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Cited by 1Artificial Intelligence in EducationVideo Surveillance and Tracking MethodsTechnology and Security Systems

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

AI-Driven Innovations for Comprehensive Campus-Wide Monitoring Support Services

Yahaya, Wan Ahmad Jaafar Wan, Muhammad, Yahaya·2025·Advances in Science, Technology & Innovation
DOI 10.1007/978-3-031-56848-0_11
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Citations

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Research works printed but not linked: 14

  1. Agrawal, V. (2022). Demystifying the Chinese Social Credit System: A Case Study on AI-Powered Control Systems in China. https://socialcredit.triviumchina.com/reports/. · doi:10.1609/aaai.v36i11.21698
  2. Ardabili, B. R., Pazho, A. D., Noghre, G. A., Neff, C., Bhaskararayuni, S. D., Ravindran, A., Reid, S., & Tabkhi, H. (2023). Understanding Policy and Technical Aspects of AI-enabled Smart Video Surveillance to Address Public Safety. Computational Urban Science, 3(1). https://doi.org/10.1007/s43762-023-00097-8 · DOI
  3. Bañeres, D., Rodríguez, M. E., Guerrero-Roldán, A. E., & Karadeniz, A. (2020). An early warning system to detect at-risk students in online higher education. Applied Sciences (Switzerland), 10(13). https://doi.org/10.3390/app10134427 · DOI
  4. Doohan, N. V., Kadam, S., Phursule, R., Wadne, V. S., & Junnarkar, A. (2022). Implementation of AI based Safety and Security System Integration for Smart City. International Journal of Electrical and Electronics Research, 10(3), 518–522. https://doi.org/10.37391/IJEER.100319 · DOI
  5. Eisenkraft, A., Goldstein, N., Merin, R., Fons, M., Ishay, A. Ben, Nachman, D., & Gepner, Y. (2023). Developing a real-time detection tool and an early warning score using a continuous wearable multi-parameter monitor. Frontiers in Physiology, 14. https://doi.org/10.3389/fphys.2023.1138647 · DOI
  6. Ferretti, L., Wymant, C., Kendall, M., Zhao, L., Nurtay, A., Abeler-Dörner, L., Parker, M., Bonsall, D., & Fraser, C. (2020). AI Surveillance during Pandemics: Ethical Implementation Imperatives. Science, 368(6491). https://doi.org/10.1126/science.abb6936 · DOI · Paper page
  7. Fontes, C., Hohma, E., Corrigan, C. C., & Lütge, C. (2022). AI-powered public surveillance systems: why we (might) need them and how we want them. Technology in Society, 71. https://doi.org/10.1016/j.techsoc.2022.102137 · DOI
  8. Gupta, A., & Prabhat, P. (2023). Towards a resource efficient and privacy-preserving framework for campus-wide video analytics-based applications. Complex and Intelligent Systems, 9(1), 161–176. https://doi.org/10.1007/s40747-022-00783-w · DOI
  9. Lees’ Loss. (2012). Human Factors and Human Error. In Loss Prevention in the Process Industries (pp. 687–751). Elsevier. https://doi.org/10.1016/b978-0-12-397189-0.00014-8 · doi:10.1016/b978-0-12-397189-0.00014-8
  10. Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organisational creativity and firm performance. Information and Management, 58(3). https://doi.org/10.1016/j.im.2021.103434 · DOI · Paper page
  11. Raimundo, R., & Rosário, A. (2021). The impact of artificial intelligence on data system security: A literature review. In Sensors (Vol. 21, Issue 21). MDPI. https://doi.org/10.3390/s21217029 · DOI
  12. Şengönül, E., Samet, R., Abu Al-Haija, Q., Alqahtani, A., Alturki, B., & Alsulami, A. A. (2023). An Analysis of Artificial Intelligence Techniques in Surveillance Video Anomaly Detection: A Comprehensive Survey. In Applied Sciences (Switzerland) (Vol. 13, Issue 8). MDPI. https://doi.org/10.3390/app13084956 · DOI
  13. Stahl, B. C. (2021). Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies. http://www.springer.com/series/13811 · DOI · Paper page
  14. Wang, M., Song, G., Yu, Y., & Zhang, B. (2023). The Current Research Status of AI-Based Network Security Situational Awareness. In Electronics (Switzerland) (Vol. 12, Issue 10). MDPI. https://doi.org/10.3390/electronics12102309 · DOI

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Metadata

Authors
Yahaya, W. A. J. W., & Muhammad, Y.
Corresponding author
Yahaya, Wan Ahmad Jaafar Wan
ORCID
Venue
Advances in Science, Technology & Innovation
Publisher
Springer Nature Switzerland
Published
2025
Pages
99-105
ISSN
  • 2522-8714 (ISSN-L)
  • 2522-8722
DOI
10.1007/978-3-031-56848-0_11
OpenAlex
W4412102860
Cited by
0
References
1
FWCI
0.00
Type
book chapter
Language
en
Open access
closed
Licence
Locations
Advances in Science, Technology & Innovation/Advances in science, technology & innovation (publishedVersion)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Computer Science › Information Systems › Technology and Security Systems
Keywords
campus safety, intelligent monitoring system, predictive analytics, anomaly detection, natural language processing, security threat detection, emergency response systems, educational institutions, real-time monitoring

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CoChat. (2026). Citation check: AI-Driven Innovations for Comprehensive Campus-Wide Monitoring Support Services. https://app.cochat.ai/papers/10.1007/978-3-031-56848-0_11
The paper
Yahaya, W. A. J. W., & Muhammad, Y. (2025). AI-Driven Innovations for Comprehensive Campus-Wide Monitoring Support Services. Advances in Science, Technology & Innovation. https://doi.org/10.1007/978-3-031-56848-0_11

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.