Development of an Internet of Things Based Volcano Monitoring System. Issue 1 (September 2021)

• Record Type: Journal Article
• Authors: Evita, Maria; Irham, Hamidan; Aminah, Nina Siti; Kane, Hansel; Srigutomo, Wahyu; Meilano, Irwan; Setiawan, Ari; Suryanto, Wiwit; Wahyudi, ; Suyanto, Imam; Darmawan, Herlan; Yasin, Mohammad; Apsari, Retna; Irzaman, ; Perdinan, ; Putra, Heriyansyah; Djamal, Mitra
• Is Part Of: IOP conference series. Volume 830:Issue 1(2021)
• Publication Date: 2021-09
• Subjects: volcano -- internet of things -- gas -- temperature -- vibration; Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/830/1/012023
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: Indonesia has the highest number of active volcano all over the world. There were 63 eruptions with more than 70000 casualties from last year eruptions. To minimize the effect of this disaster, we have developed a volcano early warning system for Indonesian volcano. The main part of the system is volcano monitoring system. A system based on Internet of Things (IoT) has been developed to monitor some activities of a volcano. The physical parameters of these activities are indicated by the changing of temperature, gases (sulphur dioxide and carbon dioxide) concentration, vibration and landslides. The system consists of these parameter sensors, a microcontroller, a solar cell and a Long Range Radio (LoRa) for data transmission to the base station. The system has been tested in laboratory environment for the solar cell, sensors and radio communication. The solar cell could generate 18.81 Volt voltage and 0.23 Ampere current. The temperature sensor has been calibrated for until 51°C measurement (volcano normal condition), while the gas sensor could properly detect the gas until 8 ppm according to the calibration result. After Fast Fourier Transform (FFT) analysis the vibration sensor detected almost zero frequency with 0.168 m/s 2, 0.0168 m/s 2 and 1.125 m/s 2 X, Y and Z axis zero offset respectively. In addition, the landslide had maximum about 4° degraded land slope error. Moreover, only 4% (maximum) percentage error rate (PER) shown by the radio for about 400 m data communication. Furthermore, the physical parameter data acquired then be real-time displayed using Node-red dashboard which can be accessed by the user or other parties who need the information.