Raed Abdulla, Raed
Asia Pacific University of Technology and Innovation (APU)

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Predictive maintenance of rotational machinery using deep learning Ali, Mohamed Iyad; Lai, Nai Shyan; Abdulla, Raed
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1112-1121

Abstract

This paper describes an implementation of a deep learning-based predictive maintenance (PdM) system for industrial rotational machinery, built upon the foundation of a long short-term memory (LSTM) autoencoder and regression analysis. The autoencoder identifies anomalous patterns, while the latter, based on the autoencoder’s output, estimates the machine’s remaining useful life (RUL). Unlike prior PdM systems dependent on labelled historical data, the developed system doesn’t require it as it’s based on an unsupervised deep learning model, enhancing its adaptability. The paper also explores a robust condition monitoring system that collects machine operational data, including vibration and current parameters, and transmits them to a database via a Bluetooth low energy (BLE) network. Additionally, the study demonstrates the integration of this PdM system within a web-based framework, promoting its adoption across various industrial settings. Tests confirm the system's ability to accurately identify faults, highlighting its potential to reduce unexpected downtime and enhance machinery reliability.
IoT based on secure personal healthcare using RFID technology and steganography Khan, Haider Ali; Abdulla, Raed; Selvaperumal, Sathish Kumar; Bathich, Ammar
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3300-3309

Abstract

Internet of things (IoT) makes it attainable for connecting different various smart objects together with the internet. The evolutionary medical model towards medicine can be boosted by IoT with involving sensors such as environmental sensors inside the internal environment of a small room with a specific purpose of monitoring of person's health with a kind of assistance which can be remotely controlled. RF identification (RFID) technology is smart enough to provide personal healthcare providing part of the IoT physical layer through low-cost sensors. Recently researchers have shown more IoT applications in the health service department using RFID technology which also increases real-time data collection. IoT platform which is used in the following research is Blynk and RFID technology for the user's better health analyses and security purposes by developing a two-level secured platform to store the acquired data in the database using RFID and Steganography. Steganography technique is used to make the user data more secure than ever. There were certain privacy concerns which are resolved using this technique. Smart healthcare medical box is designed using SolidWorks health measuring sensors that have been used in the prototype to analyze real-time data.