Marri, Deva Loknathan (2023) Enhancing Agriculture Production Engine using Machine learning with Robust Cloud Security Measures. Masters thesis, Dublin, National College of Ireland.
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Abstract
Secure and better crop recommendations in agriculture are made possible by this research’s Agricultural Optimization Engine, which integrates machine learning with partial homomorphic encryption for cloud security. Our new technique was motivated by the fact that traditional approaches often Endanger data privacy. As part of our contribution, In this process, partial homomorphic encryption provides safe data processing while deploying an accurate logistic regression model for crop suggestions. The effectiveness of the system in making precise suggestions while protecting sensitive data is shown by our findings. In order to maximize agricultural productivity, this study lays the framework for future developments in safe data analytics by bridging the gap between machine learning and data security in agriculture. The solution it provides to farming businesses is both practical and scalable. Implications for both theory and practice abound in the proposed system, which aims to improve the confidentiality of agricultural data while also giving farmers access to a safe and dependable resource for managing their crops.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Makki, Ahmed UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science S Agriculture > S Agriculture (General) T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
Divisions: | School of Computing > Master of Science in Cloud Computing |
Depositing User: | Ciara O'Brien |
Date Deposited: | 08 Apr 2025 17:58 |
Last Modified: | 08 Apr 2025 17:58 |
URI: | https://norma.ncirl.ie/id/eprint/7390 |
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