Jul 2026· TechSys 2026· pp. 5· 0 citations· 41 references
TL;DR
The study proposes a Smart Campus Education Data Model (SCEDM), which can be integrated into any FIWARE-based platform and is organized as a layered architecture that includes data acquisition, processing, and storage; analytics and decision support; application presentation; and security.
Abstract
Smart campus development is increasingly associated with the combined use of IoT technologies, artificial intelligence, cloud infrastructures, and large-scale data analytics in higher education. Despite this progress, many existing data models are not well-suited to the educational domain, particularly when interoperability and real-time analytical capabilities are required. To address this limitation, the study proposes a Smart Campus Education Data Model (SCEDM), which can be integrated into any FIWARE-based platform. The model is organized as a layered architecture that includes data acquisition, processing, and storage; analytics and decision support; application presentation; and security. The proposed model is not presented only at a conceptual level; it is also validated in a con-tainerized FIWARE environment built around the Orion-ld Context Broker and NGSI-ld specifications. The SCEDM model is validated in a system that supports real-time state management across multiple campus domains. The model’s practical operation is validated across several experimental scenarios, including a simulation of a lecture process, classroom occupancy monitoring, and automated notifications to external platforms. In addition, the study compares five international case studies from different contexts. The comparison shows that, despite differences across local settings, similar benefits can be observed in campus operations and learning conditions. The study also recognizes several continuing challenges in the development of smart campuses, including interoperability, long-term scalability, data governance, privacy protection, stakeholder engagement, and financial sustainability. In response to these issues, the authors propose practical design guidelines alongside strategic recommendations for adoption at the institutional level.
The concept of a smart campus has emerged with advances in ICT, IoT, cloud computing, and data analytics, enabling higher education institutions to improve efficiency, sustainability, and user experience. This paper presents an integrated technology framework that connects infrastructure, services, and stakeholders through intelligent systems. It highlights the role of IoT for real-time monitoring, cloud platforms for scalable data management, and AI/ML for predictive decision-making. The proposed architecture consists of sensing, network, data processing, and application layers to ensure interoperability among heterogeneous systems. The study also emphasizes the importance of cybersecurity, privacy, and governance in maintaining system integrity. Results show that smart campus implementation enhances energy efficiency, operational performance, and user satisfaction. Finally, the paper provides a roadmap for developing scalable, sustainable, and intelligent campus ecosystems.
Nandhini Ravi· International Journal of Eme...· 0 citations
The increasing adoption of digital technologies in higher education has accelerated the transformation of conventional libraries into smart learning environments that enhance operational efficiency and user experience. However, many academic libraries continue to face challenges such as misplaced books, limited visibility of study seat availability, and the inability to monitor in-library reading activities, resulting in inefficient resource management and increased staff workload. This study presents an Internet of Things (IoT)-based Smart Library Management System that integrates an ESP32 microcontroller, RFID RC522 modules, FSR402 pressure sensors, cloud computing, and a web-based dashboard to enable real-time monitoring and automation of library operations. RFID technology is employed to verify book locations and detect misplaced items, while pressure sensors monitor seat occupancy to provide users with real-time availability information. In addition, the system records the duration that books remain off the shelves to identify in-library reading activities, providing valuable insights into resource utilisation. Sensor data are transmitted via Wi-Fi to a cloud platform, enabling centralized monitoring of book status, seat occupancy, and library usage through an interactive dashboard. Prototype evaluation demonstrated reliable system integration with an average data transmission latency of approximately 180 ms, while the total prototype cost of RM121.54 demonstrates the feasibility of implementing a cost-effective smart library solution. To complement the technical evaluation, a user acceptance and usability survey involving 70 respondents indicated strong support for the proposed smart library features, particularly real-time seat occupancy monitoring and automated misplaced-book detection. Overall, the proposed framework provides a practical, scalable, and user-centred solution that supports Smart Campus initiatives by improving library services, enhancing operational decision-making, and promoting more efficient resource management in higher education institutions.
Ahmad M. A. A. Wafik, N. A. H. Amran, N. N. Norhisham et al.· International journal of res...· 0 citations
The rapid growth of the Internet of Things (IoT) has significantly accelerated the development of smart home systems, enabling automation, energy efficiency, and enhanced user experience. However, the lack of interoperability among heterogeneous devices and platforms remains a major challenge, resulting in fragmented ecosystems and limited scalability. To address these issues, the Matter protocol has emerged as a unified, IP-based connectivity standard for smart home environments. This paper presents a comprehensive study of the Matter protocol, including its architecture, communication mechanisms, and security model. A practical IoT-based smart home system is designed and implemented using ESP32 platforms and the Matter SDK. The system integrates multiple devices such as smart lighting, switches, smart plugs, and environmental sensors, supporting crossplatform interaction across different ecosystems. Experimental evaluation is conducted under real-world conditions, focusing on interoperability, latency, system stability, and security. The results show that the proposed system achieves reliable crossplatform compatibility, stable network performance, low communication latency, and secure device authentication. Additionally, the system maintains core functionality even under limited network conditions, demonstrating strong robustness. These findings confirm that the Matter protocol is a promising solution for building scalable, secure, and interoperable next-generation smart home systems.
Nghia Duong Tan, H. Manh, P. N. Huu et al.· 2026 11th International Conf...· 0 citations
The findings demonstrate that the proposed architecture reduces data fragmentation, improves interoperability, and supports evidence-based governance, facilitating a transition from compliance-based to impact-based institutional management.
Rochmawati Rochmawati, A. N. Handayani, Tran Thi Hao et al.· Matrik· 0 citations
This study proposes a conceptual framework for designing a Unified Student Information and Learning Analytics System (SIS-LA) tailored for higher education institutions in Oman. The framework addresses the current fragmentation of academic, administrative, and learning systems that limit data sharing and hinder institutional efficiency. By integrating these components into a single interoperable platform, the SIS-LA supports data-driven decision-making, personalized learning, and effective academic planning. The system design applies System Analysis and Design (SAD) and Database Management System (DBMS) methodologies to ensure robust data management and interoperability. It incorporates artificial intelligence, ontology-based data modeling, and standardized application programming interfaces (APIs) to enable real-time reporting, predictive analytics, and early identification of at-risk students. Ethical data governance and compliance with Oman’s Personal Data Protection Law are central to the framework, ensuring privacy and cultural alignment. The proposed model is benchmarked against international learning analytics frameworks to assess adaptability to Oman’s educational and regulatory context. Findings suggest that the unified, ontology-driven approach enhances institutional adaptability, strengthens data governance, and supports Oman’s digital transformation goals. The SIS-LA framework provides a foundation for future implementation and contributes to achieving the objectives of Oman Vision 2040 in advancing higher education innovation.
Francis R. Abraham· International journal of res...· 0 citations
The growing adoption of Internet of Things (IoT) technologies has created a strong demand for educational platforms that effectively demonstrate long-range, low-power wireless communication. However, most existing IoT training tools focus on short-range connectivity or are insufficiently modular for instructional use. This project addresses this gap by designing and developing a modular, PCB-based ESP32-LoRa training kit tailored for IoT education. The objective is to provide a hands-on platform that enables students to understand sensor integration, long-range communication, and real-world radio-frequency behavior. The system is built around the Heltec WiFi LoRa 32 V3 and custom-designed sensor and actuator PCBs. Experimental evaluation was conducted in two phases: sensor accuracy validation and LoRa link performance testing under line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. In this work, only temperature sensor was tested. Results show high sensor reliability with low mean absolute error, while communication trials achieved a packet delivery ratio of 94% at 50 m in LOS conditions and maintained 64% in NLOS environments at a signal-to-noise ratio of −9.8 dB. The transition from breadboard to double-layer PCB significantly reduced noise and improved signal integrity. Overall, the proposed training kit provides a robust and effective educational tool for teaching long-range IoT communication principles.
Nur Ain Natrah Abd Manan, N. M. Thamrin, Nur Aqilah Zainuddin· 2026 IEEE International Conf...· 0 citations