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All Journal International Journal of Electrical and Computer Engineering International Journal of Informatics and Communication Technology (IJ-ICT) Proceeding of the Electrical Engineering Computer Science and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Sallehuddin Ibrahim
Universiti Teknologi Malaysia
Computer Science & IT Electrical & Electronics Engineering

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 1 
Optical Tomography Sensor Configuration for Estimating the Turbidity Level of Water Mohd Taufiq Mohd Khairi; Sallehuddin Ibrahim; Mohd Amri Md Yunus; Mohd Najmi Mohd Sulaiman; Mahdi Faramarzi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 3, No 3: December 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (689.388 KB) | DOI: 10.11591/ijict.v3i3.pp153-161

Abstract

This paper presents an investigation on an optical sensor configuration to estimate the turbidity level in a sample of water based on tomography technique. The optical sensors consist of infrared light - emitting diodes (LED) as transmitters and photodiodes as the receivers where the projections of the sensors are designed in fan beam mode. The promising results obtained from the analysis of light path detection demonstrated the accuracy of the proposed technique in estimating the turbidity level of water. The approach has potential to contribute and utilize for monitoring the quality level of water in water treatment industries.
An Ultrasonic System for Determining Mango Physiological Properties Sallehuddin Ibrahim; Mohd Amri Md Yunus; Mohd Taufiq Md Khairi; Aini Hazwani Mohd Zelan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.186 KB) | DOI: 10.11591/eecsi.v2.784

Abstract

There is an increasing requirement for high qualityfruits such as mango. Hence it is vital to have a fast, accurate andreliable method for measuring and monitoring the quality of fruitfrom the field to the consumer. This paper presents aninvestigation on the use of an ultrasonic measurement system fordetermining the quality of mango.
Artificial Neural Network for Non-Intrusive Electrical Energy Monitoring System Khairell Khazin Kaman; Mahdi Faramarzi; Sallehuddin Ibrahim; Mohd Amri Md Yunus
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 1: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i1.pp124-131

Abstract

 This paper discusses non-intrusive electrical energy monitoring (NIEM) system in an effort to minimize electrical energy wastages. To realize the system, an energy meter is used to measure the electrical consumption by electrical appliances. The obtained data were analyzed using a method called multilayer perceptron (MLP) technique of artificial neural network (ANN). The event detection was implemented to identify the type of loads and the power consumption of the load which were identified as fan and lamp. The switching ON and OFF output events of the loads were inputted to MLP in order to test the capability of MLP in classifying the type of loads. The data were divided to 70% for training, 15% for testing, and 15% for validation. The output of the MLP is either ‘1’ for fan or ‘0’ for lamp. In conclusion, MLP with five hidden neurons results obtained the lowest average training time with 2.699 seconds, a small number of epochs with 62 iterations, a min square error of 7.3872×10-5, and a high regression coefficient of 0.99050.
Detection of foreign objects in milk using an ultrasonic system Mohd Taufiq Mohd Khairi; Sallehuddin Ibrahim; Mohd Amri Md Yunus; Ahmad Ridhwan Wahap
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1241-1249

Abstract

This paper presents the utilization of an ultrasonic sensing system to detect foreign objects in milk. The advantage of an ultrasonic system is that it is low cost and it can detect a wide range of materials. A foreign body is any contaminated object found in food. Because of the scale of multifarious food processing levels and distribution, the utilization of the food product are sometimes difficult to control, which will inevitably lead to some complaints by consumers. Milk is widely consumed in the world as it is considered as a healthy drink due to it is high nutrients levels. However, from time to time cases of milk contamination are reported. In this paper. the relationship between the foreign bodies in terms of their dimensions and the resultant amplitude are presented. Mathematical modelling were carried out based on two ultrasonic parameters i.e. acoustic impedance and wave amplitude utilizing several types of foreign bodies with different dimensions. Three types of foreign bodies which are steel, rubber and air were investigated to determine the voltage amplitude detected by the ultrasonic receiver when the foreign bodies obstructed the ultrasonic wave propagation path. The diameters of foreign bodies were in the range from 4 mm to 11 mm. The results showed good correlations between the receiver voltage and the size of foreign bodies with correlation coefficients greater than 0.95. Each foreign body also demonstrated different voltage amplitudes when several sizes of the foreign bodies were tested which showed the ability of the system to distinguish the size of each foreign body.
An assessment of stingless beehive climate impact using multivariate recurrent neural networks Noor Hafizah Khairul Anuar; Mohd Amri Md Yunus; Muhammad Ariff Baharudin; Sallehuddin Ibrahim; Shafishuhaza Sahlan; Mahdi Faramarzi
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp2030-2039

Abstract

A healthy bee colony depends on various elements, including a stable habitat, a sufficient source of food, and favorable weather. This paper aims to assess the stingless beehive climate data and examine the precise short-term forecast model for hive weight output. The dataset was extracted from a single hive, for approximately 36-hours, at every seven seconds time stamp. The result represents the correlation analysis between all variables. The evaluation of root-mean-square error (RMSE), as well as the RMSE performance from various types of topologies, are tested on four different forecasting window sizes. The proposed forecast model considers seven of input vectors such as hive weight, an inside temperature, inside humidity, outside temperature, outside humidity, the dewpoint, and bee count. The various network architecture examined for minimal RMSE are long short-term memory (LSTM) and gated recurrent units (GRU). The LSTM1X50 topology was found to be the best fit while analyzing several forecasting windows sizes for the beehive weight forecast. The results obtained indicate a significant unusual symptom occurring in the stingless bee colonies, which allow beekeepers to make decisions with the main objective of improving the colony’s health and propagation.
Co-Authors Ahmad Ridhwan Wahap Aini Hazwani Mohd Zelan Khairell Khazin Kaman Mahdi Faramarzi Mahdi Faramarzi Mohd Amri Md Yunus Mohd Najmi Mohd Sulaiman Mohd Taufiq Md Khairi Mohd Taufiq Mohd Khairi Muhammad Ariff Baharudin Noor Hafizah Khairul Anuar Shafishuhaza Sahlan