The increasing complexity of academic institutions demands intelligent and data-driven governance frameworks capable of supporting strategic planning, resource optimization, and operational efficiency. Integration of Internet of Things (IoT) technologies with Decision Support Systems (DSS) provides a transformative approach for real-time data acquisition, analysis, and actionable insight generation across classrooms, laboratories, administrative units, and campus facilities. This chapter presents a comprehensive framework for IoT-enabled DSS, emphasizing predictive and prescriptive analytics, scenario modeling, and resource optimization to enhance institutional planning and academic governance. Real-time monitoring of student engagement, faculty performance, and facility utilization enables proactive decision-making, reduces operational inefficiencies, and ensures evidence-based policy implementation. The study further explores challenges related to data privacy, interoperability, scalability, and cybersecurity, while providing strategic guidelines for successful deployment in higher education environments. The integration of IoT and DSS aligns with the principles of Industry 5.0, fostering human-centric governance, sustainable operations, and adaptive learning ecosystems. This chapter contributes to advancing smart campus initiatives and establishing a foundation for intelligent, responsive, and future-ready academic governance.
Modern academic institutions operate in increasingly complex and dynamic environments, driven by rapid technological advancements, evolving educational standards, and growing student populations [1]. Traditional approaches to institutional governance and resource management rely heavily on manual processes, static reporting, and retrospective analysis. Such methods are often inefficient, time-consuming, and unable to provide real-time insights required for effective planning [2]. The proliferation of digital devices, smart classrooms, and connected infrastructures has generated unprecedented volumes of data across academic, administrative, and operational domains [3]. This data, when systematically collected and analyzed, has the potential to transform decision-making processes by providing evidence-based insights into student engagement, faculty productivity, infrastructure utilization, and overall institutional performance [4]. The integration of intelligent systems into campus operations enables administrators to respond proactively to challenges, optimize resource allocation, and align operational practices with strategic objectives [5]. The ability to harness real-time information from diverse data streams is increasingly recognized as a critical enabler of adaptive and efficient governance in higher education [6].
The Internet of Things (IoT) provides a framework for continuous data acquisition through interconnected sensors, smart devices, and wearable technologies deployed across campus facilities [7]. Classrooms, laboratories, libraries, and administrative units can generate real-time information on occupancy, usage patterns, environmental conditions, and equipment performance [8]. Data from student attendance systems, learning management platforms, and smart devices allows administrators to monitor engagement levels, identify learning gaps, and track academic performance [9]. IoT deployment extends to energy management, environmental monitoring, and facility maintenance, providing a comprehensive digital representation of campus operations [10]. The integration of heterogeneous IoT devices ensures interoperability across academic and administrative systems, creating a cohesive and scalable data infrastructure [11]. These capabilities allow higher education institutions to shift from reactive management to proactive, predictive, and prescriptive decision-making, thereby enhancing operational efficiency and institutional effectiveness [12].
