A new approach based on Likelihood and Euclidean Distance for the recognition of standards in methane gas (Research, Society and Development, 2022)
For some time now, natural gas that has been used as an alternative fuel in different transport vehicles, and thus, heavy vehicles such as buses and trucks, tend to reduce functional costs, reducing pollution rates to the environment. The objective of this work is to identify and classify signs of methane gas from two biomasses, one from the first phase sewage sludge and the other from the first phase sewage sludge by increasing the bovine manure inoculum, using mathematical methods applied in the analysis of clusters in the area of computer science. The theorems used in the application of this concept were that of the Euclidean and likelihood distance. For this, it will be necessary to increase concepts related to: artificial intelligence; embedded systems; and structural design of a biodigester prototype for biogas production. The result found successfully demonstrates that, through the development of the experimental scientific model of the biodigester, methane was obtained, and cluster analysis techniques were introduced for the formation of signal pattern.