The Studying of Security Systems within Organizations using Digital Technology
Keywords:
security, digital technology, demand educationAbstract
This article presents a study of security systems within organizations using digital technology. The objective to study needs and apply the results of studies of security systems within organizations using digital technology to design systems for use. In this article, the researcher asked about the needs of three sample groups: When asked about the requirements for an internal security system using digital technology, it consists of 32 government, private sector personnel 38 people and 30 personnel from state-owned enterprises, totaling 100 people. The questionnaire has been evaluated for the quality of the tool by 3 experts, who are of the opinion that it is consistent with all objectives. The results of the evaluation responses found that personnel's needs for the system are in the highest level of demand. (x =4.75, S.D. 0.69)
References
Office of the National Strategy Committee Secretary, National Strategy 2018-2037 (abbreviated version).
A. Latifah, S. H. Supangkat and A. Ramelan, “Smart Building: A Literature Review,” International Conference on ICT for Smart Society (ICISS), 2022, DOI: 10.1109/ICISS50791.2020.9307552
X. Zhou, K. Sun, J. Wang, J. Zhao and Ch. Feng, “Computer Vision Enabled Building Digital Twin Using Building Information Model,” IEEE Transactions on Industrial Informatics, Volume 19, Issue 3, pp. 2684 - 2692, 2022 DOI: 10.1109/TII.2022.3190366
H. Qi, CH. Wu, Y. Shi, X. Qi, K. Duan and X. Wang, “A Real-Time Face Detection Method Based on Blink Detection,” Research Article, vol.11, pp. 28180-28189. 2023.
Raman, “Multiscale Facial Expression Based Face Recognition using Normalized Segment Classification Detection in Face Images,” International Conference on Advanced Computing and Communication Systems, pp. 2381-2386. 2023.
S.R. Mokalla and Th. Bourlai, “Utilizing Alignment Loss to Advance Eye Center Detection and Face Recognition in the LWIR Band,” IEEE Transaction on Biometrics Behavior and Identity Science, vol. 5, no. 2, pp. 255-265. 2023.
A.K. Sirivarshitha, K. Sravani, K.S. Priya and V. Bhavani, “An approach for Face Detection and Face Recognition using OpenCV and Face Recognition Libraries in Python,” International Conference on Advanced Computing and Communication Systems, pp. 1274-1278. 2023.
D.A.R. Wati, “Design of Face Detection and Recognition System for Smart Home Security Application,” International Conferences on Information Technology and Electrical Engineering, pp. 342-347. 2017.
J. Sun, S. Xia, Z. Sun and S. Lu, “Cross-Model Deep Feature Fusion for Face Detection,” IEEE Sensor Letter, vol.4(9). 2020.
J. Sainui, N. Jankaew and H. U-seng, “A prototype of seminar registration system using face authentication, Academic,” Journal of Information Technology Applications (in Thai), pp. 40-50. 2021.
S. Potha, “Development of a Student Attendance System using Face Detection Technique on Raspberry Pi,” Thesis Faculty of Engineering (in Thai), Chaing Mai University. 2021.
Y. Feng, S. Yu, H. Peng, Y. R. Li and J. Zhang, “Detect Faces Efficiently: A Survey and Evaluations,” IEEE Transaction on Biometrics Behavior and Identity Science, vol. 4(1). 2022.
A. A. B. Abdul Aziz and A. Bajpai, “Attire-Based Anomaly Detection in Restricted Areas Using YOLOv8 for Enhanced CCTV Security,” arXiv preprint arXiv:2404.00645, Mar. 2024.
