Biogas is produced from biological process of mixed organic materials with the help of bacteria that facilitate the anaerobic digestion process. Biogas can be produced from manure agricultural waste or from other biomass resources available almost everywhere. Many developing countries especially in Africa depends on biomass for domestic energy needs which causes many issues related to socio-economics. In other hands, cattle manure can be used to generate cleaner and cheaper biogas as secondary energy source. To transform cattle manure into Biogas, a biogas digester has been built in several countries especially in Rwanda to reduce the use of woods and Charcoal as source of cooking energy. However, those Biogas digesters built does not have a monitoring system which result in malfunctioning and sometimes produce inefficient Biogas compared to what is should produce. The purpose of this study is to observe biogas production generated from different types of organic materials and measure other parameters that contribute to biogas production .

This research aims to develop a Biogas status monitoring system. The developed system is equipped with sensors capable of measuring biogas status (Co2, Methane Gas, Temperature and PH) and the system process those data locally and then and send aggregated data to the cloud for further analytics. Biogas monitoring systems have been built and predictive model has been built in order to predict biogas yield based on the various Biogas feeding quantity and methods. The proposed predictive model has been evaluated with KNN, decision tree and random forest machine learning algorithms, and obtained results are promising.