Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : JOIV : International Journal on Informatics Visualization

Solar Powered Vibration Propagation Analysis System using nRF24l01 based WSN and FRBR Wedashwara, Wirarama; Yadnya, Made Sutha; Sudiarta, I Wayan; Arimbawa, I Wayan Agus; Mulyana, Tatang
JOIV : International Journal on Informatics Visualization Vol 7, No 1 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.1.1592

Abstract

Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.
Co-Authors Aas, Ani Ahmad Musnansyah Andri Gautama Suryabrata Andri Gautama Suryabrata, Andri Gautama Asep S Setyadin Ayasrah, Firas Tayseer Ayudia Prillia Ayudita Oktafiani Bambang Eko Saputro Dadang Hafid Daryatno, Dinda Azzahra Dava Rizki Prayoga Deden Witarsyah Derry Destian Didit Adytia Dimas Raihan Zein Dina Meliana Saragi Ekki Kurniawan Endang Budiasih Erna Sri Sugesti Euis Dasipah Fakhrizal, Valdy Rahadian Fakhruddin, Muhammad Dzaki Fakhrurroja, Hanif Faqih Hamami Firda Mawaddah Firza Ahmad Setiyansyah Fitri Awaliyah Gantini, Tuti Gijanto Purbo Suseno Gumilar, Irfan Rizki Gunawan, Roni Hakim, Aqil Rahman Haris Rachmat I Wayan Agus Arimbawa, I Wayan Agus I Wayan Sudiarta Jero Budi Darmayasa, Jero Budi Kamaludin, Muhamad Khoiroh, Lisana Made Sutha Yadnya Muhamad Kamaludin Muhammad Dzaki Fakhruddin Munawar, Soviyan Nataliningsih, Nataliningsih Nopendri Nopendri Novan Bayu Nugraha Nugraha, Rizal Yudha Nurhasan, Rohimat Pandanwangi, Nurfadilah Ros Porman Pangaribuan Prasetia Pramudita Yuliarso Pratama, Marsa Kalbu Prayoga, Dava Rizki Rahman, Jodi Rizki Rismawan, Arip Rizaldi Nurilhuda Rodiana, Ilham Mulkan Salsabilla, Annisa Maulidina Saputro, Bambang Eko Sari, Intan Tenisia Prawita Satya Wicaksana Mukhlisin Satya Wicaksana Mukhlisin Satya Wicaksana Mukhlisin, Satya Wicaksana Seno Adi Putra Setyadin, Asep S. Setyorini Setyorini Sri Martini Sri Martini Suryabrata, Andri Gautama Tee Kim Soon, Tee Teguh Prasetyo Tien Fabrianti Kusumasari W, Wahyudin Wedashwara, Wirarama Wibawa, Ismail Supriyatna Widianto Soekarnen Witari, Witari