Mohd Ilman Jais
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Preferred name
Mohd Ilman Jais
Official Name
Mohd Ilman , Jais
Alternative Name
Jais, Mohd I.
Jais, M. I.
Jais, Mohd Ilman
Main Affiliation
Scopus Author ID
17434740200
Researcher ID
AAY-6716-2021

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A multilayered acoustic signal generator for low power energy harvesting

2017-10-10 , Awal M.R. , Muzammil Jusoh , Hasliza A Rahim @ Samsuddin , Thennarasan Sabapathy , Mohamed Nasrun Osman , Mohd Ilman Jais , Kamarudin M.R.

This paper presents the design and analysis of a multilayer cantilever to harvest vibration energy by generating acoustic signal. To do so, a five layer configuration is used to design the cantilever. Lead Zirconate Titanate (PZT-8), Stainless Steel 405 Annealed, Aluminum and Zinc Oxide are used to develop the layers. Water is used as the medium to analyze the sound propagation pattern. Sound Pressure Level, displacements and electric potential of the cantilever are analyzed along with other parameters. From the results, it is evident that, the proposed cantilever can propagate sound within a range of 78.7 dB to 73.4 dB in a 50 mm spherical distance.

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Angle of arrival estimation system for radiation pattern reconfigurable antenna with modified gaussian membership function

2018 , Mohd Ilman Jais

This research focuses on developing angle of arrival (AOA) estimation system (AES) through incoming received signal strength indication (RSSI). Proposed AES is developing on a single board computer (SBC) using an open source GNU Linux operating system (OS). The good AOA estimation systems must able to covered 360° with many estimation points. However, previous AOA estimation systems prototype suffers from a major drawback to achieve 360° angle covered due to limitation of antenna radiation pattern. Therefore, radiation pattern reconfigurable (RPR) antenna operates at 2.45 GHz that capable to cover the wide AOA estimation angle is introduced. Nevertheless, the RPR antenna on AES prototype provides lack of estimation points. Thus, this thesis infuses Fuzzy Inference System (FIS) to further improve decision making and increase the number of AOA estimation points. The FISAES is the first effort in realizing the advantages of FIS with only three sets of RPR antenna abilities without any intelligent algorithm support to cover 360° angle estimation. The FIS-AES algorithm is develop by Python 2.7 programming supported by SciKit library. The proposed Fuzzy Inference System of AOA estimation system (FIS-AES) successfully increases number of estimation from nine to 18 estimation points. Four types of membership function (MF) are trained to obtain response between fuzzifier and defuzzfier of FIS-AES algorithm. A novel MF based Gaussian-MF curve named as the Pattern-MF is introduced. The response between fuzzifier and defuzzfier of FIS-AES algorithm of proposed Pattern-MF approximately ~80% to ~85%, which is the highest compared than existed MF in SciKit library. Moreover, adopted the FIS offers more AOA estimation points, thus it helps FIS-AES capable to improve the absolute error of AOA estimation and root mean square error (RMSE) is ±5° and less than 10 respectively. The investigation of SBC performance is important to verify that SBC competent to act as the main platform of AES. The SBC performance is verified in terms of CPU and memory utilization. In this work, the Raspberry-Pi has successfully completed all tasking with average CPU and average memory utilization less than 10% and less than 31% respectively for S11 measurement and less than 10% and less than 37% respectively for AES measurement. With all capabilities demonstrated and discussed, the FIS-AES have great potential as one of the best options for realizing applications such as localization system man computer interaction.

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Threading implementation on different hardware for travel time estimation purpose

2017-03-06 , Iszaidy Ismail , Ruzelita Ngadiran , R Badlishah Ahmad , Mohd Ilman Jais , Shuhaizar Daud

The travel time estimation is one of traffic management system which provide time taken from one point to another point. Travel time estimation system consists of an embedded platform with image sensor for detecting and tracking the vehicle. Due to limited resources of embedded board, it makes challenging to measure the travel time especially for fast moving vehicle. Capturing system required a high capturing rate of the camera to capture most current frame for fast moving vehicle. Threading is implemented in this system to improve embedded board resource utilization and input-output latency between camera and embedded board. In this paper, the threading technology is applied to two types of Raspberry Pi model and the performance of the embedded board is recorded and analyzed.

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Beam-switchable textile antenna for wireless body area networks (WBAN)

2014 , Mohd Ilman Jais

The research work in this dissertation focuses on beam-switchable textile antenna for wireless body area network (WBAN) application. The idea of beam-switchable textile antenna helps to reduce the antenna size and more flexible. Beam-switchable antenna is useful in the rapid growth of the wireless communication system. The advantage of beam-switchable antenna is to avoid the associated signal equalization problems that are incurred as the wearer moves or turns. This dissertation proposed a novel beam-switchable textile antenna (BSTA) with reconfigurable ability which uses Radio Frequency (RF) PIN diodes biasing circuit as the switching mechanism. BSTA is the first effort in realizing a combination of such beam-switching feature onto a wearable radiator by exploiting silver loaded epoxy adhesive to provide a solderless connection between conductive textiles and the RF circuits. Four PIN diode switches are integrated into shieldit super of symmetrical BSTA designed. The BSTA is capable to achieve beam steering ±16° with peak simulated and measured directivities of 6.8 dBi and 6.69 dBi, respectively. The antenna maintains input impedance approximately 50 Ω at 2.45 GHz without the use of additional quarter wavelength transformers. With dimension of 88 x 88 mm2, it is compact enough to be integrated in clothing for WBAN applications. Based on preliminary assessment of specific absorption rate (SAR) results, this research confirms that BSTA is safe to the human being where the simulation SAR result is less than 1.6 W/kg and 2 W/kg for 1g and 10g mass of tissues correspondingly at particular body parts based on ICNIRP regulation. With all capabilities demonstrated and discussed, the BSTA antenna has big potential in realizing a new smart garment antenna.

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Embedded system for automatic plant irrigation using raspberry-Pi (APLIRasPi)

2017-01-01 , Mohd Ilman Jais , Shuhaizar Daud , Ismail I. , Nurfatin A.S. , R Badlishah Ahmad

Nowadays, an irrigation system in Malaysia mainly uses an irrigation system manually. With this method, water consumption is rather wasted because each soil requires different quantities of water. Similarly, in terms of working on high energy consumption. The purpose of this research work is to upgrade it to the automatic irrigation system using a single board computer (SBC) which is Raspberry-Pi (RasPi). Thus, by upgrading the irrigation system to automatic, there are various pros and recovery can be achieved. Using an automatic irrigation system, farmers can save time and cost. Farmers are also able to control irrigation pumps automatically or by using cell phones or other electronic devices anywhere and anytime through web based. The system also uses soil moisture sensor to detect the humidity of soil. Each soil has a certain moisture level.

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A Fuzzy-Based Angle-of-Arrival Estimation System (AES) using Radiation Pattern Reconfigurable (RPR) antenna and modified gaussian membership function

2019 , Mohd Ilman Jais , Thennarasan Sabapathy , Muzammil Jusoh , R. Badlishah, Ahmad , Mohd Haizal Jamaluddin , Muhammad Ramlee Kamarudin , Phak Len Al Eh Kan , L. Murukesan Loganathan , Soh Ping Jack

Angle-of-arrival (AOA) estimation is an important factor in various wireless sensing applications, especially localization systems. This paper proposes a new type of AOA estimation sensor node, known as AOA-estimation system (AES) where the received signal strength indication (RSSI) from multiple radiation pattern reconfigurable (RPR) antennas are used to calculate the AOA. In the proposed framework, three sets of RPR antennas have been used to provide a coverage of 15 regions of radiation patterns at different angles. The salient feature of this RPR-based AOA estimation is the use of Fuzzy Inferences System (FIS) to further enhance the number of estimation points. The introduction of a modified FIS membership function (MF) based on Gaussian function resulted in an improved 85% FIS aggregation percentage between the fuzzy input and output. This later resulted in a low AOA error (of less than 5%) and root-mean- square error (of less than 8â—¦ ).

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Video size comparison for embedded vehicle speed detection & travel time estimation system by using Raspberry Pi

2017-03-06 , Iszaidy Ismail , Alias A. , Ruzelita Ngadiran , R Badlishah Ahmad , Mohd Ilman Jais , Shuhaizar Daud

As traffic continues to grow up, the issue regarding the road accident also growing quickly. The accident occurred due to the high speed of vehicles on the road. This paper proposed a vehicle speed detection and travel time estimation system using Raspberry Pi to estimate the speed of passing vehicles through this system. The system is designed to detect the moving vehicles and calculate its velocity. The system used OpenCV as an image processing software to detect and track the moving vehicles. Several types of capturing size of the video are used in this system to check and measure the performance of the embedded board.

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Received signal strength indication (RSSI) code assessment for wireless sensors network (WSN) deployed Raspberry-Pi

2017-03-06 , Mohd Ilman Jais , Thennarasan Sabapathy , Muzammil Jusoh , Phak Len Al Eh Kan , Murukesan L. , Ismail I. , R Badlishah Ahmad

Wireless sensor network (WSN) is commonly used for localization applications. Through sniffing receive signal strength indicator (RSSI) in WSN system, localization and connection to access point highest RSSI can be done automatically. In this paper, we propose Raspberry-Pi (RasPi), based best access point selection method utilizing RSSI metric. The RasPi brings the advantages of a personal computer (PC) to the domain of sensor network, which makes it the perfect platform for interfacing with a wide variety of external peripherals. This work aims to investigate various source codes deployed on RasPi for localization purpose by sniffing the RSSI metric. Consequently, comparative analysis of its key elements and performances with some of the currently available wireless sensor nodes have shown that despite few disadvantages, RasPi remains an inexpensive single board computer (SBC) which has been used very successfully in sensor network domain and diverse range of research applications.

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