Using IoT to assist monitoring of the methane gas extraction at Lake Kivu
Date
2021-05
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Methane gas is a powerful greenhouse gas with global warming potential. The current techniques
being used to monitor the leaks are expensive and likely onerous and demands for trained
operators. There are available solutions tried by the space agencies such as National Aeronautics
and Space Administration (NASA) and European Space Agency (ESA) using satellites to better
understand the distribution of greenhouse gases on regional and global scales. Those are
ENVISAT, GOSAT, OCO-2, and the recently launched TROPOMI instrument on the Sentinel 5P
satellite, but all these, regardless of the advanced technology associated cannot pinpoint the source
of emissions.
In this study, the performance of low-cost Internet of Things (IoT) sensors and isolation forest
anomaly detection machine learning technique was implemented. Isolation Forest is one of the
outstanding outlier detectors in the real-time DataStream for faulty detection, and money
laundering in banking industry. It was tested in this system to improve the accuracy in detecting
the methane gas leak. According to the experimental results, the anomaly detection based on
isolation forest achieved an excellent performance in terms of accuracy of outlier detection while
minimizing the false positives. Decarbonization is an essential component in the climate system,
and this plays a key role in reducing methane emissions. Finally, the study presents future research
directions to carry out research on the machine learning with Internet of Things (IoT).
Description
Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, May 2021
item.page.type
Capstone project
item.page.format
Keywords
gas flaring