An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method

Helen Onovwerosuoke Sanubi; Augustine Aduge

doi:doi:10.11648/j.ijssam.20251002.12

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An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method

Helen Onovwerosuoke Sanubi^*

, Augustine Aduge

Published in International Journal of Systems Science and Applied Mathematics (Volume 10, Issue 2)

Received: 17 April 2025 Accepted: 4 May 2025 Published: 12 June 2025

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Abstract

This study presents the Epidemiological Quick Response and Alternative Code (EpiMod-QR/Alt) system, an innovative framework designed to address attendance management challenges in certain Nigerian higher institutions. By integrating QR/Alt code technology with compartmental differential equation modeling, the system offers real-time tracking, predictive analysis, and actionable insights for data-driven decision-making. Leveraging the Differential Transform Method (DTM), the system solves the underlying differential equations with enhanced computational efficiency and accuracy. The model categorizes students into dynamic compartments—scheduled, attending, and absent—allowing for continuous monitoring and analysis of attendance trends. The EpiMod-QR/Alt system is designed to overcome the limitations of traditional and semi-digital attendance systems, such as inaccuracy, time inefficiency, and lack of scalability. It supports hybrid learning environments by accommodating both physical and virtual attendance tracking, ensuring that data collection remains seamless and secure. Through theoretical validation and simulated scenarios, including fixed policies and dynamic interventions, the system demonstrates adaptability and robustness across diverse institutional contexts. Results indicate that the system significantly reduces absenteeism, improves administrative oversight, and supports the optimal allocation of institutional resources. Its predictive capabilities enable proactive interventions and long-term planning, aligning with the broader goals of smart campus transformation. The research lays the groundwork for practical implementation and highlights potential for future enhancements, including the integration of machine learning algorithms and expansion to multi-campus systems. By combining mathematical modeling with technological innovation, the EpiMod-QR/Alt system offers a scalable, efficient, and intelligent solution to modern attendance management in higher education.

Published in	International Journal of Systems Science and Applied Mathematics (Volume 10, Issue 2)
DOI	10.11648/j.ijssam.20251002.12
Page(s)	27-40
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Attendance Management, Differential Transform Method (DTM), Epidemiological Model, Hybrid Learning, Predictive Analytics

References

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APA Style

Sanubi, H. O., Aduge, A. (2025). An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. International Journal of Systems Science and Applied Mathematics, 10(2), 27-40. https://doi.org/10.11648/j.ijssam.20251002.12

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ACS Style

Sanubi, H. O.; Aduge, A. An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. Int. J. Syst. Sci. Appl. Math. 2025, 10(2), 27-40. doi: 10.11648/j.ijssam.20251002.12

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AMA Style

Sanubi HO, Aduge A. An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. Int J Syst Sci Appl Math. 2025;10(2):27-40. doi: 10.11648/j.ijssam.20251002.12

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@article{10.11648/j.ijssam.20251002.12,
  author = {Helen Onovwerosuoke Sanubi and Augustine Aduge},
  title = {An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method
},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {10},
  number = {2},
  pages = {27-40},
  doi = {10.11648/j.ijssam.20251002.12},
  url = {https://doi.org/10.11648/j.ijssam.20251002.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20251002.12},
  abstract = {This study presents the Epidemiological Quick Response and Alternative Code (EpiMod-QR/Alt) system, an innovative framework designed to address attendance management challenges in certain Nigerian higher institutions. By integrating QR/Alt code technology with compartmental differential equation modeling, the system offers real-time tracking, predictive analysis, and actionable insights for data-driven decision-making. Leveraging the Differential Transform Method (DTM), the system solves the underlying differential equations with enhanced computational efficiency and accuracy. The model categorizes students into dynamic compartments—scheduled, attending, and absent—allowing for continuous monitoring and analysis of attendance trends. The EpiMod-QR/Alt system is designed to overcome the limitations of traditional and semi-digital attendance systems, such as inaccuracy, time inefficiency, and lack of scalability. It supports hybrid learning environments by accommodating both physical and virtual attendance tracking, ensuring that data collection remains seamless and secure. Through theoretical validation and simulated scenarios, including fixed policies and dynamic interventions, the system demonstrates adaptability and robustness across diverse institutional contexts. Results indicate that the system significantly reduces absenteeism, improves administrative oversight, and supports the optimal allocation of institutional resources. Its predictive capabilities enable proactive interventions and long-term planning, aligning with the broader goals of smart campus transformation. The research lays the groundwork for practical implementation and highlights potential for future enhancements, including the integration of machine learning algorithms and expansion to multi-campus systems. By combining mathematical modeling with technological innovation, the EpiMod-QR/Alt system offers a scalable, efficient, and intelligent solution to modern attendance management in higher education.
},
 year = {2025}
}

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TY  - JOUR
T1  - An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method

AU  - Helen Onovwerosuoke Sanubi
AU  - Augustine Aduge
Y1  - 2025/06/12
PY  - 2025
N1  - https://doi.org/10.11648/j.ijssam.20251002.12
DO  - 10.11648/j.ijssam.20251002.12
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 27
EP  - 40
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20251002.12
AB  - This study presents the Epidemiological Quick Response and Alternative Code (EpiMod-QR/Alt) system, an innovative framework designed to address attendance management challenges in certain Nigerian higher institutions. By integrating QR/Alt code technology with compartmental differential equation modeling, the system offers real-time tracking, predictive analysis, and actionable insights for data-driven decision-making. Leveraging the Differential Transform Method (DTM), the system solves the underlying differential equations with enhanced computational efficiency and accuracy. The model categorizes students into dynamic compartments—scheduled, attending, and absent—allowing for continuous monitoring and analysis of attendance trends. The EpiMod-QR/Alt system is designed to overcome the limitations of traditional and semi-digital attendance systems, such as inaccuracy, time inefficiency, and lack of scalability. It supports hybrid learning environments by accommodating both physical and virtual attendance tracking, ensuring that data collection remains seamless and secure. Through theoretical validation and simulated scenarios, including fixed policies and dynamic interventions, the system demonstrates adaptability and robustness across diverse institutional contexts. Results indicate that the system significantly reduces absenteeism, improves administrative oversight, and supports the optimal allocation of institutional resources. Its predictive capabilities enable proactive interventions and long-term planning, aligning with the broader goals of smart campus transformation. The research lays the groundwork for practical implementation and highlights potential for future enhancements, including the integration of machine learning algorithms and expansion to multi-campus systems. By combining mathematical modeling with technological innovation, the EpiMod-QR/Alt system offers a scalable, efficient, and intelligent solution to modern attendance management in higher education.

VL  - 10
IS  - 2
ER  -

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Author Information

Helen Onovwerosuoke Sanubi

Department of Mathematics and Computer Science, Delta State College of Education, Mosogar, Nigeria

Contact Email

http://orcid.org/0009-0009-8241-8761
Augustine Aduge

Department of Mathematics and Computer Science, Delta State College of Education, Mosogar, Nigeria

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APA Style

Sanubi, H. O., Aduge, A. (2025). An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. International Journal of Systems Science and Applied Mathematics, 10(2), 27-40. https://doi.org/10.11648/j.ijssam.20251002.12

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ACS Style

Sanubi, H. O.; Aduge, A. An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. Int. J. Syst. Sci. Appl. Math. 2025, 10(2), 27-40. doi: 10.11648/j.ijssam.20251002.12

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AMA Style

Sanubi HO, Aduge A. An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method. Int J Syst Sci Appl Math. 2025;10(2):27-40. doi: 10.11648/j.ijssam.20251002.12

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@article{10.11648/j.ijssam.20251002.12,
  author = {Helen Onovwerosuoke Sanubi and Augustine Aduge},
  title = {An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method
},
  journal = {International Journal of Systems Science and Applied Mathematics},
  volume = {10},
  number = {2},
  pages = {27-40},
  doi = {10.11648/j.ijssam.20251002.12},
  url = {https://doi.org/10.11648/j.ijssam.20251002.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijssam.20251002.12},
  abstract = {This study presents the Epidemiological Quick Response and Alternative Code (EpiMod-QR/Alt) system, an innovative framework designed to address attendance management challenges in certain Nigerian higher institutions. By integrating QR/Alt code technology with compartmental differential equation modeling, the system offers real-time tracking, predictive analysis, and actionable insights for data-driven decision-making. Leveraging the Differential Transform Method (DTM), the system solves the underlying differential equations with enhanced computational efficiency and accuracy. The model categorizes students into dynamic compartments—scheduled, attending, and absent—allowing for continuous monitoring and analysis of attendance trends. The EpiMod-QR/Alt system is designed to overcome the limitations of traditional and semi-digital attendance systems, such as inaccuracy, time inefficiency, and lack of scalability. It supports hybrid learning environments by accommodating both physical and virtual attendance tracking, ensuring that data collection remains seamless and secure. Through theoretical validation and simulated scenarios, including fixed policies and dynamic interventions, the system demonstrates adaptability and robustness across diverse institutional contexts. Results indicate that the system significantly reduces absenteeism, improves administrative oversight, and supports the optimal allocation of institutional resources. Its predictive capabilities enable proactive interventions and long-term planning, aligning with the broader goals of smart campus transformation. The research lays the groundwork for practical implementation and highlights potential for future enhancements, including the integration of machine learning algorithms and expansion to multi-campus systems. By combining mathematical modeling with technological innovation, the EpiMod-QR/Alt system offers a scalable, efficient, and intelligent solution to modern attendance management in higher education.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - An EpiMod-QR/Alt Code-Based Model for Smart Campus Attendance Management Using the Differential Transform Method

AU  - Helen Onovwerosuoke Sanubi
AU  - Augustine Aduge
Y1  - 2025/06/12
PY  - 2025
N1  - https://doi.org/10.11648/j.ijssam.20251002.12
DO  - 10.11648/j.ijssam.20251002.12
T2  - International Journal of Systems Science and Applied Mathematics
JF  - International Journal of Systems Science and Applied Mathematics
JO  - International Journal of Systems Science and Applied Mathematics
SP  - 27
EP  - 40
PB  - Science Publishing Group
SN  - 2575-5803
UR  - https://doi.org/10.11648/j.ijssam.20251002.12
AB  - This study presents the Epidemiological Quick Response and Alternative Code (EpiMod-QR/Alt) system, an innovative framework designed to address attendance management challenges in certain Nigerian higher institutions. By integrating QR/Alt code technology with compartmental differential equation modeling, the system offers real-time tracking, predictive analysis, and actionable insights for data-driven decision-making. Leveraging the Differential Transform Method (DTM), the system solves the underlying differential equations with enhanced computational efficiency and accuracy. The model categorizes students into dynamic compartments—scheduled, attending, and absent—allowing for continuous monitoring and analysis of attendance trends. The EpiMod-QR/Alt system is designed to overcome the limitations of traditional and semi-digital attendance systems, such as inaccuracy, time inefficiency, and lack of scalability. It supports hybrid learning environments by accommodating both physical and virtual attendance tracking, ensuring that data collection remains seamless and secure. Through theoretical validation and simulated scenarios, including fixed policies and dynamic interventions, the system demonstrates adaptability and robustness across diverse institutional contexts. Results indicate that the system significantly reduces absenteeism, improves administrative oversight, and supports the optimal allocation of institutional resources. Its predictive capabilities enable proactive interventions and long-term planning, aligning with the broader goals of smart campus transformation. The research lays the groundwork for practical implementation and highlights potential for future enhancements, including the integration of machine learning algorithms and expansion to multi-campus systems. By combining mathematical modeling with technological innovation, the EpiMod-QR/Alt system offers a scalable, efficient, and intelligent solution to modern attendance management in higher education.

VL  - 10
IS  - 2
ER  -

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