Harnessing artificial intelligence for enhanced bioethanol productions: a cutting-edge approach towards sustainable energy solution

Abstract

Abstract The adoption of biofuels as an energy source has experienced a substantial increase, exceeding the consumption of fossil fuels. The shift can be ascribed to the availability of renewable resources for energy production and the ecological advantages linked to their utilisation. Nevertheless, due to its intricate characteristics, the process of producing ethanol fuel from biomass poses difficulties in terms of administration, enhancement, and forecasting future results. To tackle these difficulties, it is crucial to utilise modelling techniques like artificial intelligence (AI) to create, oversee, and improve bioethanol production procedures. Artificial Neural Networks (ANN) is a prominent AI technique that offers significant advantages for modelling bioethanol production systems’ pretreatment, fermentation, and conversion stages. They are highly flexible and accurate, making them particularly well-suited. This study thoroughly examines several artificial intelligence techniques used in bioethanol production, specifically focusing on research published in the past ten years. The analysis emphasises the importance of using AI methods to address the complexities of bioethanol production and shows their role in enhancing efficiency and sustainability in the biofuel industry.