Smart microalgae farming with internet-of-things for sustainable agriculture

被引:54
作者
Lim, Hooi Ren [1 ,2 ]
Khoo, Kuan Shiong [3 ]
Chia, Wen Yi [2 ]
Chew, Kit Wayne [4 ,5 ]
Ho, Shih-Hsin [1 ]
Show, Pau Loke [2 ]
机构
[1] Harbin Inst Technol, Sch Environm, State Key Lab Urban Water Resource & Environm, Harbin 150090, Peoples R China
[2] Univ Nottingham Malaysia, Fac Sci & Engn, Dept Chem & Environm Engn, Semenyih 43500, Selangor, Malaysia
[3] UCSI Univ, Fac Appl Sci, UCSI Hts, Kuala Lumpur 56000, Malaysia
[4] Xiamen Univ Malaysia, Sch Energy & Chem Engn, Sepang 43900, Selangor, Malaysia
[5] Xiamen Univ, Coll Chem & Chem Engn, Xiamen 361005, Fujian, Peoples R China
关键词
Internet of things; Machine learning; Artificial intelligence; Microalgae; Smart farming; LIPID EXTRACTION; SPIRULINA-PLATENSIS; OPTICAL-PROPERTIES; REMOTE ESTIMATION; WASTE-WATER; BIOMASS; GROWTH; CULTIVATION; IOT; OPTIMIZATION;
D O I
10.1016/j.biotechadv.2022.107931
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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 bioprocessing industries into the digitalisation industrial era.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Smart Farming: Internet of Things (IoT)-Based Sustainable Agriculture
    Dhanaraju, Muthumanickam
    Chenniappan, Poongodi
    Ramalingam, Kumaraperumal
    Pazhanivelan, Sellaperumal
    Kaliaperumal, Ragunath
    AGRICULTURE-BASEL, 2022, 12 (10):
  • [2] Artificial Intelligence and Internet of Things for Sustainable Farming and Smart Agriculture
    AlZubi, Ahmad Ali
    Galyna, Kalda
    IEEE ACCESS, 2023, 11 : 78686 - 78692
  • [3] Internet of Things-Based Smart Precision Farming in Soilless Agriculture: Opportunities and Challenges for Global Food Security
    Dutta, Monica
    Gupta, Deepali
    Tharewal, Sumegh
    Goyal, Deepam
    Sandhu, Jasminder Kaur
    Kaur, Manjit
    Alzubi, Ahmad Ali
    Alanazi, Jazem Mutared
    IEEE ACCESS, 2025, 13 : 34238 - 34268
  • [4] Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review
    Madushanki, A. A. Raneesha
    Halgamuge, Malka N.
    Wirasagoda, W. A. H. Surangi
    Syed, Ali
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2019, 10 (04) : 11 - 28
  • [5] Sustainable smart photobioreactor for continuous cultivation of microalgae embedded with Internet of Things
    Tham, Pei En
    Ng, Yan Jer
    Vadivelu, Navintran
    Lim, Hooi Ren
    Khoo, Kuan Shiong
    Chew, Kit Wayne
    Show, Pau Loke
    BIORESOURCE TECHNOLOGY, 2022, 346
  • [6] An Internet-of-Things Enabled Smart System for Wastewater Monitoring
    Solano, Fernando
    Krause, Steffen
    Woellgens, Christoph
    IEEE ACCESS, 2022, 10 : 4666 - 4685
  • [7] Organic Black Soldier Flies (BSF) Farming in Rural Area using Libelium Waspmote Smart Agriculture and Internet-of-Things Technologies
    Chew, Kevin Thomas
    Jo, Riady Siswoyo
    Lu, Marlene
    Raman, Valliappan
    Then, Patrick Hang Hui
    11TH IEEE SYMPOSIUM ON COMPUTER APPLICATIONS & INDUSTRIAL ELECTRONICS (ISCAIE 2021), 2021, : 228 - 232
  • [8] Internet of Things Empowered Smart Greenhouse Farming
    Rayhana, Rakiba
    Xiao, Gaozhi
    Liu, Zheng
    IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION, 2020, 4 (03): : 195 - 211
  • [9] Integration of Internet-of-Things as sustainable smart farming technology for the rearing of black soldier fly to mitigate food waste
    Van, Josiah Cheng Foong
    Tham, Pei En
    Lim, Hooi Ren
    Khoo, Kuan Shiong
    Chang, Jo-Shu
    Show, Pau Loke
    JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS, 2022, 137
  • [10] Towards a Sustainable Circular Economy: Algae-Based Bioplastics and the Role of Internet-of-Things and Machine Learning
    Bin Abu Sofian, Abu Danish Aiman
    Lim, Hooi Ren
    Manickam, Sivakumar
    Ang, Wei Lun
    Show, Pau Loke
    CHEMBIOENG REVIEWS, 2024, 11 (01) : 39 - 59