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IoT-Based Seismic Sensor Network Design for Early Warning System in Kalimantan : Literature Review Ilham Muthahhari; Muhammad Dzakwan Firdaus
Journal of Computation Physics and Earth Science (JoCPES) Vol 4 No 2 (2024): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v4i2.02

Abstract

Kalimantan is not commonly associated with significant seismic activity due to its relative distance from major tectonic plate boundaries; however, it remains vulnerable to earthquakes that pose risks to human safety and the integrity of infrastructure. A recent seismic incident in the region has raised alarms about the adequacy of current preparedness and mitigation measures. This review seeks to establish a robust early warning system (EWS) for earthquakes by incorporating seismograph technology and IoT-based sensor networks tailored for Kalimantan. Despite its traditional classification as a low-seismic area, the region is susceptible to risks stemming from nearby active faults and tectonic dynamics. By analyzing recent research, this paper highlights the distinct geographical and environmental factors that must be considered when implementing a seismic sensor network in Kalimantan. It also examines the critical elements of seismographic devices for earthquake detection and discusses the role of IoT in enhancing real-time monitoring and early warning capabilities. The proposed IoT-based EWS utilizes affordable, distributed sensors to improve response times and detection precision, thereby providing timely notifications to vulnerable areas. This strategy presents a scalable and economically viable model for regions at risk of earthquakes, emphasizing the significance of both sophisticated instrumentation and accessible IoT technology for communities.
Unveiling Seismic Patterns in Kalimantan: Insights into Earthquake Events Over the Last Two Decades (2000-2024) Eva Darnila; Ilham Muthahhari; R. Grata Sabdo Yudhopratidino
Journal of Computation Physics and Earth Science (JoCPES) Vol 4 No 2 (2024): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v4i2.03

Abstract

Seismic activity in Kalimantan, once considered to be relatively minimal, has garnered increased scrutiny due to the presence of active fault lines, including the Mangkalihat, Meratus, and Tarakan faults. This research examines earthquake occurrences in Kalimantan from 2000 to 2024, utilizing seismic data from the USGS and analytical tools such as QGIS and Microsoft Excel. The findings reveal that earthquake occurrences are predominantly located in the northeastern and southeastern parts of the region, with magnitudes varying between 3.9 and 6.1. Notably, the year 2015 experienced a marked increase in seismic events. The results emphasize the critical need for disaster preparedness, the resilience of infrastructure, and the establishment of Early Warning Systems (EWS) to alleviate potential hazards. This study advocates for ongoing monitoring and enhanced public awareness to diminish seismic vulnerability in Kalimantan.  
Perancangan dan Pengembangan Alat Pengukur UV dan Pelacak Surya Dual-Axis Berbasis IoT untuk Optimalisasi Pemantauan Indeks UV Secara Real-Time Dwi Agustian; Ilham Muthahhari; Valiant Yuvi Syahreza; Anton Widodo; Muchamad Rizqy Nugraha; Edward Trihadi
Journal of Computation Physics and Earth Science (JoCPES) Vol 5 No 1 (2025): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v5i1.01

Abstract

The ultraviolet (UV) radiation emitted by the sun has both positive and negative impacts on human life. Excessive exposure to UV rays can lead to various health issues, such as skin cancer and cataracts. Therefore, UV radiation monitoring becomes crucial, especially in the face of climate change, which may increase the intensity of UV radiation due to the depletion of the ozone layer. This study aims to design an Internet of Things (IoT)-based UV index monitoring system, equipped with a dual- axis solar tracker to optimize UV index measurements. The system utilizes the ESP32 microcontroller as the main processing unit, the UVM-30A sensor to detect UV radiation, and the DS3231 Real Time Clock (RTC) module for time synchronization. UV index data is displayed in real-time through a Liquid Crystal Display (LCD) screen and the Blynk platform for easy remote access. Test results show that the system performs well, with a low relative error compared to UV index data from the reference site uvindex.app. This system provides an innovative solution for efficient and real-time UV index monitoring, which can increase public awareness about the dangers of UV radiation.