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Djauhari, Teuku
Faculty Of Computer Science Universitas Nurdin Hamzah
Aerospace Engineering Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : Internet of Things and Artificial Intelligence Journal

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Smart Hotel Security: Integrating AI for Advanced Safety Solutions Rahmawati, Noni; Djauhari, Teuku
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 1 (2025): Volume 5 Issue 1, 2025 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i1.787

Abstract

Security systems are essential for hotels and lodging services, considering that this lodging service is a service that is intended for all people from various circles and from anyone who comes from various places, this is very common and dangerous, in terms of security and comfort. Several security systems are built by hotels, such as CCTV and security systems on doors and various security system techniques such as retina, fingerprint, RFID, and various security techniques. Not only at the door but safety boxes are made with various locking techniques from a combination of numbers. In addition to hardware, software with enhanced capabilities in Artificial Intelligence can also be applied such as face detection, predictive analysis, and automated surveillance. The combination of hardware such as Jetson Nano and software can be improved to build AI-based security systems in creating security systems in hotels that can be built professionally and smartly. Some methods developed in the face detection system of a person trying to enter a hotel room to commit theft, for example, are using Convolutional Neural Network (CNN). The developed system can detect predictions of age, gender, and other parameters.
Co-Authors -, Sailani Afif Rahman Riyanda Ahadi, Ahmad Husna Ahmad Husna Ahadi Aktan, Rizky Nurman Aminuddin, Fattachul Huda Angga Angga Arjansyah, Arnol BAHRI, FAISAL Brestina Gultom Chandra Kusuma darex susanto, darex Dede, Alan Dede, Alan Ezrifal Sany Fattachul Huda Aminuddin Fitra Novriadi Gustina Gustina Gustina Gustina Gustinar Gwandy Rianto, Muhammad Huda Aminuddin, Fattachul Husna Ahadi, Ahmad Imti Tsalil Amri Irfandi, Baso Junaidi Surya, Junaidi Kasih Adinda S. Merti Megawaty Merty Megawati M.Pd MULYADI Mulyadi Rusli Noni Rahmawati Novriadi, Fitra Pariyadi, Pariyadi Rahmawati, Noni Rizky Nurman Aktan Santoso Santoso Santoso Santoso Santoso Setiawan Assegaf Windy Adriana Yandi Anzari