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Implementation of Object Detection Method for Intelligent Surveillance Systems at the Faculty of Engineering, Universitas Sebelas Maret (UNS) Surakarta Aris Maulana Fauzan; Sutrisno Ibrahim; Meiyanto Eko Sulistyo
Journal of Electrical, Electronic, Information, and Communication Technology Vol 4, No 1 (2022): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.4.1.61197

Abstract

The number of positive Covid-19 cases in Indonesia continue to increase. This increase influenced by the behavior of Indonesian citizens in dealing with the pandemic, one of which is rarely wearing masks. In this study, we implemented an object detection method for intelligent surveillance systems (ISS) at the Faculty of Engineering, Universitas Sebelas Maret (UNS), Surakarta. By implementing face detection and mask detection, the surveillance system can recognize whether a person in a CCTV video frame is wearing a mask or not. In addition, deep metric learning and histogram of gradient (HOG) are applied to recognize faces of unmasked people in images. The test results show that the surveillance system can recognize the use of masks with 75%-87% accuracy rate. Furthermore, the accuracy rate for facial recognition on images ranges from 69% -100% for each person
AR-NAVIS: Mobility Application for Blind and Deaf Students Based on Augmented Reality Joko Slamet Saputro; Gunardi Gunardi; Fadjri Kirana Anggarani; Najya Anastasya; Reva Setiabudi; Sutrisno Ibrahim
Journal of Electrical, Electronic, Information, and Communication Technology Vol 6, No 1 (2024): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.6.1.85475

Abstract

Students with disabilities, especially those with visual and hearing impairments, face challenges in navigating through the campus environment. Hence, the development of AR-NAVIS as an Augmented Reality (AR)-based mobility orientation application stands as a significant innovation in providing services for them. This application aims to assist disabled students in moving within the campus environment, both indoors and outdoors. AR-NAVIS identifies the safest and most efficient routes, enabling disabled students to engage in independent activities and enhancing both their academic and non-academic performance. The application development process involves analyzing students' needs, prototype design, model validation, trials, and dissemination. Its features include AR-based 3D guidance, directional text, voice, vibration mode, and hazard information. The app is expected to provide accurate information about buildings or locations that are the destination for disabilities students. The result show that application development can guide disabilities user move between buildings smoothly. The experiment found that there was an increase in student activity after having this application.