Design and Development of an IoT-based Greenhouse Gas Monitoring System

Greenhouse gas (GHG) emissions from water bodies, including rivers, lakes, and reservoirs, significantly contribute to global GHG levels. These emissions primarily consist of carbon dioxide $\left(\mathrm{CO}_{2}\right)$ and methane $\left(\mathrm{CH}_{4}\right)$, released through various natural and anthropogenic processes. Detecting GHGs in aquatic environments like inland waterbodies poses significant challenges due to spatial-temporal variability, sensor accuracy, environmental interference, and high costs. To address these issues, we developed an IoT-based system for real-time monitoring of CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and CH<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</inf>, along with temperature, pressure, and humidity. The system integrates a Raspberry Pi for data collection and transmission to a cloud database, enabling continuous and remote monitoring. A web-based dashboard facilitates real-time access and control from any internet-connected device, providing comprehensive data and system management. This approach enhances our understanding of GHG dynamics and environmental conditions, offering valuable insights for addressing critical challenges in inland waterbodies like ponds and rivers.