| Autor: |
Adegbenjo, Aderonke A., Onuiri, Ernest E., Kalesanwo, Olamide B., Agbaje, Michael O., Abel, Samuel B., Fatade, Oluwayemisi B., Amusa, Afolarin I., Umeaka, Kelechi C., Ehioghae, Eseosa, Onamade, Korede O. |
| Předmět: |
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| Zdroj: |
Journal Européen des Systèmes Automatisés; Oct2023, Vol. 56 Issue 5, p889-897, 9p |
| Abstrakt: |
The transformative capacity of the Internet of Things (IoT) has become evident across various sectors. Despite its potential, a discernible hesitancy exists in its adoption within higher education institutions. This research explores the specific advantages and challenges of implementing IoT in the context of higher education, particularly in optimizing data-driven decision-making processes. The approach focuses on creating a comprehensive IoT framework tailored for higher education, encompassing a foundational data warehouse layer, an intermediary application layer for streamlining data, a message broker layer for data orchestration, a granular message consumer layer for data refinement, and a central data lake that consolidates both real-time and structured data. This system adeptly manages a continuous stream of structured and real-time data. With the integration of Kafka and TensorFlow, real-time video streams are processed, providing enhanced security measures for campuses. Biometric devices, strategically positioned, offer detailed data on institutional dynamics, all converging into a central data reservoir. This vast data collection presents profound insights, shaping administrative strategies and improving institutional efficiency. The adoption of IoT in higher education holds vast potential, yet challenges persist. Striking a balance between surveillance and privacy, ensuring data integrity, and navigating the complexities of scalability are vital considerations. However, with careful and strategic implementation, IoT integration can usher in a revolutionary era of data-driven academic operations, enhancing both security and institutional efficiency. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
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