TY - JOUR
T1 - How does the Internet of Things (IoT) help in microalgae biorefinery?
AU - Wang, Kexin
AU - Khoo, Kuan Shiong
AU - Leong, Hui Yi
AU - Nagarajan, Dillirani
AU - Chew, Kit Wayne
AU - Ting, Huong Yong
AU - Selvarajoo, Anurita
AU - Chang, Jo Shu
AU - Show, Pau Loke
N1 - Funding Information:
This work was supported by the Fundamental Research Grant Scheme, Malaysia [ FRGS/1/2019/STG05/UNIM/02/2 ] and MyPAIR-PHC-Hibiscus Grant [ MyPAIR/1/2020/STG05/UNIM/1 ]. The authors also gratefully acknowledge the financial support by Taiwan’s Ministry of Science and Technology (MOST) under grant nos. 110-2221-E-029 -004 -MY3 , 110-2621-M-029 -001 , and 109-2622-E-110 -011 .
Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Microalgae biorefinery is a platform for the conversion of microalgal biomass into a variety of value-added products, such as biofuels, bio-based chemicals, biomaterials, and bioactive substances. Commercialization and industrialization of microalgae biorefinery heavily rely on the capability and efficiency of large-scale cultivation of microalgae. Thus, there is an urgent need for novel technologies that can be used to monitor, automatically control, and precisely predict microalgae production. In light of this, innovative applications of the Internet of things (IoT) technologies in microalgae biorefinery have attracted tremendous research efforts. IoT has potential applications in a microalgae biorefinery for the automatic control of microalgae cultivation, monitoring and manipulation of microalgal cultivation parameters, optimization of microalgae productivity, identification of toxic algae species, screening of target microalgae species, classification of microalgae species, and viability detection of microalgal cells. In this critical review, cutting-edge IoT technologies that could be adopted to microalgae biorefinery in the upstream and downstream processing are described comprehensively. The current advances of the integration of IoT with microalgae biorefinery are presented. What this review discussed includes automation, sensors, lab-on-chip, and machine learning, which are the main constituent elements and advanced technologies of IoT. Specifically, future research directions are discussed with special emphasis on the development of sensors, the application of microfluidic technology, robotized microalgae, high-throughput platforms, deep learning, and other innovative techniques. This review could contribute greatly to the novelty and relevance in the field of IoT-based microalgae biorefinery to develop smarter, safer, cleaner, greener, and economically efficient techniques for exhaustive energy recovery during the biorefinery process.
AB - Microalgae biorefinery is a platform for the conversion of microalgal biomass into a variety of value-added products, such as biofuels, bio-based chemicals, biomaterials, and bioactive substances. Commercialization and industrialization of microalgae biorefinery heavily rely on the capability and efficiency of large-scale cultivation of microalgae. Thus, there is an urgent need for novel technologies that can be used to monitor, automatically control, and precisely predict microalgae production. In light of this, innovative applications of the Internet of things (IoT) technologies in microalgae biorefinery have attracted tremendous research efforts. IoT has potential applications in a microalgae biorefinery for the automatic control of microalgae cultivation, monitoring and manipulation of microalgal cultivation parameters, optimization of microalgae productivity, identification of toxic algae species, screening of target microalgae species, classification of microalgae species, and viability detection of microalgal cells. In this critical review, cutting-edge IoT technologies that could be adopted to microalgae biorefinery in the upstream and downstream processing are described comprehensively. The current advances of the integration of IoT with microalgae biorefinery are presented. What this review discussed includes automation, sensors, lab-on-chip, and machine learning, which are the main constituent elements and advanced technologies of IoT. Specifically, future research directions are discussed with special emphasis on the development of sensors, the application of microfluidic technology, robotized microalgae, high-throughput platforms, deep learning, and other innovative techniques. This review could contribute greatly to the novelty and relevance in the field of IoT-based microalgae biorefinery to develop smarter, safer, cleaner, greener, and economically efficient techniques for exhaustive energy recovery during the biorefinery process.
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U2 - 10.1016/j.biotechadv.2021.107819
DO - 10.1016/j.biotechadv.2021.107819
M3 - Review article
C2 - 34454007
AN - SCOPUS:85114732777
SN - 0734-9750
VL - 54
JO - Biotechnology Advances
JF - Biotechnology Advances
M1 - 107819
ER -