Optimizing Biomass-to-Biofuel Conversion

Abstract

This chapter explores the integration of IoT and AI technologies to optimize biomass-to-biofuel conversion processes. AI algorithms can be used to optimize process parameters such as temperature, pressure, and enzyme dosage, leading to increased biofuel yields, reduced energy consumption, and improved quality control. Sustainability assessment is also highlighted, with IoT and AI playing a crucial role in monitoring and analyzing sustainability metrics. Companies such as Pacific Ethanol, Renmatix, IOCL, and GranBio have achieved significant improvements in biofuel yield, energy efficiency, quality control, and sustainability by leveraging IoT and AI technologies. These advancements inspire potential applications and strategies in different biomass feedstock scenarios, enabling organizations to drive the transition towards cleaner and more sustainable energy sources while improving operational efficiency and competitiveness.