Abstract
As the world becomes increasingly dependent on fossil fuels, it faces growing environmental and economic challenges, particularly with carbon emissions and energy sustainability. One promising solution involves using photosynthetic microalgae, which can absorb carbon dioxide and convert sunlight into energy-rich materials, such as biofuels. Microalgae can grow on land that is unsuitable for conventional farming and can utilize various types of water, including seawater, making them an eco-friendlier option. A critical technology for large-scale algae cultivation is the photobioreactor (PBR), a controlled system designed to promote algae growth by regulating factors such as light, temperature, and nutrients. Recent innovations are integrating PBRs with smart bio-panels, which capture solar energy, generate electricity, and simultaneously facilitate carbon dioxide removal from the atmosphere. Machine learning tools, such as Support Vector Machines (SVM), are also being employed to predict algal growth and optimize conditions for enhanced productivity. However, microalgae utilize only a small portion of sunlight for photosynthesis, and traditional cultivation methods can result in energy inefficiencies and increased salinity due to water evaporation. To enhance algae cultivation, researchers are exploring methods to capture more sunlight, including the use of specialized lighting systems or genetically engineered algae strains. These advancements could make microalgae a more efficient and sustainable source of biofuels, bioplastics, and other valuable products, contributing to the resolution of both energy and climate issues. Microalgae offer a renewable, carbon-neutral alternative to fossil fuels and could play a vital role in addressing global energy needs while minimizing the environmental impact of conventional energy sources. By integrating advanced technologies in cultivation, renewable energy production, and carbon capture, microalgae farming presents a sustainable approach to tackling energy and climate challenges, offering economic and environmental benefits.
Cite
CITATION STYLE
Karade, N. R., Lohar, S. D., Patil, R. S., & Desai, S. R. (2024). Integrating Smart Bio-Panels and Machine Learning for Enhanced Microalgae Cultivation and Carbon Reduction. Asian Journal of Engineering and Applied Technology, 13(2), 36–43. https://doi.org/10.70112/ajeat-2024.13.2.4252
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.