Smart Nutrient Management in Anaerobic Digestion: A CNN-Powered Strategy for Optimizing Trace Elements in Biogas Production

Authors- Srinivas Kasulla, S J Malik, Anjani Yadav, Gaurav Kathpal, Fredrick Kayusi

Abstract-AD is one of the most significant biological processes that convert organic waste into biogas. It provides renewable energy by cutting down on waste management and environmental problems. Trace elements are part of the component, that is used to maximize microbial activities in the AD system because some of the activities were uniquely essential to perform a function within the machine of enzymes involved in methanogenesis; consequently, any deficiency or imbalance lowers yields of biogas (Speece and Parkin, 1987; Menon et al., 2017). The present study integrates implementing an optimization trace element supplement model in the framework of anaerobic digestion. They proposed trace element concentration forecasting and handling as an optimization means of enhancing efficiency in biogas generation through real-time AD operations. Their results with the CNN model are tremendous in predicting the optimal trace element concentrations that went along with increases in the rates of biogas production among different feedstocks. The main outcome of the research further showed that the yield of methane and system stability increased significantly upon optimizing trace elements supplementation through the CNN-based approach (Wang et al., 2020; Zieliński et al., 2019). Optimizing trace elements supplementation using CNN has indicated a promising platform for upscaling into an industrial biogas system with an effective data-driven decision that is sure to improve upon nutrient management. Further expansion of the model’s applicability may lead to further extension of the different feedstocks and variable environmental conditions and further introduce sustainability and efficiency in biogas production practices (Azbar et al., 2019; Kasulla and Malik, 2021). The proposed CNN model, therefore, is better as it leads to higher accuracy, precision, and lower time complexity compared with the conventional methods due to their far more accurate, dynamic, and real-time optimization of trace element supplementation and hence of utmost importance for the maximization of the production of biogas using a wide variety of feedstocks and therefore leads to an even more efficient and adaptable method for industrial-scale digestions.

DOI: /10.61463/ijset.vol.12.issue6.385