Review on Smart Algae Bio Panel and its Growth Forecasting Using Machine Learning
DOI:
https://doi.org/10.51983/arme-2022.11.2.3628Keywords:
Micro Algae, Machine Learning Algorithms, Bio-Fuel, Growth ForecastingAbstract
The world is facing major issues associated with the reliance on fossil fuels for energy supply, including rising prices, greenhouse gas emissions, and the risk of depletion. Various technologies have been developed for fixing carbon dioxide, which contributes to global warming. Biological fixation using photosynthetic microalgae cultured on a large scale is a promising method. In this method, carbon should be either wholly stored in the algal biomass or substituted for fossil fuel. Algal biomass can be degraded to carbon dioxide or methane, which is released to the atmosphere. The use of microalgae as a sustainable source of renewable energy and biofuels has garnered significant attention in recent years. One of the advantages of microalgae is their ability to accumulate high levels of lipids, making them a promising feedstock for biofuel production. Moreover, microalgae can be cultivated on non-arable land and can be grown using alternative water sources such as seawater, which further enhances their potential as a sustainable and environmentally friendly energy source. A photo bioreactor (PBR) is essential equipment for microalgal photosynthetic fixation of CO2. A PBR system implemented in a smart bio panel utilizes algae to trap sunlight energy and convert it into electricity, while also generating biomass as a by-product and acting as a CO2 scrubber. To make the system smart, machine learning algorithms were implemented to monitor and predict the growth rate of the algae Support Vector Machines (SVM) were used to predict the growth behavior of the microalgae, and the results showed that the SVM-based model can predict the growth rate of microalgae with a correlation coefficient of 90 percent. Microalgae biomass production heavily relies on photosynthesis, which only utilizes a small portion of the solar energy, mainly in the blue and red wavelengths. However, in traditional microalgae cultivation, the unused portion of the solar spectrum heats up the algae ponds and causes water evaporation, leading to increased salinity, especially in hot and semi-arid locations.
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