Abstract
Smart environments have proven very supportive to the improvement of the performance of people in different workplaces. Plenty of applications have been introduced spanning different settings including healthcare, ambient assisted living, homes, offices, and manufacturing environment, etc. However, subjectivity and ambiguity prevail in the majority of research, and still, up to date, rare approaches found quantitatively and objectively constructing or assessing the impact of smart enabling technologies on the performance of the subject environment. Further, no approaches have considered optimizing the adoption of those smart technologies with respect to objectives achievement. This article presents a novel optimization methodology for designing a smart workplace environment in conditions of ambiguity or fuzziness. The methodology begins with defining and weighing the overall goals and objectives of the workplace. The Prometthe multi-criterion decision-making technique is used to weigh the operational objectives with respect to the overall workplace goals. Next, the relation among basic building blocks of the model; namely: the operational objectives, smartness features, and smart enabling technologies are quantified, utilizing fuzzy relations. Then, the fuzzy goal programming techniques will be utilized to optimize the impact relation values while considering the budget constraint. The proposed optimization methodology is implemented on the development and optimization of the smart clinic, as a typical instance of the workplace.
Highlights
Smart enabling technologies represent the major fundamental building blocks of the smart environment application
The smart workplace environment is logically built around three basic model building blocks: The smart enabling technologies (SETs): sensors, actuators, microcontrollers, and other basic software and hardware constituents that shall be installed in the workplace environment, such as offices, industrial plants, hospitals, etc
Currently, there is a lack of systematic optimization procedures for developing smart environments
Summary
Smart enabling technologies represent the major fundamental building blocks of the smart environment application. Zhao et al (2021) [9] implemented a network of physical sensors and a closed control loop to optimize an office workplace environment They applied two modes of control involving learning from user responses and the other was based on predefined rules sets. Bansal and Gandhi (2019)[14] emphasized the role of utilizing IoT together with Big Data technologies in transmitting ECG sensors data from the patient to the doctors and other concerned persons for effective and efficient smart health monitoring. Section four presents the proposed methodology for optimizing the design of a workplace utilizing three techniques: the multi-criterion decision-making tool, PROMETHEE, fuzzy relations, and fuzzy goal programming.
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