Smart Biomass Energy Management: Machine Learning Models and the Emerging Role of Post-Quantum Computing

Nowadays, the population is increasing, and with it, many kinds of waste are also increasing mainly animal waste, forestry residues, energy crops, and municipal solid waste. This growth has led to innovations that recycle these wastes to produce energy for the betterment of society and to protect the environment from waste-related impacts. Biomass energy plays a vital role in fulfilling the energy requirements of any nation. In this paper, the emerging technology of machine learning is presented to make the bioenergy process smart and automated. Various machine learning techniques support smart biomass energy management (SBEM). Furthermore, future technologies such as quantum computing have the potential to completely transform biomass energy management through their high computational power, which may lead to a revolution in SBEM.