A comprehensive review of biomass and biofuels and their progress using digital technologies

Abstract

This review provides a critical, end-to-end synthesis of how digital technologies are reshaping the biomass and biofuel value chain—from feedstock sourcing to end use. We examine the roles of artificial intelligence and machine learning, the Internet of Things, blockchain, and plant-scale digital twins in optimizing supply chains, catalysis, and conversion systems. Evidence indicates that AI-driven predictive models can raise biofuel yields by 15–25%, while IoT-enabled, real-time monitoring cuts operational waste and greenhouse-gas emissions by up to 40%. Beyond process efficiency, we show how digital tools enable rigorous life-cycle assessment, support environmental and health risk management, and expand socioeconomic opportunities, including improved market access for smallholders and demand for skilled jobs. Policy dimensions are addressed through digital frameworks for traceability, transparency, and compliance with evolving regulations. A distinctive feature is our focus on fourth-generation biofuels and the synergistic potential of synthetic biology with AI. We conclude with a practical implementation roadmap that integrates technical, organizational, and policy actions; identifies persistent challenges in data quality, interoperability, cybersecurity, skills, and governance; and outlines research priorities in hybrid physics–ML models, open standards, trustworthy MRV, and equitable deployment. The result is a concise reference for researchers, industry, and policymakers seeking to accelerate a sustainable, low-carbon bioeconomy aligned with global climate goals.