Blockchain and Big Data to Revolutionize Archaeological Photogrammetry (AP): A Safe and Effective Method

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ID: 313252
2023
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Abstract
The enormous amount of data circulating via the internet today has resulted in the generation of a vast amount of complex information. Large datasets from various sectors, including academia, businesses, energy, healthcare, and more, contain extremely large and diverse sets of data that are difficult to manage. This is known as "big data," and it presents a significant challenge in terms of effectively handling such large volumes of data, particularly in the field of photogrammetry. Traditional methods are incapable of dealing with large amounts of data, necessitating the development of more sophisticated tools. Big data is often described using the "V's" characteristics, which originally included volume, velocity, and variety. Over time, these six V's have been expanded through research to a total of 65 V's. Some of these V's were identified by the author of this paper, which means the number has increased by almost twenty times. Researchers have conducted numerous studies to identify and compare all of these characteristics in order to answer the longstanding question of "How many V's characteristics are there in big data with artificial intelligence and blockchain?" This paper provides a comprehensive overview of all known big data V's characteristics, as well as their strengths and limitations in the context of photogrammetry and blockchain.
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Authors Fatima Bukhari, Shaista Ilyas, Laiba Rehman, Humera Batool Gill, Khadija Kanwal, Nadeem Iqbal Kajla
Journal Journal of Computing & Biomedical Informatics
Year 2023
DOI
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URL
https://jcbi.org/index.php/Main/article/view/176
Keywords Keywords not found

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