A Modularized IoT Monitoring System with Edge-Computing for Aquaponics

Wan, Shiqi; Zhao, Kun; Lu, Zhongling; Li, Jianke; Lu, Tiangang; Wang, Haihua

doi:10.3390/s22239260

Cited by 10 publications

(3 citation statements)

References 14 publications

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“…Plants are efficient biofactories for the manufacture of recombinant proteins and growth monitoring is a vital aspect when it comes to both laboratory scale and commercial production. Several automation technologies including affordable sensors built on Raspberry Pi, robotics and high-definition cameras work based on image acquisition ( Jahnke et al., 2016 ; Jolles, 2021 ; Banerjee et al., 2022 ; Wan et al., 2022 ). The camera sensors have been deployed to analyze the plant growth patterns, phenotypes such as plant morphology, height, canopy, temperature, leaf biomass, leaf area index, greenness, age and different stresses.…”

Section: Ai-based ML Algorithms In Recombinant Protein Productionmentioning

confidence: 99%

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Parthiban,

Vijeesh,

Gayathri

et al. 2023

Front. Plant Sci.

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Recombinant biopharmaceuticals including antigens, antibodies, hormones, cytokines, single-chain variable fragments, and peptides have been used as vaccines, diagnostics and therapeutics. Plant molecular pharming is a robust platform that uses plants as an expression system to produce simple and complex recombinant biopharmaceuticals on a large scale. Plant system has several advantages over other host systems such as humanized expression, glycosylation, scalability, reduced risk of human or animal pathogenic contaminants, rapid and cost-effective production. Despite many advantages, the expression of recombinant proteins in plant system is hindered by some factors such as non-human post-translational modifications, protein misfolding, conformation changes and instability. Artificial intelligence (AI) plays a vital role in various fields of biotechnology and in the aspect of plant molecular pharming, a significant increase in yield and stability can be achieved with the intervention of AI-based multi-approach to overcome the hindrance factors. Current limitations of plant-based recombinant biopharmaceutical production can be circumvented with the aid of synthetic biology tools and AI algorithms in plant-based glycan engineering for protein folding, stability, viability, catalytic activity and organelle targeting. The AI models, including but not limited to, neural network, support vector machines, linear regression, Gaussian process and regressor ensemble, work by predicting the training and experimental data sets to design and validate the protein structures thereby optimizing properties such as thermostability, catalytic activity, antibody affinity, and protein folding. This review focuses on, integrating systems engineering approaches and AI-based machine learning and deep learning algorithms in protein engineering and host engineering to augment protein production in plant systems to meet the ever-expanding therapeutics market.

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Section: Ai-based ML Algorithms In Recombinant Protein Productionmentioning

confidence: 99%

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Parthiban,

Vijeesh,

Gayathri

et al. 2023

Front. Plant Sci.

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“…The architecture of the model is shown in Fig. 9 [49]. The IoT based sensing consists of three layers including Application, Network and Perception layer allow the system to communicate and pass information without human interaction [50].…”

Section: Literature Reviewmentioning

confidence: 99%

A Systematic Literature Review of Computational Studies in Aquaponic System

Taji,

Sohail,

Ghanimi

et al. 2023

IJACSA

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The word aquaponics means the growth of aquatic organisms as well as plants in the controlled environment. As the nutrients used for sustainable plant growth is obtained from aquatic organisms and the nutrients that are absorbed by the plants remediate the water for the aquatic life. The advancement in the computational studies plays a vital role in every field of life. The aim of the proposed study is to deeply analyze the computational studies that used IoT, AI, Machine learning and deep learning for aquaponic systems between the years 2019 to 2022. The literature survey deeply discuss the proposed methodology, comprehends the fundamental researches, tool, advantages, limitations, concepts, and results of the recent studies proposed by the researchers in context of aquaponic system. The proposed study extract 41 research articles from these libraries based on year of publication, title, methodology, citation, paper quality and abstract. These articles are collected from seven different research article libraries including Google Scholar, Worldwide Science, IEEE Xplore, Google Books, Refseek, ACM digital Library and Science Direct. This study develops a state of the art research for the next researchers to work on the loopholes of the previous researches in an efficient manner. The results of the proposed study shows that the implementation of IoT based machine learning and deep learning framework shows state of the art results for the nutrients regulation, sensing, monitoring and controlling of the aquaponic environment. It is concluded from the proposed study that there need to be develop ensemble learning model with an efficient dataset in context of aquaponic environment.

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“…The authors of [9] provide an analysis of the possibilities of using a Raspberry Pi microcomputer on a ship, while an overview of the components for an onboard control system of an autonomous ship is presented in [10]. In [11], a Raspberry Pi microcomputer embedded with image processing algorithms is introduced to realise edgecomputing. In [12], the study thoroughly examines how blockchain-based decentralised architecture can potentially improve IoT access management.…”

Section: Literature Reviewmentioning

confidence: 99%

A Personal Microcomputer as an Access Control Management Platform in Road Transport

Wójcik,

Neumann

2023

Applied Sciences

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For many years, the use of new computer systems to control various elements of everyday human life has been observed. Separate systems manage access control; others are used to control blinds and roller shutters; and others manage systems in the garden. Many of these systems can be integrated using available systems. This paper presents an example of an access control management system based on the Raspberry Pi microcomputer and shows an analysis of its performance, accuracy, and possibility of improvement. This study used official devices manufactured by the Raspberry Pi Foundation; however, it is possible to create a similar system with custom parts. This project used open-source software. The authors argued that it is possible to create an autonomous vehicle access control system using microcomputers and optical character recognition technology. Using simple devices, the plate recognition system was built and tested, proving the thesis that it is possible to build an access control system using available devices. This also confirms the thesis that microcomputers can be used to control other systems in the human environment.

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A Modularized IoT Monitoring System with Edge-Computing for Aquaponics

Cited by 10 publications

References 14 publications

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

Artificial intelligence-driven systems engineering for next-generation plant-derived biopharmaceuticals

A Systematic Literature Review of Computational Studies in Aquaponic System

A Personal Microcomputer as an Access Control Management Platform in Road Transport

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