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From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses. / Fayoumi, Amjad; Orachorn, Chanapat ; Shi, Xiao .
The 7th International Conference on Big Data and Artificial Intelligence: (BDAI 2024). IEEE, 2024.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Fayoumi, A, Orachorn, C & Shi, X 2024, From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses. in The 7th International Conference on Big Data and Artificial Intelligence: (BDAI 2024). IEEE. https://doi.org/10.1109/BDAI62182.2024.10692750

APA

Fayoumi, A., Orachorn, C., & Shi, X. (2024). From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses. In The 7th International Conference on Big Data and Artificial Intelligence: (BDAI 2024) IEEE. https://doi.org/10.1109/BDAI62182.2024.10692750

Vancouver

Fayoumi A, Orachorn C, Shi X. From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses. In The 7th International Conference on Big Data and Artificial Intelligence: (BDAI 2024). IEEE. 2024 Epub 2024 Jul 5. doi: 10.1109/BDAI62182.2024.10692750

Author

Fayoumi, Amjad ; Orachorn, Chanapat ; Shi, Xiao . / From Big Data to Massive Data : Towards a Massive Data Storage Solution for the Internet of Senses. The 7th International Conference on Big Data and Artificial Intelligence: (BDAI 2024). IEEE, 2024.

Bibtex

@inproceedings{92ceba7f33ed43fd8b07ad348c1b6001,
title = "From Big Data to Massive Data: Towards a Massive Data Storage Solution for the Internet of Senses",
abstract = "The increased maturity of current digitalization techniques expands the scope of practical deployments in various fields, including the precipitation of “digital biology” as a novel and highly important new field of research. This research area specializes in the convergence of various digital technologies and investigations into biology, offering the possibility to produce new comprehension of and applications for living systems by leveraging frameworks of digital technology. The enhanced scope of current capacities in computation facilitates simulated models of multifaceted biological artefacts and novel ways to gather, analyze, and interpret data, moving far beyond the primitive scope of legacy solutions in this field. This paper explores potential “massive data” databases, developing a conceptual model to move beyond the existing “big data” paradigm.",
author = "Amjad Fayoumi and Chanapat Orachorn and Xiao Shi",
year = "2024",
month = oct,
day = "1",
doi = "10.1109/BDAI62182.2024.10692750",
language = "English",
isbn = "9798350352016",
booktitle = "The 7th International Conference on Big Data and Artificial Intelligence",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - From Big Data to Massive Data

T2 - Towards a Massive Data Storage Solution for the Internet of Senses

AU - Fayoumi, Amjad

AU - Orachorn, Chanapat

AU - Shi, Xiao

PY - 2024/10/1

Y1 - 2024/10/1

N2 - The increased maturity of current digitalization techniques expands the scope of practical deployments in various fields, including the precipitation of “digital biology” as a novel and highly important new field of research. This research area specializes in the convergence of various digital technologies and investigations into biology, offering the possibility to produce new comprehension of and applications for living systems by leveraging frameworks of digital technology. The enhanced scope of current capacities in computation facilitates simulated models of multifaceted biological artefacts and novel ways to gather, analyze, and interpret data, moving far beyond the primitive scope of legacy solutions in this field. This paper explores potential “massive data” databases, developing a conceptual model to move beyond the existing “big data” paradigm.

AB - The increased maturity of current digitalization techniques expands the scope of practical deployments in various fields, including the precipitation of “digital biology” as a novel and highly important new field of research. This research area specializes in the convergence of various digital technologies and investigations into biology, offering the possibility to produce new comprehension of and applications for living systems by leveraging frameworks of digital technology. The enhanced scope of current capacities in computation facilitates simulated models of multifaceted biological artefacts and novel ways to gather, analyze, and interpret data, moving far beyond the primitive scope of legacy solutions in this field. This paper explores potential “massive data” databases, developing a conceptual model to move beyond the existing “big data” paradigm.

U2 - 10.1109/BDAI62182.2024.10692750

DO - 10.1109/BDAI62182.2024.10692750

M3 - Conference contribution/Paper

SN - 9798350352016

BT - The 7th International Conference on Big Data and Artificial Intelligence

PB - IEEE

ER -