Internet of things enabled landfill pollution gas monitoring

Due to the increasing concern on how to manage wastes and ensure environmental safety across the globe, a new tool that assists in the monitoring of methane, humidity, and temperature in the landfill using internet of things (IoT) has been created. This system uses ESP32 microcontroller and MQ-4 and DHT-22 sensors to measure environmental conditions at three different spots in a landfill. The samples of data are collected at three times a day, that is, in the morning at 7:00 am, at midday at 12:00 pm and in the evening at 5:00 pm and the data is transmitted to an online sheet where the public can access it in real time hence increasing transparency in the management of wastes. The tool shows a very good precision and effectiveness and the parameters are 94. 6% data integrity over three months testing period. The first findings show that the mean methane concentration is the highest at midday, which is related to the temperature and underlines the role of temperature in the methane emission process. The presented IoT based monitoring system also enhances the accuracy and efficiency in the monitoring of landfill gas and at the same time reduces the intervention of human effort and increases the capability to make prompt adjustments to changes in the environment. Used as an instrument for obtaining accurate and easily understandable data, it is hoped that this tool will in some way help to enhance global environmental health and safety standards, and help pave a way for methane storage for renewable energy purposes.

Authors

Institutions

Publication Details

Journal
Indonesian Journal of Electrical Engineering and Computer Science
Published
2024-10-31
DOI
https://doi.org/10.11591/ijeecs.v37.i1.pp48-55
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Internet of things enabled landfill pollution gas monitoring

Farida Arinie Soelistianto, Mochammad Junus, David Fydo Putradi, Mohammad Abdullah Anshori et al.
Indonesian Journal of Electrical Engineering and Computer Science
Fire Detection and Safety Systems
article

Internet of things enabled landfill pollution gas monitoring

Farida Arinie Soelistianto, Mochammad Junus, David Fydo Putradi, Mohammad Abdullah Anshori, Rizky Ardiansyah
article en

Abstract

Due to the increasing concern on how to manage wastes and ensure environmental safety across the globe, a new tool that assists in the monitoring of methane, humidity, and temperature in the landfill using internet of things (IoT) has been created. This system uses ESP32 microcontroller and MQ-4 and DHT-22 sensors to measure environmental conditions at three different spots in a landfill. The samples of data are collected at three times a day, that is, in the morning at 7:00 am, at midday at 12:00 pm and in the evening at 5:00 pm and the data is transmitted to an online sheet where the public can access it in real time hence increasing transparency in the management of wastes. The tool shows a very good precision and effectiveness and the parameters are 94. 6% data integrity over three months testing period. The first findings show that the mean methane concentration is the highest at midday, which is related to the temperature and underlines the role of temperature in the methane emission process. The presented IoT based monitoring system also enhances the accuracy and efficiency in the monitoring of landfill gas and at the same time reduces the intervention of human effort and increases the capability to make prompt adjustments to changes in the environment. Used as an instrument for obtaining accurate and easily understandable data, it is hoped that this tool will in some way help to enhance global environmental health and safety standards, and help pave a way for methane storage for renewable energy purposes.

Indonesian Journal of Electrical Engineering and Computer ScienceVol. 37(1)
State University of Malang (ID)
Openalex Percentile: Top 77%
Fire Detection and Safety Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Internet of things enabled landfill pollution gas monitoring — Farida Arinie Soelistianto, Mochammad Junus, et al. · Indonesian Journal of Electrical Engineering and Computer Science (2024) | TGRS Research Map | TGRS