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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  • Publication
    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.
  • Publication
    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.
  • Publication
    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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