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Machine Learning-based Peer-to-Peer Platform for Precision Agriculture in Crop Growth and Disease Monitoring

Imtiaz Ahmed, Gousia Habib, Parmod Kumar Yadav

Abstract


Farmer suicides are a significant problem in India due to various circumstances. One of the main problems is the financial side of managing and growing crops while still trying to make a profit. This study proposes a decentralized platform for buying and selling agricultural produce by connecting farmers with individuals interested in investing in their fields and continuous monitoring of quality and crop health using IoT, Blockchain, and Machine Learning for disease prediction in agricultural produce. Blockchain has swiftly become a key technology in various precision agriculture applications. The requirement for smart peer-to-peer systems capable of verifying, securing, monitoring, and analysing agricultural data has prompted researchers to consider developing blockchain-based IoT systems in precision agriculture. The significance of blockchain in replacing traditional means of storing, sorting, and sharing agricultural data with a more trustworthy, immutable, transparent, and decentralized system is critical. In precision farming, the Internet of Things and blockchain will transform us from having merely smart farms to having the internet of smart farms, giving us more control over supply-chain networks. As a result of this combination, precision agriculture will be managed with more autonomy and intelligence in a more efficient and optimum manner. This research provides a thorough examination of the value of combining blockchain and IoT in developing smart precision agriculture applications. Novel blockchain models were also offered in the study, which can be employed as essential solutions to major difficulties in IoT-based precision agriculture systems. Furthermore, the study examined and thoroughly highlighted the major roles and strengths of typical blockchain platforms used to control several precision agriculture sub-sectors, such as crops, livestock grazing, and the food supply chain. Finally, the study examined some of the security and privacy concerns and blockchain-related issues that have hampered the development of blockchain-based precision agriculture systems. A farmer's difficulty may be the same as another farmer's problem in another place. It has always been difficult to provide information to farmers and connect them. Cloud computing and economic development are viable options for addressing these issues.


Keywords


Machine learning, blockchain, precision agriculture, food supply, blockchain technology, IoT

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References


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