Hasmah Mansor
International Islamic University Malaysia

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Performance Evaluation of Smart Home System using Internet of Things Teddy Surya Gunawan; Intan Rahmithul Husna Yaldi; Mira Kartiwi; Hasmah Mansor
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1117.986 KB) | DOI: 10.11591/ijece.v8i1.pp400-411

Abstract

Nowadays, many researches have been conducted on smart home. Smart home control system (SHCS) can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. We have proposed a smart home system using internet of things and four types of sensors, including PIR, temperature, ultrasonic, and smoke gas sensor for automatic environmental control and intrustion detection. In this paper, the performance of the previously developed prototype of smart home system will be evaluated. First, experiments on various sensors will be conducted. Next, the communicaton channel using wireless and Ethernet modules will be discussed. Moreover, the overall SHCS will be evaluated in terms of hardware and software performance. Additionaly, solar charger enhances the availability of our prototype system. Results showed the effectiveness of our proposed smart home system in the prototype and real life experiments.
Design and Implementation of Portable Outdoor Air Quality Measurement System using Arduino Teddy Surya Gunawan; Yasmin Mahira Saiful Munir; Mira Kartiwi; Hasmah Mansor
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (755.272 KB) | DOI: 10.11591/ijece.v8i1.pp280-290

Abstract

Recently, there is increasing public awareness of the real time air quality due to air pollution can cause severe effects to human health and environments. The Air Pollutant Index (API) in Malaysia is measured by Department of Environment (DOE) using stationary and expensive monitoring station called Continuous Air Quality Monitoring stations (CAQMs) that are only placed in areas that have high population densities and high industrial activities. Moreover, Malaysia did not include particulate matter with the size of less than 2.5μm (PM2.5) in the API measurement system. In this paper, we present a cost effective and portable air quality measurement system using Arduino Uno microcontroller and four low cost sensors. This device allows people to measure API in any place they want. It is capable to measure the concentration of carbon monoxide (CO), ground level ozone (O3) and particulate matters (PM10 & PM2.5) in the air and convert the readings to API value. This system has been tested by comparing the API measured from this device to the current API measured by DOE at several locations. Based on the results from the experiment, this air quality measurement system is proved to be reliable and efficient.
A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.859 KB) | DOI: 10.11591/eei.v8i4.1645

Abstract

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.
A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.859 KB) | DOI: 10.11591/eei.v8i4.1645

Abstract

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.
A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.859 KB) | DOI: 10.11591/eei.v8i4.1645

Abstract

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.
Design of travel angle control of quanser bench-top helicopter using mamdani-based fuzzy logic controller Hasmah Mansor; Mohamad K. Azmi Mat Esa; Teddy Surya Gunawan; Zuriati Janin
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp815-825

Abstract

This research focuses on travel angle control of a laboratory scale bench-top helicopter developed by Quanser Inc.  Bench top-helicopter is usually used by engineers and researchers to test their designed controllers before applying to the actual helicopter. Bench-top helicopter has the same behavior as the real helicopter, with 3 degree of freedom.  The bench-top helicopter is mounted on a flat surface with two rotors that depends on the voltage supplied to change the direction of the helicopter in 3 different angles. The movement of the helicopter is based on the direction of three-different angles; travel, pitch and yaw angles. The existing Linear Quadratic Regulator-Integral controller used by Quanser Inc has some limitations in terms of tracking capability and settling time; therefore this research is proposed. The objective of this research is to develop Mamdani-based Fuzzy Logic Controller for travel angle control of bench-top helicopter. Performance comparison has been done with the existing Linear Quadratic Regulator-Integral controller in both simulation and hardware. From the test results, it was found that the performance of Fuzzy Logic Controller is better than LQR-I controller especially for closed-loop simulation at desired angle of 30°. The percentage of overshoot of the Fuzzy Logic Controller has been improved from the existing controller which is 4.912% compared to 7.002% for LQR-I.
Development of Approximate Prediction Model for 3-DOF Helicopter and Benchmarking with Existing Controllers Farhat Anwar; Rounakul Islam Boby; Hasmah Mansor; Sabahat Hussain; Afsah Sharmin
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp502-510

Abstract

Recent trend of living is getting modernized rapidly by the involvement of automatic systems. Within the aviation industry, automatic systems had become heavily reliable by the end of the nineteen centuries. The systems usually require controllable devices with desired control algorithm known as controller. Controllers can be replaced with, almost every mechanical automation aspect where, safety is a serious issue. But it is not easy to adapt a controller with a specific model at the beginning. It is important to predict the model before a controller works on the model and the controller parameters need to be adapted to get maximum efficiency. A 3-DOF (Three Degrees of Freedom) airframe model is an advanced benchmark model of real 3-DOF helicopter. It has the same uncommon model dynamics with nonlinearities, strong duel motor cross coupling system, uncertain characteristics, disturbances dependent, unmodeled dynamics and many more. The 3-DOF airframe model is a well-known platform for controller performance benchmarking. This research paper shows the development of an approximate prediction model of a Three Degrees of Freedom helicopter model and uses the proposed approximate model to observe the performance of an existent hybrid controller. The hybrid controller is the combination of two different controllers named Quantitative Feedback Theory (QFT) controller and Adaptive controller. To achieve the research objective, the proposed mathematical model of this airframe was used to develop transfer function and simulate with the hybrid controller in MATLAB. The performance of the controller based on the proposed heliframe model of 3-DOF helicopter have also been reported added within this paper.
Neural Network Prediction for Efficient Waste Management in Malaysia Siti Hajar Yusoff; Ummi Nur Kamilah Abdullah Din; Hasmah Mansor; Nur Shahida Midi; Syasya Azra Zaini
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp738-747

Abstract

Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on population growth factor. This study uses Malaysian population as sample size and the data for weight is acquired via authorized Malaysia statistics’ websites. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with ten and five nodes were used respectively. The result portrayed that there will be an increase of 29.03 percent of SWG in year 2031 compared to 2012. The limitation to this study is that the data was not based on real time as it was restricted by the government.
Design of Smart Waste Bin and Prediction Algorithm for Waste Management in Household Area Siti Hajar Yusoff; Ummi Nur Kamilah Abdullah Din; Hasmah Mansor; Nur Shahida Midi; Syasya Azra Zaini
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp748-758

Abstract

Maintaining current municipal solid waste management (MSWM) for the next ten years would not be efficient anymore as it has brought many environmental issues such as air pollution. This project has proposed Artificial Neural Network (ANN) based prediction algorithm that can forecast Solid Waste Generation (SWG) based on household size factor. Kulliyyah of Engineering (KOE) in International Islamic University Malaysia (IIUM) has been chosen as the sample size for household size factor. A smart waste bin has been developed that can measure the weight, detect the emptiness level of the waste bin, stores information and have direct communication between waste bin and collector crews. This study uses the information obtained from the smart waste bin for the waste weight while the sample size of KOE has been obtained through KOE’s department. All data will be normalized in the pre-processing stage before proceeding to the prediction using Visual Gene Developer. This project evaluated the performance using R2 value. Two hidden layers with five and ten nodes were used respectively. The result portrayed that the average rate of increment of waste weight is 2.05 percent from week one until week twenty. The limitation to this study is that the amount of smart waste bin should be replicated more so that all data for waste weight is directly collected from the smart waste bin.
Development of Quran Reciter Identification System Using MFCC and Neural Network Tayseer Mohammed Hasan Asda; Teddy Surya Gunawan; Mira Kartiwi; Hasmah Mansor
Indonesian Journal of Electrical Engineering and Computer Science Vol 1, No 1: January 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v1.i1.pp168-175

Abstract

Currently, the Quran is recited by so many reciters with different ways and voices.  Some people like to listen to this reciter and others like to listen to other reciters. Sometimes we hear a very nice recitation of al-Quran and want to know who the reciter is. Therefore, this paper is about  the development of Quran reciter recognition and identification system based on Mel Frequency Cepstral Coefficient (MFCC) feature extraction and artificial neural network (ANN). From every speech, characteristics from the utterances will be extracted through neural network model. In this paper a database of five Quran reciters is created and used in training and testing. The feature vector will be fed into Neural Network back propagation learning algorithm for training and identification processes of different speakers. Consequently,  91.2%  of the successful match between targets and input occurred with certain number of hidden layers  which shows how efficient are Mel Frequency Cepstral Coefficient (MFCC) feature extraction  and artificial neural network (ANN) in identifying the reciter voice perfectly.