Towards The Creation Of The Future Fish Farm

TL;DR

This paper proposes a secure, distributed ledger-based ecosystem for fish farms using Hyperledger Fabric, aiming to improve data accuracy and decision-making in aquaculture management.

Contribution

It introduces a novel fish farm ecosystem architecture leveraging private blockchain technology for secure data storage and analysis, surpassing traditional methods.

Findings

Demonstrates a proof-of-concept for the blockchain-based fish farm system.

Shows improved data security and accuracy in fish farm monitoring.

Highlights potential for enhanced decision-making in aquaculture.

Abstract

A fish farm is an area where fish raise and bred for food. Fish farm environments support the care and management of seafood within a controlled environment. Over the past few decades, there has been a remarkable increase in the calorie intake of protein attributed to seafood. Along with this, there are significant opportunities within the fish farming industry for economic development. Determining the fish diseases, monitoring the aquatic organisms, and examining the imbalance in the water element are some key factors that require precise observation to determine the accuracy of the acquired data. Similarly, due to the rapid expansion of aquaculture, new technologies are constantly being implemented in this sector to enhance efficiency. However, the existing approaches have often failed to provide an efficient method of farming fish. This work has kept aside the traditional approaches and opened up new dimensions to perform accurate analysis by adopting a distributed ledger technology. Our work analyses the current state-of-the-art of fish farming and proposes a fish farm ecosystem that relies on a private-by-design architecture based on the Hyperledger Fabric private-permissioned distributed ledger technology. The proposed method puts forward accurate and secure storage of the retrieved data from multiple sensors across the ecosystem so that the adhering entities can exercise their decision based on the acquired data. This study demonstrates a proof-of-concept to signify the efficiency and usability of the future fish farm.