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All Journal Brilliance: Research of Artificial Intelligence
Popy Maria
Department of Electrical Engineering, Telecommunication Engineering Study Program, Padang State Polytechnic
Decision Sciences, Operations Research & Management Mathematics Other

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Fiber Optical Network Damage Detection Passive Splitter 1:8 in ODC uses IOT Technology as a means of Real Time Reporting Aprinal Adila Asril; Uzma Septima; Ratna Dewi; Popy Maria; Deri Latika Herda
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.2966

Abstract

Fiber optic networks currently have a lot of interest, so a network monitoring system is needed that guarantees quality and speed of repair if mass disruption occurs. in research [1] regarding fiber network damage detection using IoT with the use of a 1:4 splitter and the use of a detector that can work at a wavelength of 650nm so that it can detect damaged cables with output in the software. So in connection with this, the author wants to develop the results of this research by using a 1:8 splitter and carrying out detection using the LDR sensor and NodeMCU ESP32 using IoT (Internet of Things) technology. The ESP32 NodeMCU will receive data in the form of light intensity values ??at each ODC from the LDR sensor. And then sent to a database that is connected directly to the Android application. The cable identification process occurs in three states: normal, warning, and error. The test and analysis results show that the hardware device can work well, with attenuation in the passive splitter cable of 10.28 dB and a light source with a wavelength of 650 nm. Cable detected as damaged is indicated by an output in the software with a delay of 4.56 s.
Installation and Activation of Fiber To The Home (FTTH) Networks and Macrobending Problems in the Feeder Cable Segment Yustini; Aprinal Adila Asril; Herry Setiawan; Popy Maria; Silfia Rifka
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.2967

Abstract

Macrobending is a form of disturbance in Fiber To The Home (FTTH) networks that occurs due to macro-level bending of the cable caused by damage to the fiber optic. Macrobending frequently occurs in FTTH networks within the feeder cables. Feeder cables serve as connectors between the Optical Line Terminal (OLT) and Optical Distribution Cabinet (ODC) in the FTTH system. The occurrence of macrobending in feeder cables affects the quality of the FTTH network. In this study, the impact of macrobending is analyzed based on curvature diameters of 50 cm, 25 cm, and 5 cm on feeder cables before and after FTTH network activation. Before FTTH network activation, the High Super Luminescent Diode (HSL) is used as the input power source, whereas after activation, the input power source comes from the OLT using Small Form-factor Pluggable (SFP) modules. The attenuation (loss) before activation due to macrobending, with curvature diameters of 50 cm, 25 cm, and 5 cm, is found to be 0.02 dB, 0.05 dB, and 0.26 dB, respectively. After activation, the attenuation with the same curvature diameters is measured as 0.01 dB, 0.02 dB, and 0.20 dB, respectively. It is observed that as the curvature diameter decreases, the attenuation increases. The comparison of attenuation before and after network activation doesn't show a significant difference because the input power doesn't affect macrobending, rather it is influenced by the curvature diameter.
Co-Authors Aprinal Adila Asril Deri Latika Herda Herry Setiawan Ratna Dewi Silfia Rifka Uzma Septima - Yustini