A multi-attribute utility decision support tool for a smart campus—UAE as a case study

Abstract

The advancement in technologies in the education sector has improved living standards and acts as a sustaining factor for future development. Recently, the integration of technologies into the campus to transform it into a Smart Campus has experienced exponential growth in interest from researchers. Though various definitions of the concept of ‘Smart Campus’ have been proposed, the integration of the end users’ perception is always lacking in the concept. This study, therefore, intends to build on the theory to classify the most significant criteria that underpin the ‘Smart Campus’ by considering the institute’s stakeholders’ perceptions. A multi-step methodological approach is adopted to develop a decision support tool that allows the decision makers to invest in the optimum solution to transform a traditional campus into a smart campus. The study initially looks into the criteria and sub-criteria from the literature that defines a ‘Smart Campus’. Secondly, a survey was conducted by targeting a sample of students, faculty, administrative staff, and IT support personnel from a leading institute in the UAE region as a single case study. Thirdly, an AHP analysis was performed among different stakeholders. The findings suggested that there exists a consensus among the perception of a diverse group of participants who perceive smart security and safety, campus navigation, and adaptive learning as the most important criteria and applications to transform the traditional campus into a smart campus. Finally, the decision support tool development on the Utility function model allows the decision makers, i.e., Network Managers, IT Managers, Systems and Cloud Managers, and Senior Managers from the Finance departments, to make informed and strategic decisions in terms of the optimum solution for the transformation from a traditional campus to a smart campus.

Examining IoT-Based Smart Campus Adoption Model: An Investigation Using Two-Stage Analysis Comprising Structural Equation Modelling and Artificial Neural Network

“…Other studies propose the criteria and indicators for successful smart campus initiatives [54]- [59]. There is an extensive literature on the theoretical or conceptual framework for smart campuses [56], [60]- [63], and utilizing multi-decision criteria to investigate the factors for smart campuses [27], [64], [65]. Specifically, several studies, e.g., [42], [66], have explored the implementation of IoT in the educational sector.…”

“…The concept of a campus edge computing network, using elements such as street lighting as IoT communication nodes, has gained traction in recent research [43]. Similarly, some existing papers, e.g., [44], [64], emphasize the importance of robust data acquisition, management, and storage systems in smart campuses. Additionally, addressing semantic interoperability issues is a critical aspect of IoT-enabled smart campuses, as highlighted by Ref.…”

“…Investigation using AHP [64] This study defines criteria for a 'Smart Campus' using AHP analysis with input from students, faculty, administrative staff, and IT support personnel at a UAE-based institute. The study ultimately developed a decision support tool based on the Utility function model to assist decision-makers in choosing the optimal solution for smart campus transformation.…”