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Journal : Jurnal EECCIS

Performance Analysis of OFDM under AWGN and Rayleigh Fading Channels Based on Software Defined Radio Arum Dimarsasi, Ivana; Saptono, Rachmad; Syirajjudin, Muhammad
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 18 No. 3 (2024)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v18i3.1748

Abstract

Orthogonal Frequency Division Multiplexing (OFDM) is a very efficient and popular modulation technique in modern wireless communication systems. OFDM offers advantages in terms of spectrum efficiency, resistance to multi-path interference, and is able to support high data rates. This OFDM system uses the concept of Software Defined Radio (SDR) because it is able to implement directly with the help of USRP B210 hardware. The OFDM system consists of a transmitter and receiver that are processed by digital signal processing to encode, decode, and modulate data. This study uses GNU Radio software as a transmitter and receiver model. The purpose of this study is to compare the performance of real-time data transmission through the AWGN (Additive White Gaussian Noise) and Rayleigh Fading channels. The results of the study show that the performance of the OFDM system built, namely the use of BPSK modulation on the AWGN channel has the best performance with the lowest BER results of 0.376 and SNR 14 dB.
Monitoring and Controlling System for Ammonia and Methane Gas in Broiler Chicken Farms Using Fuzzy Mamdani-Based Hybrid Junus, Mochammad; Saptono, Rachmad; Putri Nabila, Anggraeni
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v19i3.1805

Abstract

The broiler poultry industry significantly contributes to food security by supplying animal protein; however, it also generates harmful gases such as ammonia (NH?) and methane (CH?) from accumulated waste. These gases not only endanger poultry health but also contribute to environmental pollution and climate change. This research proposes the development of an Internet of Things (IoT)-based monitoring and control system for ammonia and methane gas levels in broiler chicken farms. The system employs MEMS NH? and MQ4 gas sensors integrated with an ESP32 microcontroller, and applies the Mamdani fuzzy logic method to classify gas levels into safe, unhealthy, or dangerous categories. Based on the fuzzy output, a water pump powered by a hybrid solar energy system is activated automatically to reduce gas concentrations. Data is transmitted in real-time to a Firebase database and can be accessed via an Android application supporting both manual and automatic control modes. Experimental results demonstrate the system's effectiveness in detecting gas levels accurately and responding efficiently to maintain a healthy farm environment while utilizing renewable energy sources.