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Updated: Oct 2, 2025

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation
Published on: August 14, 2020
Smart microalgae farming with internet-of-things for sustainable agriculture
Hooi Ren Lim1, Kuan Shiong Khoo2, Wen Yi Chia3
1State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, PR China; Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, Semenyih 43500, Selangor Darul Ehsan, Malaysia.
Abstract:
Agriculture farms such as crop, aquaculture and livestock have begun the implementation of Internet of Things (IoT) and artificial intelligence (AI) technology in improving their productivity and product quality. However, microalgae farming which requires precise monitoring, controlling and predicting the growth of microalgae biomass has yet to incorporate with IoT and AI technology, as it is still in its infancy phase. Particularly, the cultivation stage of microalgae involves many essential parameters (i.e. biomass concentration, pH, light intensity, temperature and tank level) which require precise monitoring as these parameters are important to ensure an effective biomass productivity in the microalgae farming. Besides, the conventional practices in the current process equipment are still powered by electricity, thus further development by integrating IoT into these processes can ease the production process. Further to that, many researchers has studied the machine learning approach for the identification and classification of microalgae. However, there are still limited studies reported on applying machine learning for the application of microalgae industry such as optimising microalgae cultivation for higher biomass productivity. Therefore, the implementation of IoT and AI in microalgae farming can contribute to the development of the global microalgae industry. The purpose of this current review paper focuses on the overview microalgae biomass production process along with the implementation of IoT toward the future of smart farming. To bridge the gap between the conventional and microalgae smart farming, this paper also highlights the insights on the implementation phases of microalgae smart farming starting from the infant stage that involves the installation and programming of IoT hardware. Then, it is followed by the application of machine learning to predict and auto-optimise the microalgae smart farming process. Furthermore, the process setup and detailed overview of microalgae farming with the integration of IoT have been discussed critically. This review paper would provide a new vision of microalgae farming for microalgae researchers and bio-processing industries into the digitalisation industrial era.
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