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All Journal Infotekmesin Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Asep andang
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Kendali Kecepatan Motor BLDC dengan metode Mesin Sinkron dan Variasi PWM berbasis IoT Asep Andang; Rahayu, Andri Ulus; Imam Taufiqurrahman; Ervan Paryono
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2417

Abstract

This study investigates speed control of brushless DC (BLDC) motors using a synchronous machine method and Pulse Width Modulation (PWM) variations based on IoT. A three-phase inverter controlled by an STM32 microcontroller was used to drive the BLDC motor. Speed control was implemented by adjusting the inverter frequency based on the synchronous machine principle, while PWM duty cycle was varied to regulate the input voltage. An IoT-based system using a smartphone app allowed remote speed settings. Experimental results showed that the synchronous machine method could effectively control BLDC motor speed, with frequency changes linearly affecting inverter output voltage. Varying PWM duty cycles impacted the voltage required to achieve target speeds, with higher duty cycles requiring lower voltages. The control system achieved speed accuracies within 3% of setpoints across different duty cycles. This approach demonstrates the feasibility of applying synchronous machine principles for BLDC motor control with IoT integration.
Deteksi Duplikasi Data pada Sistem Pemantauan Kualitas Udara Berbasis IoT Dwi Ilham Maulana; Asep Andang; Ifkar Usrah; Agus Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 2: Mei 2025
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i2.16272

Abstract

The increasing volume of data on the Internet of things (IoT)-based systems has driven the need for efficiency in data management, particularly in air quality monitoring systems. One approach to address this challenge is data duplication detection, which works to eliminate redundant data to reduce storage requirements and power consumption. This study aims to develop an IoT-based air quality monitoring system incorporating a data duplication detection method as part of an effort to support the green IoT concept. The methodology involved a comparative analysis between systems with and without the implementation of data duplication detection, accompanied by a comprehensive evaluation of system performance. The data tested included the size of transmitted data and device power consumption during the transmission process. Testing was conducted under real operational conditions over a 24-hour period. The results indicate that the implementation of data duplication detection successfully reduced the size of transmitted data from 56 bytes to 11–44 bytes, depending on the level of data redundancy. Power consumption was reduced by 1.59% to 3.84% compared to the system without data duplication detection. This method was also proven not to affect the accuracy of the displayed data, thereby maintaining the system’s functional requirements. In conclusion, the implementation of the data duplication detection method in an IoT-based air quality monitoring system not only optimizes data transmission processes but also supports energy efficiency in line with the principles of green IoT. This research provides a significant contribution to the development of more sustainable and energy-efficient IoT systems.
Co-Authors Agus Purnomo Andri Ulus Rahayu Dwi Ilham Maulana Ervan Paryono Ifkar Usrah Imam Taufiqurrahman