Hybrid RFID-Geolocation Smart Attendance Unit for Enhanced Inclusivity and Efficiency
DOI:
https://doi.org/10.33003/fjs-2026-1016-5858Keywords:
IoTs, Attendance Management, Smart Campus, Access control, RFiDs, Wireless sensor networksAbstract
Adoption of Internet of Things (IoTs) in attendance management rebirths pedagogical practices to advance operational differentiation as modern procedural standards in learning citadels. Its utilization yields a transformative platform with smart access points towards inclusivity for teachers and learners while providing the needed reachability cum availability for ubiquitous learning with substantial cost reduction as an expansive tool. With its converged technology, wireless sensor networks and educational pedagogy – it equips administration with intelligent units that ease data exchange. Result shows the proposed artifact yielded a throughput with an average successful authenticated login time of 3.2secs with a zero false acceptance/rejection rate(s) (FAR/FRR) in properly configured sessions. Also, the peak Auth_Server response of 1.6secs for successful login helped to affirms the system’s high authentication accuracy, and an exceptional reliability for a 30-days testing period with an uptime of 0.997, and no latency for remote management. System also showed a recovery rate of 1.000 with an average recovery time of 4.2secs. The study has successfully demonstrated a working prototype that integrates knowledge-factor (PIN+OTP), possession-factor (RFID), and inherence-factor (biometrics) – utilized as authentication modes secured via the hashed MFA-records tokenization approach.
References
Abdul Hannan, S. (2023). a Blockchain Technology and Internet of Things To Secure in Healthcare System. Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552), 9(4), 12–19. https://doi.org/10.53555/nncse.v9i4.1641
Aghaunor, T. C., Agboi, J., Ugbotu, E. V., Onoma, P. A., Ojugo, A. A., Odiakaose, C. C., Eboka, A. O., Ezzeh, P. O., Geteloma, V. O., Binitie, A. P., Orobor, A. I., Nwozor, B., Ejeh, P. O., & Onochie, C. C. (2025). EcoSMEAL: Energy Consumption with Optimization Strategy via a Secured Smart Monitor- Alert Ensemble. Journal of Fuzzy Systems and Control, 3(3), 190–196. https://doi.org/10.59247/jfsc.v3i3.319
Aghaunor, T. C., Ugbotu, E. V., Ugboh, E., Onoma, P. A., Emordi, F. U., Ojugo, A. A., Geteloma, V. O., Idama, R. O., & Ezzeh, P. O. (2026). Investigating Security Enhancement in Hybrid Clouds via a Blockchain-Fused Privacy Preservation Strategy: Pilot Study. Journal of Computing Theories and Applications, 3(4), 428–442. https://doi.org/10.62411/jcta.15508
Aherobo, O. V., Okpor, M. D., Agboi, J., Ugboh, E., Asheshemi, N., Onoma, P. A., Ojugo, A. A., Ako, R. E., Geteloma, V. O., Max-Egba, A. T., Ugbotu, E. V., Aghaunor, T. C., Okperigho, S., Igulu, K. T., Asunogie, T. O., & Abere, R. A. (2026). GeoSMATS: geolocation smart attendance management unit for secured learner verification and educational inclusivity. Dutse Journal of Pure and Applied Sciences, 12(2d), 410–425. https://doi.org/10.4314/dujopas.v12i2d.33
Akazue, M. I., Edje, A. E., Okpor, M. D., Adigwe, W., Ejeh, P. O., Odiakaose, C. C., Ojugo, A. A., Edim, E. B., Ako, R. E., & Geteloma, V. O. (2024). FiMoDeAL: pilot study on shortest path heuristics in wireless sensor network for fire detection and alert ensemble. Bulletin of Electrical Engineering and Informatics, 13(5), 3534–3543. https://doi.org/10.11591/eei.v13i5.8084
Ako, R. E., Okpako, A. E., Okoro, D. A., Ojie, D. V., Ojugo, A. A., Geteloma, V. O., Niemogha, S. U., Nwankwo, P. C., & Nwankwo, W. (2026). Proactive Fall Risk Prediction in Construction Sites: An Explainable AI Approach. 2026 IEEE ICCOMTECH, 1–6.
Al-Turjman, F., Zahmatkesh, H., & Mostarda, L. (2019). Quantifying uncertainty in internet of medical things and big-data services using intelligence and deep learning. IEEE Access, 7, 115749–115759. https://doi.org/10.1109/ACCESS.2019.2931637
Allam, A. H., Gomaa, I., Zayed, H. H., & Taha, M. (2024). IoT-based eHealth using blockchain technology: a survey. Cluster Computing, 0123456789. https://doi.org/10.1007/s10586-024-04357-y
Almadani, M. S., Alotaibi, S., Alsobhi, H., Hussain, O. K., & Hussain, F. K. (2023). Blockchain-based multi-factor authentication: A systematic literature review. Internet of Things, 23, 100844. https://doi.org/10.1016/j.iot.2023.100844
Anthony-Akhutie, P., Omosor, J. C., Onoma, P. A., Ojugo, A. A., Ako, R. E., Agboi, J., Odiakaose, C. C., Max-Egba, A. T., Geteloma, V. O., Niemogha, S. U., & Abdullahi, M. B. (2025). SEMAEco-IoT: A Secured IoT-based Smart Energy Monitor and Alert for Enhanced Energy Conservation and Optimization. FUPRE Journal of PetroScience, 1(1), 150–166.
Anwar, T., & Uma, V. (2021). Comparative study of recommender system approaches and movie recommendation using collaborative filtering. International Journal of System Assurance Engineering and Management, 12(3), 426–436. https://doi.org/10.1007/s13198-021-01087-x
Arachchige, K. G., Branch, P., & But, J. (2024). An Analysis of Blockchain-Based IoT Sensor Network Distributed Denial of Service Attacks. Sensors, 24(10), 3083. https://doi.org/10.3390/s24103083
Asheshemi, N. O., Okpor, M. D., Agboi, J., Ugboh, E., Ugbotu, E. V., Abere, R. A., Odim-Kalu, T. V., Onoma, P. A., Ojugo, A. A., Max-Egba, A. T., Aghaunor, T. C., Igulu, K. T., Asunogie, T. O., Okoh, K. C., Inaya, A., & Niemogha, S. U. (2026). Adaptive Content-Aware Model for Learner-Centric Blended-Learning: A Pilot Study. FUDMA Journal of Sciences, 10(14), 27–37. https://doi.org/10.33003/fjs-2026-1014-5735
Aworonye, E. ., Abere, R. A., Ako, R. E., Nwozor, B., & Geteloma, V. O. (2024). IoT-Motion electric eye ensemble for reduced power consumption in automated homes. FUPRE Journal of Scientific and Industrial Research, 8(2), 128–142.
Bamashmos, S., Chilamkurti, N., & Shahraki, A. S. (2024). Two-Layered Multi-Factor Authentication Using Decentralized Blockchain in an IoT Environment. Sensors, 24(11). https://doi.org/10.3390/s24113575
Binitie, A. P., Okofu, S. N., Okpor, M. D., Anazia, K. E., Ojugo, A. A., Egbokhare, F. A., Egwali, A., Ezzeh, P. O., Ako, R. E., Geteloma, V. O., Aghaunor, T. C., Ugbotu, E. V., & Onyemenem, S. I. (2025). MoBiSafe: an obfuscated single factor authentication mode to enhance secured USSD channel transaction in Nigeria. Indonesian Journal of Electrical Engineering and Computer Science, 40(1), 426. https://doi.org/10.11591/ijeecs.v40.i1.pp426-436
Binitie, A. P., Onyemenem, S. I., Anujeonye, N. C., Ojugo, A. A., Egbokhare, F. A., & Aghaunor, T. C. (2026). A Graph-Augmented Isolation Forest Using Node2Vec and GraphSAGE for Mobile User Behavior Anomaly Detection. Journal of Computing Theories and Applications, 3(3), 369–383. https://doi.org/10.62411/jcta.15494
Brijwani, G. N., Ajmire, P. E., Jewani, V., Thawani, P. V., Mohammad, D., Junaid, M. A., Khan, T., & Pawar, D. S. (2024). HealthShield: A Blockchain-Based Electronic Health Recording System with Enhanced Security Algorithm for Immutable and Confidential Health Data Management. International Journal of Scientific Research in Science and Technology, 11(3), 794–814. https://doi.org/10.32628/ijsrst24113234
Brizimor, S. E., Okpor, M. D., Yoro, R. E., Emordi, F. U., Ifioko, A. M., Odiakaose, C. C., Ojugo, A. A., Ejeh, P. O., Abere, R. A., Ako, R. E., & Geteloma, V. O. (2024). WiSeCart: Sensor-based Smart-Cart with Self-Payment Mode to Improve Shopping Experience and Inventory Management. Social Informatics, Business, Politics, Law, Environmental Sciences and Technology Journal, 10(1), 53–74. https://doi.org/10.22624/aims/sij/v10n1p7
Chans, G. M., & Portuguez Castro, M. (2021). Gamification as a Strategy to Increase Motivation and Engagement in Higher Education Chemistry Students. Computers, 10(10), 132. https://doi.org/10.3390/computers10100132
Dhinakaran, E. al. (2023). IoT-Based Environmental Control System for Fish Farms with Sensor Integration and Machine Learning Decision Support. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 203–217. https://doi.org/10.17762/ijritcc.v11i10.8482
Dwivedi, A. D., Srivastava, G., Dhar, S., & Singh, R. (2019). A Decentralized Privacy-Preserving Healthcare Blockchain for IoT. Sensors, 19(2), 326. https://doi.org/10.3390/s19020326
Eboka, A. O., Aghware, F. O., Okpor, M. D., Odiakaose, C. C., Okpako, A. E., Ojugo, A. A., Ako, R. E., Binitie, A. P., Onyemenem, S. I., Ejeh, P. O., & Geteloma, V. O. (2025). Pilot study on deploying a wireless sensor-based virtual-key access and lock system for home and industrial frontiers. International Journal of Informatics and Communication Technology, 14(1), 287–297. https://doi.org/10.11591/ijict.v14i1.pp287-297
Eboka, A. O., & Ojugo, A. A. (2020). Mitigating technical challenges via redesigning campus network for greater efficiency, scalability and robustness: A logical view. International Journal of Modern Education and Computer Science, 12(6), 29–45. https://doi.org/10.5815/ijmecs.2020.06.03
Fan, K., Bao, Z., Liu, M., Vasilakos, A. V., & Shi, W. (2020). Dredas: Decentralized, reliable and efficient remote outsourced data auditing scheme with blockchain smart contract for industrial IoT. Future Generation Computer Systems, 110, 665–674. https://doi.org/10.1016/j.future.2019.10.014
Fereidooni, H., König, J., Rieger, P., Chilese, M., Gökbakan, B., Finke, M., Dmitrienko, A., & Sadeghi, A.-R. (2023). AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms.
Finlow-bates, K. (2020). Towards a Decentralized Certificate Authority (Issue April 2019).
Geteloma, V. O., Aghware, F. O., Adigwe, W., Odiakaose, C. C., Ashioba, N. C., Okpor, M. D., Ojugo, A. A., Ejeh, P. O., Ako, R. E., & Ojei, E. O. (2024). AQuamoAS: unmasking a wireless sensor-based ensemble for air quality monitor and alert system. Applied Engineering and Technology, 3(2), 70–85. https://doi.org/10.31763/aet.v3i2.1409
Govea, J., Gaibor-Naranjo, W., & Villegas-Ch, W. (2024). Securing Critical Infrastructure with Blockchain Technology: An Approach to Cyber-Resilience. Computers, 13(5), 122. https://doi.org/10.3390/computers13050122
Hao, L., & Wang, X. (2025). Application of EM-transformer hybrid model in real-time detection of directed DDoS attacks on botnet devices. Discover Internet of Things, 5(1). https://doi.org/10.1007/s43926-025-00247-w
Hayati, N., & Nugraha, A. E. (2023). Design and Implementation Proximity Based IoT for Smart Attendance System. Bulletin Pos Dan Telekomunikasi, 21(2), 16–31. https://doi.org/10.17933/bpostel.v21i2.380
Huang, M., Liu, W., Wang, T., Song, H., Li, X., & Liu, A. (2019). A queuing delay utilization scheme for on-path service aggregation in services-oriented computing networks. IEEE Access, 7, 23816–23833. https://doi.org/10.1109/ACCESS.2019.2899402
Hussien, S. H. T., Vinukumar, L., Alexander, C. H. C., & Sivakumar, S. (2024). Smart Campus Attendance and Security Systems : AIP Conference Proceedings, 020153. https://doi.org/10.1063/5.0229386
Ibor, A. E., Ashishie, D. U., Odey, J. A., Ele, B. I., & Ojugo, A. A. (2026). Can We Unchain the Blockchain? A Review of Attacks on Elliptic Curve Cryptography and Countermeasures. Security and Privacy, 9(4). https://doi.org/10.1002/spy2.70234
Islam, N., Farhin, F., Sultana, I., Kaiser, S., Rahman, S., Mahmud, M., Hosen, S., & Cho, G. H. (2021). Towards Machine Learning Based Intrusion Detection in IoT Networks. Computers, Materials and Continua, 69(2), 1801–1821. https://doi.org/10.32604/cmc.2021.018466
Jin, X., & Omote, K. (2024). An efficient blockchain-based authentication scheme with transferability. PLoS ONE, 19(9 September), 1–16. https://doi.org/10.1371/journal.pone.0310094
Jose, J., Rivera, D., Akbar, W., Khan, T. A., & Muhammad, A. (2023). Secure Enrollment Token Delivery Mechanism for Zero Trust Networks Using Secure enrollment token delivery mechanism for Zero Trust networks using blockchain ‡. July. https://doi.org/10.1587/trans.E0.
Kafetzopoulos, D., Stylios, C., & Skalkos, D. (2020). Managing traceability in the meat processing industry: Principles, guidelines and technologies. CEUR Workshop Proceedings, 2761(2010), 302–308.
Kakhi, K., Alizadehsani, R., Kabir, H. M. D., Khosravi, A., Nahavandi, S., & Acharya, U. R. (2022). The internet of medical things and artificial intelligence: trends, challenges, and opportunities. Biocybernetics and Biomedical Engineering, 42(3), 749–771. https://doi.org/10.1016/j.bbe.2022.05.008
Kizilkaya, B., Ever, E., Yatbaz, H. Y., & Yazici, A. (2022). An Effective Forest Fire Detection Framework Using Heterogeneous Wireless Multimedia Sensor Networks. ACM Transactions on Multimedia Computing, Communications, and Applications, 18(2), 1–21. https://doi.org/10.1145/3473037
Kumar, S., Tiwari, P., & Zymbler, M. (2019). Internet of Things is a revolutionary approach for future technology enhancement: a review. Journal of Big Data, 6(1), 111. https://doi.org/10.1186/s40537-019-0268-2
Lin, H. C., Chen, M. J., Lee, C. H., Kung, L. C., & Huang, J. T. (2023). Fall Recognition Based on an IMU Wearable Device and Fall Verification through a Smart Speaker and the IoT. Sensors, 23(12). https://doi.org/10.3390/s23125472
Malasowe, B. O., Aghware, F. O., Okpor, M. D., Edim, E. B., Ako, R. E., & Ojugo, A. A. (2024). Techniques and Best Practices for Handling Cybersecurity Risks in Educational Technology Environment. NIPES - Journal of Science and Technology Research, 6(2), 293–311. https://doi.org/10.5281/zenodo.12617068
Malasowe, B. O., Akazue, M. I., Okpako, A. E., Aghware, F. O., Ojugo, A. A., & Ojie, D. V. (2023). Adaptive Learner-CBT with Secured Fault-Tolerant and Resumption Capability for Nigerian Universities. International Journal of Advanced Computer Science and Applications, 14(8), 135–142. https://doi.org/10.14569/IJACSA.2023.0140816
Mishra, S., Ngangbam, B., Raj, S., & Pradhan, N. R. (2023). CURA: Real Time Artificial Intelligence and IoT based Fall Detection Systems for patients suffering from Dementia. EAI
Endorsed Transactions on Pervasive Health and Technology, 9(1), 1–6. https://doi.org/10.4108/eetpht.9.3967
Nur, M. J., Setiadi, D. R. I. M., Ojugo, A. A., & Nguyen, M. T. (2025). Improving Customer Churn Prediction Using Domain-Driven Feature Engineering, Resampling, and CatBoost with Explainability Extensions. 2025 International Seminar on Application for Technology of Information and Communication (ISemantic), 493–499. https://doi.org/10.1109/ISemantic67418.2025.11291801
Obasuyi, D. A., Yoro, R. E., Okpor, M. D., Ifioko, A. M., Brizimor, S. E., Ojugo, A. A., Odiakaose, C. C., Emordi, F. U., Ako, R. E., Geteloma, V. O., Abere, R. A., Atuduhor, R. R., & Akiakeme, E. (2024). NiCuSBlockIoT: Sensor-based Cargo Assets Management and Traceability Blockchain Support for Nigerian Custom Services. Advances in Multidisciplinary & Scientific Research Journal Publications, 15(2), 45–64. https://doi.org/10.22624/aims/cisdi/v15n2p4
Og, S., & Ying, L. (2021). The Internet of Medical Things. ICMLCA 2021 - 2nd International Conference on Machine Learning and Computer Application, 273–276.
Ohwomado, K., Akazue, M. I., & Ojugo, A. A. (2026). A Systematic Ablation-Based Optimisation Protocol for Convolutional Neural Networks in Electronic Banking Fraud Detection. FUDMA Journal of Sciences, 10(12), 79–84. https://doi.org/10.33003/fjs-2026-1012-5285
Ojugo, A. A., Agboi, J., Ugboh, E., Asunogie, T. O., Igulu, K. T., Onoma, P. A., Abere, R. A., Aherobo, O. V., & Okperigho, S. U. (2026). Unmasking High Performance Phishing Detection with Feature Fusion of a Tree-based Transfer Learning Boosted Approach using SMOTE-Tomek Balancing: A Pilot Study. FUPRE Journal of Scientific and Industrial Research, 10(1), 43–58. https://doi.org/10.60787/FJSIR.v10i1.43-58
Ojugo, A. A., Ben Iwhiwhu, E., Kekeje, O. D., Yerokun, M. O., & Iyawa, I. J. (2014). Malware Propagation on Social Time Varying Networks: A Comparative Study of Machine Learning Frameworks. International Journal of Modern Education and Computer Science, 6(8), 25–33. https://doi.org/10.5815/ijmecs.2014.08.04
Ojugo, A. A., & Eboka, A. O. (2018). Comparative Evaluation for High Intelligent Performance Adaptive Model for Spam Phishing Detection. Digital Technologies, 3(1), 9–15. https://doi.org/10.12691/dt-3-1-2
Ojugo, A. A., & Eboka, A. O. (2019). Inventory prediction and management in Nigeria using market basket analysis associative rule mining: memetic algorithm based approach. International Journal of Informatics and Communication Technology (IJ-ICT), 8(3), 128. https://doi.org/10.11591/ijict.v8i3.pp128-138
Ojugo, A. A., Okpor, M. D., Igulu, K. T., Ugboh, E., Asunogie, T. O., Usiobaifo, R., Onoma, P. A., Aghaunor, T. C., Binitie, A. P., Ezzeh, P. O., Ugbotu, E. V., & Okperigho, S. U. (2026). Pilot Investigation on Security Enhancement for a Door Access Management for a Commercial Manufacturing Environment. Dutse Journal of Pure and Applied Sciences, 12(2a), 145–159. https://doi.org/10.4314/dujopas.v12i2a.14
Ojugo, A. A., & Otakore, O. D. (2020). Computational solution of networks versus cluster grouping for social network contact recommender system. International Journal of Informatics and Communication Technology (IJ-ICT), 9(3), 185. https://doi.org/10.11591/ijict.v9i3.pp185-194
Ojugo, A. A., & Oyemade, D. A. (2021). Boyer moore string-match framework for a hybrid short message service spam filtering technique. IAES International Journal of Artificial Intelligence, 10(3), 519–527. https://doi.org/10.11591/ijai.v10.i3.pp519-527
Ojugo, A. A., & Yoro, R. E. (2021). Extending the three-tier constructivist learning model for alternative delivery: Ahead the COVID-19 pandemic in Nigeria. Indonesian Journal of Electrical Engineering and Computer Science, 21(3), 1673–1682. https://doi.org/10.11591/ijeecs.v21.i3.pp1673-1682
Okofu, S. N., Akazue, M. I., Oweimieotu, A. E., Ako, R. E., Ojugo, A. A., & Asuai, C. E. (2024). Improving Customer Trust through Fraud Prevention E-Commerce Model. Journal of Computing, Science and Technoloogy, 1(1), 76–86.
Okofu, S. N., Anazia, K. E., Akazue, M. I., Okpor, M. D., Oweimieotu, A. E., Asuai, C. E., Nwokolo, G. A., Ojugo, A. A., & Ojei, E. O. (2024). Pilot Study on Consumer Preference, Intentions and Trust on Purchasing-Pattern for Online Virtual Shops. International Journal of Advanced Computer Science and Applications, 15(7), 804–811. https://doi.org/10.14569/IJACSA.2024.0150780
Okpor, M. D., Aghware, F. O., Akazue, M. I., Eboka, A. O., Ako, R. E., Ojugo, A. A., Odiakaose, C. C., Binitie, A. P., Geteloma, V. O., & Ejeh, P. O. (2024). Pilot Study on Enhanced Detection of Cues over Malicious Sites Using Data Balancing on the Random Forest Ensemble. Journal of Future Artificial Intelligence and Technologies, 1(2), 109–123. https://doi.org/10.62411/faith.2024-14
Okpor, M. D., Aghware, F. O., Akazue, M. I., Ojugo, A. A., Emordi, F. U., Odiakaose, C. C., Ako, R. E., Geteloma, V. O., Binitie, A. P., & Ejeh, P. O. (2024). Comparative Data Resample to Predict Subscription Services Attrition Using Tree-based Ensembles. Journal of Fuzzy Systems and Control, 2(2), 117–128. https://doi.org/10.59247/jfsc.v2i2.213
Okpor, M. D., Anazia, K. E., Adigwe, W., Okpako, A. E., Setiadi, D. R. I. M., Ojugo, A. A., Omoruwou, F., Ako, R. E., Geteloma, V. O., Ugbotu, E. V., Aghaunor, T. C., & Oweimieotu, A. E. (2025). Unmasking effects of feature selection and SMOTE-Tomek in tree-based random forest for scorch occurrence detection. Bulletin of Electrical Engineering and Informatics, 14(3), 2393–2403. https://doi.org/10.11591/eei.v14i3.8901
Olaniyi, O. O., Okunleye, O. J., Olabanji, S. O., Asonze, C. U., & Ajayi, S. A. (2023). IoT Security in the Era of Ubiquitous Computing: A Multidisciplinary Approach to Addressing Vulnerabilities and Promoting Resilience. Asian Journal of Research in Computer Science, 16(4), 354–371. https://doi.org/10.9734/ajrcos/2023/v16i4397
Omede, E. U., Edje, A. E., Akazue, M. I., Utomwen, H., & Ojugo, A. A. (2024). IMANoBAS: An Improved Multi-Mode Alert Notification IoT-based Anti-Burglar Defense System. Journal of Computing Theories and Applications, 1(3), 273–283. https://doi.org/10.62411/jcta.9541
Omosor, J. C., Onoma, P. A., Ojugo, A. A., Ako, R. E., Geteloma, V. O., Akhutie-Anthony, P., & Okperigho, S. U. (2025). Security Enhancement using Multifactor Authentication Strategy for the Solenoid Door Access Control and Management: A Pilot Study. FUPRE Journal of Scientific and Industrial Research, 6(3), 80–94.
Ou, H.-H., Pan, C.-H., Tseng, Y.-M., & Lin, I.-C. (2024). Decentralized Identity Authentication Mechanism: Integrating FIDO and Blockchain for Enhanced Security. Applied Sciences, 14(9), 3551. https://doi.org/10.3390/app14093551
Oyemade, D. A., Akpojaro, J., Ojugo, A. A., Ureigho, R. J., Imouokhome, F. A.-A., & Omoregbee, E. U. (2016). A Three Tier Learning Model for Universities in Nigeria. Journal of Technologies in Society, 12(2), 9–20. https://doi.org/10.18848/2381-9251/cgp/v12i02/9-20
Oziegbe, T. E., Ojugo, A. A., Edje, A. E., & Osezele, A. N. (2026). Convolutional neural network deep learning and digital twin technology for intrusion detection, realtime analytics and digital transformation of the Oil and Gas Industry: a review of literature. FUDMA Journal of Sciences, 10(7), 287–295. https://doi.org/10.33003/fjs-2026-1007-5024
Rahman, K., Hussain, T., Ayaan, S., & Yasmeen, H. (2025). Automated Attendance System Using Opencv With Face And Iris Detection. International Journal of Information Technology and Computer Engineering, 13(2), 285–291. https://doi.org/10.62647/IJITCE2025V13I2sPP285-291
Rangga, D., Zuhdiyanto, O., & Asriningtias, Y. (2026). Real-Time Location Monitoring and Routine Reminders Based on Internet. 5(158), 9–10.
Roy, D. G., Bhattacharjee, A., Das, R., & Das, P. (2025). Trigger Based Smart Attendance Framework with Machine Learning for Predictive Student Performance Analysis. International Journal of Research and Review, 12(May), 321–330.
Salunkhe, A., Pawar, V., Pise, P., Mule, S., Survase, A., Godase, V., & Zambre, S. (2025). A Review on Real-Time RFID-Based Smart Attendance Systems for Efficient Record Management. Advance Research in Analog and Digital Communications, 2(2).
Şentürk, A., & Terazi, S. (2023a). IoT security with blockchain: A review. The European Journal of Research and Development, 3(4), 117–132. https://doi.org/10.56038/ejrnd.v3i4.370
Şentürk, A., & Terazi, S. (2023b). IoT security with blockchain: A review. The European Journal of Research and Development, 3(4), 117–132. https://doi.org/10.56038/ejrnd.v3i4.370
Sheikhtaheri, A., & Sabermahani, F. (2022). Applications and Outcomes of Internet of Things for Patients with Alzheimer’s Disease/Dementia: A Scoping Review. BioMed Research International, 2022(1). https://doi.org/10.1155/2022/6274185
Singh, J., Patel, C., & Chaudhary, N. K. (2022). Resilient Risk based Adaptive Authentication and Authorization (RAD-AA) Framework. https://doi.org/10.48550/arXiv.
Tahir, H. T., Aghaunor, T. C., Ugbotu, E. V., Onoma, P. A., Ojugo, A. A., Abere, R. A., Agboi, J., & Aherobo, O. V. (2025). Enhancing Security with Blockchain-Enabled Privacy Preservation for Multi-and-Hybrid Cloud Environment: A Pilot Study. Advances in Multidisciplinary & Scientific Research Journal Publication, 16(4), 25–44. https://doi.org/10.22624/AIMS/CISDI/V16N4P3
Ugbotu, E. V., Ako, R. E., Odoh, A., Oghorodi, D., Okpako, A. E., Aghaunor, T. C., Emordi, F. U., Ugboh, E., Agboi, J., Odiakaose, C. C., Ojugo, A. A., Geteloma, V. O., Abere, R. A., Idama, R. O., Eboka, A. O., Ezzeh, P. O., Onochie, C. C., Oweimieotu, A. E., Ojo, B., & Onoma, P. A. (2025). Equipping the GREDDIoMT Device with Early Behavioural Risk Detection of Dementia via a Pre-Activated SENet fused BiGRU. Journal of Behavioral Informatics, Digital Humanities and Development Research, 11(3), 36–56. https://doi.org/10.22624/AIMS/BHI/V11N3P4
Ukadike, I. D., Akazue, M. I., Omede, E. U., & Akpoyibo, T. . (2023). Development of an IoT based Air Quality Monitoring System. International Journal of Innovative Technology and Exploring Engineering, 7(4), 53–62. https://doi.org/10.35940/ijitee.J1004.08810S19
Yoro, R. E., Okpor, M. D., Akazue, M. I., Okpako, A. E., Eboka, A. O., Ejeh, P. O., Ojugo, A. A., Odiakaose, C. C., Binitie, A. P., Ako, R. E., Geteloma, V. O., Onoma, P. A., Max-Egba, A. T., Ibor, A. E., Onyemenem, S. I., & Ukwandu, E. (2025). Adaptive DDoS detection mode in software-defined SIP-VoIP using transfer learning with boosted meta-learner. Plos One, 20(6 June), 1–20. https://doi.org/10.1371/journal.pone.0326571
Zhao, Y., & Otteson, A. (2024). AI-Driven Strategies for Reducing Student Withdrawal -- A Study of EMU Student Stopout
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 Reuben Akpos Abere, Adesuwa Inaya, Arnold Adim Ojugo, Paul Avwerosuo Onoma, Ovie Victor Aherobo, Samuel Okperigho, Tabitha Chukwudi Aghaunor, Eferhire Valentin Ugbotu, Kingsley Theo Igulu, Nelson Asheshemi, Emeke Ugboh, Margaret Dumebi Okpor, Taibat Onome Asunogie, Star Umiyeromesu Niemogha
This work is licensed under a Creative Commons Attribution 4.0 International License.
