RETRACTED: Estimation of methane emissions from energy combustion based on wireless sensors and machine learning (Retracted article. See vol. 106, 2024)

Methane emissions from garbage dumps have become a global mantra due to global climate change and its significant impact. The portable air quality meter used in this study estimates methane emissions from six storage locations. The results show that the spatial level is in the methane range. The previous method based on Neural Network and IOT (Internet of Thing) for methane emissions based energy combustion. In the previous method, Low complexity requires massive processing, and it cannot improve any application. So in the proposed methane, emissions from energy combustion are used for energy combustion, and sensors are easily interfaces with the controller without any complex. There is a time-varying level of methane-based on the high value during the rainy season. On the other hand, the number of methane emissions by the control station is not detected. According to the Air Quality Index (AQI) model, methane emissions are also moderate, confirming that methane emissions come from human activities in the garbage dump, excluding mainly radio stations, and estimating it as safe. They recommend policies intended to isolate methane emissions, including recycling, recycling and reduction. Climate change is an important issue that needs to be addressed immediately. The effects of climate change, such as ocean acidification and extreme weather conditions, are so severe that they are essential for learning the combat effectiveness behind these phenomena.