Issue |
EPJ Web Conf.
Volume 325, 2025
International Conference on Advanced Physics for Sustainable Future: Innovations and Solutions (IEMPHYS-24)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 35 | |
DOI | https://doi.org/10.1051/epjconf/202532501004 | |
Published online | 05 May 2025 |
https://doi.org/10.1051/epjconf/202532501004
Transforming Precision Agriculture with Quantum Computing: A Novel Algorithm for Boosting Crop Yields and Optimizing Resources
1 Final Year B. Tech Student, Computer Science and Engineering Department, Abacus Institute of Engineering and Management, Mogra, India
2 Professor, Basic Science and Humanities Department, Institute of Engineering & Management (School of University of Engineering and Management), Kolkata, India
Published online: 5 May 2025
New zenith of agriculture technology, precision agriculture has emerged as a crucial tool to feed India and manage the scarce irrigation facility where nearly 600 million people are facing hardship of severe water crisis. This paper proposes a new algorithm of variational quantum computing (VQC), which has showed potential in optimizing crop yield and resource utilisation based on the data sets such as soil quality, climate and genetic makeup of crops. The algorithm makes use of qubits to allow the real time data processing through IoT sensors to allow for real time monitoring and decision making. Two trials performed on various agricultural data sets this approach presented about 30% increase in the predictive accuracy of crop yields and 25% decrease in water and fertilizer usage. Furthermore, enhanced detection capacities enhanced illness control capacities by 40% thereby leading to decreased crop losses. In addition to bridging significant gaps in the currently available literature, this paper incorporates quantum computing into precision agriculture to offer farmers and other stakeholders’ usable formulations that may shape the future of farming with the help of advancing quantum technologies.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.