How does the Internet of Things (IoT) help in microalgae biorefinery?

Wang, Kexin; Khoo, Kuan Shiong; Leong, Hui Yi; Nagarajan, Dillirani; Chew, Kit Wayne; Ting, H. Y.; Selvarajoo, Anurita; Chang, Jo‐Shu; Show, Pau Loke

doi:10.1016/j.biotechadv.2021.107819

Cited by 59 publications

(40 citation statements)

References 188 publications

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“…Following the critique of various arguments made concerning the reliability of sensors [50][51][52][53], the researcher notes that the accuracy of IoT sensors in agricultural settings was influenced by application-and context-specific factors. The worldview is corroborated by Wang et al [1], who reported high accuracy in sensors designed to measure biological parameters in microalgae farms. The high accuracy of the sensors was linked to optimal design configurations [1].…”

Section: Growthmentioning

confidence: 80%

“…Presently, there is a wide array of IoT-based sensors for smart greenhouses, including plant growth sensors, temperature and humidity sensors, insect detection sensors, soil temperature, pH, and moisture sensors, and solar radiation, atmospheric pressure, wind speed, and CO 2 (and other gas) sensors, which rely on Bragg, piezoelectric, electrochemical, electromagnetic [31], and fiber-optic technologies for accurate assessment of the desired parameters [47] (see Table 1). The parameters of interest include different wavelengths of light, photocurrent, fluorescence intensity, the fluorescent signal emitted by plant chlorophyll, optical density, and the electrochemical signal generated by enzyme-catalyzed redox reaction (SHA principle) [1]. Advances in research and design have resulted in the development of electromagnetic sensors for analyzing chlorophyll values and nitrogen concentration in plants; this approach relies on light reflectance and pulsating laser diodes [31].…”

Section: Iot-based Sensors For Smart Greenhousesmentioning

confidence: 99%

“…Considering that Rayhana et al [4] and Castañeda-Miranda et al [49] observed that IoT sensors achieved superior performance in the optimization of the greenhouse microclimate, the low accuracy reported by Ryder et al [48] could be attributed to the sensor properties or poor control of external variables. Such drawbacks can be offset by system maintenance and calibration with spectrophotometers [1] and customization of the system to match the local environmental conditions. Alternatively, the ongoing deployment of the 5G network would catalyze the expansion of IoT infrastructure and the deployment of advanced sensors with better precision [37].…”

Section: Growthmentioning

confidence: 99%

“…Alternatively, the ongoing deployment of the 5G network would catalyze the expansion of IoT infrastructure and the deployment of advanced sensors with better precision [37]. From another perspective, the contradicting evidence on the accuracy of the sensors documented by Ryder et al [48] and Wang et al [1] raises fundamental questions concerning the reliability of sensors for agricultural applications, which might, in turn, affect the commercial uptake of sensors. The central role of accurate sensor data on IoT platform data integration, real-time visualization, and application prototyping is illustrated in Figure 3.…”

Section: Growthmentioning

confidence: 99%

“…This review article synthesizes current scholarly research on the application of IoT for optimized greenhouse environments with an emphasis on IoT-mediated and optimized microclimates for crop production. The focus on IoT is grounded on the immense contribution of technology to modern civilizations after computers and the internet [1]. The immense contribution of IoT in agriculture and commercial greenhouses could be linked to the integration of intelligent machines, actuators, sensors, unmanned aerial systems, radio frequency identification (RFID) devices, big data analytics, artificial intelligence, and satellites [2], and this has facilitated its widespread application in various agricultural and non-agricultural applications, including intelligent farming and frost prevention in greenhouses [3], intelligent control of greenhouse structures [4], fire hazard prevention [5], transition to agriculture 4.0 [6], precise-control of nutrients in soilless greenhouse cultivation [7], smart cities [8,9], emission monitoring [10], distributed/decentralized energy storage, solar-powered sensors [11], smart feeding, shading and lighting control, and security [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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Application of Internet of Things (IoT) for Optimized Greenhouse Environments

Maraveas

Bartzanas

2021

AgriEngineering

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This review presents the state-of-the-art research on IoT systems for optimized greenhouse environments. The data were analyzed using descriptive and statistical methods to infer relationships between the Internet of Things (IoT), emerging technologies, precision agriculture, agriculture 4.0, and improvements in commercial farming. The discussion is situated in the broader context of IoT in mitigating the adverse effects of climate change and global warming in agriculture through the optimization of critical parameters such as temperature and humidity, intelligent data acquisition, rule-based control, and resolving the barriers to the commercial adoption of IoT systems in agriculture. The recent unexpected and severe weather events have contributed to low agricultural yields and losses; this is a challenge that can be resolved through technology-mediated precision agriculture. Advances in technology have over time contributed to the development of sensors for frost prevention, remote crop monitoring, fire hazard prevention, precise control of nutrients in soilless greenhouse cultivation, power autonomy through the use of solar energy, and intelligent feeding, shading, and lighting control to improve yields and reduce operational costs. However, particular challenges abound, including the limited uptake of smart technologies in commercial agriculture, price, and accuracy of the sensors. The barriers and challenges should help guide future Research & Development projects and commercial applications.

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Section: Growthmentioning

confidence: 80%

Section: Iot-based Sensors For Smart Greenhousesmentioning

confidence: 99%

Section: Growthmentioning

confidence: 99%

Section: Growthmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Internet of Things (IoT) for Optimized Greenhouse Environments

Maraveas

Bartzanas

2021

AgriEngineering

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Design, fabrication, automation, and scaleup of anaerobic reactors for waste management and bioenergy recovery

Fröner‐Lacerda,

Sganzerla,

Lacerda

et al. 2024

Biofuels Bioprod Bioref

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Digitally controlled reactors can optimize biological reactions and process control through a neural network system. This study reports on the design, fabrication, and automation of a laboratory‐scale anaerobic reactor for the management of agrifood byproducts and bioenergy recovery. The process described here can digitally control the operational parameters, which is beneficial for stable methane production. The proposed process comprises the digital measurement of temperature, pH, humidity, biogas volume, and methane composition by integrating the data in a processor module. The proposed automated reactor can assist significantly in controlling and monitoring the anaerobic digestion process, providing decision making during waste management and bioenergy recovery. A case study is described with the application of automated reactors in a pilot‐scale plant, operated with the flow of 8 m3 slaughterhouse wastewater per day and a biogas production of 10 m3 h−1. The automated pilot‐scale process presents many advantages, including a continuous mode of operation and a faster adaptation of the microorganisms to the substrate, improving biogas production.

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Monitoring microalgal growth of Chlorella minutissima with a new all solid‐state contact nitrate selective sensor

Balkanli

Işıldak

İnan

et al. 2022

Biotechnology Progress

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As third generation feedstock, microalgae are microorganisms that can grow only in the optimum conditions. There are parameters including the concentration of macro and microelements in nutrient solution, pH, temperature and light intensity that have significant impact on microalgal growth. In recent years, various sensing devices have been developed for sensitive measurement of these parameters during microalgal growth. In this study, a new potentiometric nitrate selective sensor was developed to indicate the nitrate uptake of microalgae and the effect of nitrate nutrient on microalgal growth, specifically, and this sensor was successfully applied to determine nitrate concentration in medium during microalgal growth. Moreover, the effects of nitrate, carbonate and phosphate concentration in the growth medium on biomass production of Chlorella minutissima were investigated by using Box–Behnken design method, and optimum conditions were determined for the highest biomass production of microalgae. As a result of the experiments, it was seen that the highest C. minutissima production was achieved using the medium consist of 2.63 g/L NaNO3, 0.35 g/L Na2CO3 and 0.4 g/L KH2PO4. Statistically, it was observed that there was a proportional relationship between the microalgae production and investigated parameters such as carbon, nitrogen and phosphate amounts of culture mediums. The electrode showed a wide linear range between 1.0 × 10−1 and 5.0 × 10−5 M with a detection limit of the 5 × 10−6 M and the response time was found as 10 s. The results showed that developed nitrate selective sensor could be successfully applied for continuous measurement of nitrate in microalgal productions at reduced cost.

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How does the Internet of Things (IoT) help in microalgae biorefinery?

Cited by 59 publications

References 188 publications

Application of Internet of Things (IoT) for Optimized Greenhouse Environments

Application of Internet of Things (IoT) for Optimized Greenhouse Environments

Design, fabrication, automation, and scaleup of anaerobic reactors for waste management and bioenergy recovery

Monitoring microalgal growth of Chlorella minutissima with a new all solid‐state contact nitrate selective sensor

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