Issue |
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
|
|
---|---|---|
Article Number | 01036 | |
Number of page(s) | 11 | |
Section | Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development | |
DOI | https://doi.org/10.1051/shsconf/202521601036 | |
Published online | 23 May 2025 |
Robotics in Vertical Farming: Enhancing Automation for Seed Sowing and Harvesting
1
Department of CS & IT, Kalinga University,
Raipur, India
2
Research Scholar, Department of CS & IT, Kalinga University,
Raipur, India
* Corresponding author: ku.chandni.sawlani@kalingauniversity.ac.in
Vertical farming has emerged as a sustainable method to meet the increasing demand for food. However, the labor-intensive nature of tasks such as seed sowing and harvesting has hindered its widespread adoption. Traditional methods are often inefficient, expensive, and yield inconsistent results. This research addresses these challenges by integrating robotic automation into vertical farming to automate seed sowing and harvesting processes. Robotics enables precision seed placement, optimization of resource usage, and enhanced harvesting efficiency, ultimately leading to improved crop yields. The system's feasibility was demonstrated through the implementation of robotic arm manipulation for precise seed planting, automated sensors for monitoring and harvesting, and other innovative techniques. Evaluation criteria included crop yield improvement, labor cost reduction, and efficient resource utilization. The results revealed that the system significantly enhanced crop yield and harvesting efficiency, reduced labor costs, and effectively utilized water and nutrients. This research highlights the potential of robotics to revolutionize vertical farming, offering a paradigm shift toward more efficient and sustainable agricultural practices.
© 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.
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