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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Haslinah Mohd Nasir
Universiti Teknikal Malaysia Melaka
Computer Science & IT Electrical & Electronics Engineering Engineering

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Android based application for visually impaired using deep learning approach Haslinah Mohd Nasir; Noor Mohd Ariff Brahin; Mai Mariam Mohamed Aminuddin; Mohd Syafiq Mispan; Mohd Faizal Zulkifli
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp879-888

Abstract

People with visually impaired had difficulties in doing activities related to environment, social and technology. Furthermore, they are having issues with independent and safe in their daily routine. This research propose deep learning based visual object recognition model to help the visually impaired people in their daily basis using the android application platform. This research is mainly focused on the recognition of the money, cloth and other basic things to make their life easier. The convolution neural network (CNN) based visual recognition model by TensorFlow object application programming interface (API) that used single shot detector (SSD) with a pre-trained model from Mobile V2 is developed at Google dataset. Visually impaired persons capture the image and will be compared with the preloaded image dataset for dataset recognition. The verbal message with the name of the image will let the blind used know the captured image. The object recognition achieved high accuracy and can be used without using internet connection. The visually impaired specifically are largely benefited by this research.
Development of vocabulary learning application by using machine learning technique Noor Mohd Ariff Brahin; Haslinah Mohd Nasir; Aiman Zakwan Jidin; Mohd Faizal Zulkifli; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.1 KB) | DOI: 10.11591/eei.v9i1.1616

Abstract

Nowadays an educational mobile application has been widely accepted and opened new windows of opportunity to explore. With its flexibility and practicality, the mobile application can promote learning through playing with an interactive environment especially to the children. This paper describes the development of mobile learning to help children above 4 years old in learning English and Arabic language in a playful and fun way. The application is developed with a combination of Android Studio and the machine learning technique, TensorFlow object detection API in order to predict the output result. Developed application namely “LearnWithIman” has successfully been implemented and the results show the prediction of application is accurate based on the captured image with the list item. The inclusion of the user database for lesson tracking and new lesson will be added for improvement in the future.
Lightweight hardware fingerprinting solution using inherent memory in off-the-shelf commodity devices Mohd Syafiq Mispan; Aiman Zakwan Jidin; Muhammad Raihaan Kamarudin; Haslinah Mohd Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 1: January 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i1.pp105-112

Abstract

An emerging technology known as Physical unclonable function (PUF) can provide a hardware root-of-trust in building the trusted computing system. PUF exploits the intrinsic process variations during the integrated circuit (IC) fabrication to generate a unique response. This unique response differs from one PUF to the other similar type of PUFs. Static random-access memory PUF (SRAM-PUF) is one of the memory-based PUFs in which the response is generated during the memory power-up process. Non-volatile memory (NVM) architecture like SRAM is available in off-the-shelf microcontroller devices. Exploiting the inherent SRAM as PUF could wide-spread the adoption of PUF. Therefore, in this study, we evaluate the suitability of inherent SRAM available in ATMega2560 microcontroller on Arduino platform as PUF that can provide a unique fingerprint. First, we analyze the start-up values (SUVs) of memory cells and select only the cells that show random values after the power-up process. Subsequently, we statistically analyze the characteristic of fifteen SRAM-PUFs which include uniqueness, reliability, and uniformity. Based on our findings, the SUVs of fifteen on-chip SRAMs achieve 42.64% uniqueness, 97.28% reliability, and 69.16% uniformity. Therefore, we concluded that the available SRAM in off-the-shelf commodity hardware has good quality to be used as PUF.
Proof of concept for lightweight PUF-based authentication protocol using NodeMCU ESP8266 Mohd Syafiq Mispan; Aiman Zakwan Jidin; Muhammad Raihaan Kamaruddin; Haslinah Mohd Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1392-1398

Abstract

Wireless sensor node is the foundation for building the next generation of ubiquitous networks or the so-called internet of things (IoT). Each node is equipped with sensing, computing devices, and a radio transceiver. Each node is connected to other nodes via a wireless sensor network (WSN). Examples of WSN applications include health care monitoring, and industrial monitoring. These applications process sensitive data, which if disclosed, may lead to unwanted implications. Therefore, it is crucial to provide fundamental security services such as identification and authentication in WSN. Nevertheless, providing this security on WSN imposes a significant challenge as each node in WSN has a limited area and energy consumption. Therefore, in this study, we provide a proof of concept of a lightweight authentication protocol by using physical unclonable function (PUF) technology for resource-constrained wireless sensor nodes. The authentication protocol has been implemented on NodeMCU ESP8266 devices. A server-client protocol configuration has been used to verify the functionality of the authentication protocol. Our findings indicate that the protocol used approximately 7% of flash memory and 48% of static random-access memory (SRAM) in the sensor node during the authentication process. Hence, the proposed scheme is suitable to be used for resource-constrained IoT devices such as WSN.
Co-Authors Aiman Zakwan Jidin Mai Mariam Mohamed Aminuddin Mohd Faizal Zulkifli Mohd Syafiq Mispan Muhammad Raihaan Kamaruddin Muhammad Raihaan Kamarudin Noor Mohd Ariff Brahin Tole Sutikno