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Abstract

There is no currently known systematic and quantitative procedure developed to design smart workplace environments through guiding efficient and effective adoption and exploitation of the currently available wide variety of smart-environment-enabling technologies. This article presents a novel methodology to design a smart workplace environment objectively to improve, for example, productivity and safety. The proposed methodology starts by analysing the given subject workplace environment in terms of tasks and goals, and then structures and quantifies effect relations among workplace overall goals and the smart-environment-enabling technologies through linking them to the intermediate task objectives, potential improvement opportunities and smart characteristics affected by those smart technologies. Fuzzy relations are utilized to express vague effect relations among related goals, objectives, concepts and technology elements of the proposed design model. The Max–Min composition is used to compose relations to obtain the final overall goal-technology relationships. The methodology eventually yields a composed relation among workplace overall performance goals and the investigated smart-environment-enabling technologies. This overall composed relation reveals promising enabling technologies that are relevant to achievement of the specified goals. Identification of goals promising smart technologies can be used directly as a guide to realize a goal-based smart workplace environment design. Promising technology relations to task goals also help to deploy those promising technologies to the relevant tasks. A comprehensive example case is used to demonstrate the applicability of the methodology.

Keywords

Ambient intelligence smart workplace smart technologies goal-based model fuzzy relations Max–Min composition

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A novel methodology for designing smart workplace environments utilizing fuzzy relations

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