Semantic Scholar Open Access 2020 168 sitasi

A secure fish farm platform based on blockchain for agriculture data integrity

L. Hang Israr Ullah Do-Hyeun Kim

Abstrak

Abstract Internet of Things (IoT) has opened up a new dimension for smart farming and agriculture because of the natural feature that makes it possible to assign tasks made by a user or that transfers agriculture data obtained through sensors to producers for analysis on various terminal devices. In recent years, heightened interest in agriculture data has arisen since the commercialization of precision agriculture technology. Agriculture data are known to be messy, especially from combine yield monitors, and analysts are concerned with the validity of data, especially given that other people may have impacted data quality at various steps along the data path. The blockchain can be a possible solution to the analyst’s problem of uncertain data quality from prior data manipulation since it ensures data have not been inappropriately manipulated or at the very least documents what changes have been made by specific individuals. This paper proposes a blockchain-based fish farm platform to ensure agriculture data integrity. The designed platform aims to provide fish farmers with secure storage for preserving the large amounts of agriculture data that cannot be tampered with. Diverse processes of the fish farm are executed automatically by using the smart contract to reduce the risk of error or manipulation. A proof of concept that integrates a legacy fish farm system with the Hyperledger Fabric blockchain is implemented on top of the proposed architecture. The efficiency and usability of the proposed platform are demonstrated through a series of experiments using various metrics.

Topik & Kata Kunci

Penulis (3)

L

L. Hang

I

Israr Ullah

D

Do-Hyeun Kim

Format Sitasi

Hang, L., Ullah, I., Kim, D. (2020). A secure fish farm platform based on blockchain for agriculture data integrity. https://doi.org/10.1016/j.compag.2020.105251

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Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Total Sitasi
168×
Sumber Database
Semantic Scholar
DOI
10.1016/j.compag.2020.105251
Akses
Open Access ✓