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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Advances in Intelligent Informatics
Khairun Nidzam Ramli
Universiti Tun Hussein Onn Malaysia
Computer Science & IT

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Cable fault classification in ADSL copper access network using machine learning Nurul Bashirah Ghazali; Dang Fillatina Hashim; Fauziahanim Che Seman; Khalid Isa; Khairun Nidzam Ramli; Zuhairiah Zainal Abidin; Saizalmursidi Md Mustam; Mohammed Al Haek
International Journal of Advances in Intelligent Informatics Vol 7, No 3 (2021): November 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v7i3.488

Abstract

Asymmetrical Digital Subscriber Line (ADSL) is the technology widely deployed worldwide, but its performance may be limited with respect to its intrinsic. The nature of the copper cable causes it to be more susceptible to signal degradation and faulty line. Common ADSL line faults are short-wired fault, open-wired fault, bridge taps, and uneven pair. However, ADSL technology is still one of the most established networks, and users in the suburban area still depend on the technology to access the internet service. This paper discussed and compared a machine learning algorithm based on Decision Trees (J48), K-Nearest Neighbor, Multi-level Perceptron, Naïve Bayes, Random Forest, and Sequential Minimal Optimization (SMO) for ADSL line impairment that affects the line operation performance concerning their percentage of accuracy. Resulting from classifications done using algorithms as mentioned above, the random forest algorithm gives the highest overall accuracy for the ADSL line impairment dataset. The best algorithm for classifying DSL line impairment is chosen based on the highest accuracy percentage. The accomplishment classification of fault type in the ADSL copper access network project may benefit the telecommunication network provider by remotely assessing the network condition rather than on-site.
High accuracy sensor nodes for a peat swamp forest fire detection using ESP32 camera Shipun Anuar Hamzah; Mohd Noh Dalimin; Mohamad Md Som; Mohd Shamian Zainal; Khairun Nidzam Ramli; Wahyu Mulyo Utomo; Nor Azizi Yusoff
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i3.pp229-239

Abstract

The use of smoke sensors in high-precision and low-cost forest fire detection kits needs to be developed immediately to assist the authorities in monitoring forest fires especially in remote areas more efficiently and systematically. The implementation of automatic reclosing operation allows the fire detector kit to distinguish between real smoke and non-real smoke successfully. This has profitably reduced kit errors when detecting fires and in turn prevent the users from receiving incorrect messages. However, using a smoke sensor with automatic reclosing operation has not been able to optimize the accuracy of identifying the actual smoke due to the working sensor node situation is difficult to predict and sometimes unexpected such as the source of smoke received. Thus, to further improve the accuracy when detecting the presence of smoke, the system is equipped with two digital cameras that can capture and send pictures of fire smoke to the users. The system gives the users choice of three interesting options if they want the camera to capture and send pictures to them, namely request, smoke trigger and movement for security purposes. In all cases, users can request the system to send pictures at any time. The system equipped with this camera shows the accuracy of smoke detection by confirming the actual smoke that has been detected through images sent in the user’s Telegram channel and on the Graphical User Interface (GUI) display. As a comparison of the system before and after using this camera, it was found that the system that uses the camera gives advantage to the users in monitoring fire smoke more effectively and accurately.
Co-Authors Dang Fillatina Hashim Fauziahanim Che Seman Khalid Isa Mohamad Md Som Mohammed Al Haek Mohd Noh Dalimin Mohd Shamian Zainal Nor Azizi Yusoff Nurul Bashirah Ghazali Saizalmursidi Md Mustam Shipun Anuar Hamzah Wahyu Mulyo Utomo Zuhairiah Zainal Abidin