environs trust levels at both coarse and fine grain levels. To achieve this, we illustrate the approach using a low-level architecture model. We then conclude by outlining our theoretical lightweight trust model which aims to demonstrate how a smart city in general and a smart space in particular can provide an increased level of trust visualisation for it's citizens, through collective intelligence gathering.