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Journal : control systems and optimization letters

A Systematic Design of a Low-Cost Real-Time Vehicle Tracking System for Enhanced Security and Location Monitoring Marhoon, Hamzah M.; Sabah, Sabah Ali; Basil, Noorulden; Tarik, Benmessaoud Mohammed; Mohammed, Raghad Jassim; Fadhil Abbas, Riyam
Control Systems and Optimization Letters Vol 3, No 3 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i3.219

Abstract

The rapid development of vehicle tracking technology has significantly enhanced the safety and security of vehicles worldwide. This paper presents the design and implementation of a real-time vehicle tracking system utilising Global Positioning System (GPS) and Global System for Mobile Communication (GSM) technologies, based on the Arduino Uno platform. The proposed system enables vehicle owners to continuously monitor their vehicle's location, receiving instant SMS notifications for unauthorised movement, speed violations, and historical location data. The system's core components include an Arduino Uno microcontroller, interfaced with a SIM900A GSM module and a NEO-6 M GPS module, enabling real-time tracking via SMS alerts and Google Maps integration. Key features include automatic alerts for unauthorised car startups, exceeding speed limits, live tracking requests, and location history retrieval. The system stores the last five GPS coordinates in EEPROM memory and offers a user-friendly interface for retrieving data via SMS. The integration of Google Maps enhances the tracking experience by providing a visual representation of the vehicle’s location. This solution offers a cost-effective and reliable means of vehicle monitoring, contributing to improved vehicle security and owner peace of mind.
DC to AC Inverter Prototype for Small Scale Power Supply with SPWM Method Listyantoro, Fiki; Ma'arif, Alfian; Sharkawy, Abdel-Nasser; Marhoon, Hamzah M.
Control Systems and Optimization Letters Vol 1, No 2 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i2.24

Abstract

Inverter is a device to convert Dc current voltage into AC current voltage. In this article, the inverter is designed using the H-Bridge configuration. The advantage of this configuration is that there is no need for diodes and capacitors to balance the voltage. The main components in designing this inverter are the Arduino Nano, the IR2103 IC, and also the MOSFET. The switching method used is SPWM with H-Bridge configuration which is controlled by 2 IC IR2103. Based on the test results, the output voltage of this inverter is 7.45 Volts. With a DC voltage of 12 Volts. With the use of an oscilloscope that is used to measure the output waveform from the switching results of the MOSFET, the signal is still in the form of a square wave. To make a sine wave, an inductor filter is needed which functions to produce a signal to become a sine wave, and to keep the frequency at 50Hz. The voltage generated from the step-up transformer can be adjusted by rotating the feedback trimpot. The resulting voltage is 88 Vac to 260 Vac. and can accommodate a maximum load of 250 Watts. This inverter is also equipped with a PZEM-004T sensor which functions to read voltage, current, frequency and power data.
Design and Implementation of an RFID-Based Smart Parking Control System with Infrared Sensors and Queueing-Theory Traffic Modelling Marhoon, Hamzah M.
Control Systems and Optimization Letters Vol 4, No 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i1.261

Abstract

The growing trends in the need for automated and trusted parking control have fostered the enhancement of smart systems that can do effective access control, precise occupancy identification, and effective traffic control. This paper provides both the design, implementation, and analytical evaluation of a low-cost smart parking control system based on Radio Frequency Identification (RFID)- based vehicle authentication, Infrared (IR) sensor-based slot monitoring, and servo-controlled gate actuation based on an Arduino-based embedded architecture. A working prototype is created to exemplify a one-level parking system, where IR sensors are used to detect live availability slots, an RFID module is used to provide authenticated access, and a Liquid Crystal Display (LCD) device is used to show occupants of the slot. In order to come up with a strict performance evaluation, Queueing Theory is adopted by modelling the entrance gate as a service system of M/M/1. This analytical model can be used to measure waiting times, queue time, and system usage quantitatively at different rates of arrival. Measurements conducted during experimental evaluation involve the accuracy of IR detection, RFID authentication latency, servo response time, system reliability, error-rate characterization, and analysis of energy consumption of each hardware component. These results indicate high accuracy in operation, fast authentication, consistent actuation operation, and low power consumption, applicable when a device is compact or battery powered. The queueing-based modelling also substantiates the fact that the system operates efficiently at the levels below saturation points.
Understanding Large Language Models: A Review Wulandari, Annastasya Nabila Elsa; Purwono, Purwono; Ma’arif, Alfian; Basil, Noorulden; Marhoon, Hamzah M.
Control Systems and Optimization Letters Vol 4, No 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i2.292

Abstract

Large Language Models (LLMs) have experienced rapid development and have been established as the dominant paradigm in modern Natural Language Processing (NLP), with high performance demonstrated across various language understanding and generation tasks. Increasing architectural complexity has led to the need for a structured conceptual framework to explain how architectural design, training paradigms, and inference mechanisms are collectively associated with model behavior. A conceptual and analytical review of LLMs is presented in this article through an examination of the relationship between Transformer-based architectures, multi-stage training processes, and the resulting capabilities and limitations. Encoder-only, decoder-only, and encoder–decoder architectural variants are examined in relation to structural characteristics and functional implications. The roles of pretraining, supervised fine-tuning, and instruction tuning are analyzed to clarify how output characteristics are shaped during model development. This study emphasizes how architectural and training strategies causally influence generative capabilities and inherent limitations. Fundamental issues, including hallucination, bias, data dependency, computational cost, and evaluation challenges, are critically examined as consequences of the probabilistic modeling paradigm adopted in LLMs. This review contributes a structured analytical perspective for evaluating LLMs design choices and their operational consequences, supporting more informed development and deployment practices.