Issue |
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
|
|
---|---|---|
Article Number | 01067 | |
Number of page(s) | 11 | |
Section | Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development | |
DOI | https://doi.org/10.1051/shsconf/202521601067 | |
Published online | 23 May 2025 |
IoT-Enabled Smart Greenhouses: Real-Time Environmental Monitoring and Climate Control
1
Department of CS & IT, Kalinga University,
Raipur, India
2
Research Scholar, Department of CS & IT, Kalinga University,
Raipur, India
* Corresponding author: ku.SonaliMondal@kalingauniversity.ac.in
With the upsurge in demand for the sustainable agriculture practices, the development of IoT driven smart greenhouses has become very popular as it not only increases the crop production but also reduces resource use. But the current practice of greenhouse management is usually limited to real-time monitoring of few environmental parameters and energy intensive climate control methods resulting in conditions suboptimal for plant growth. The goal of this research is to build smart greenhouse system where the environmental parameters are temperature, humidity, soil moisture and light levels are monitored in real time using IoT. The system achieves improved environmental regulation and resource management through integrating the sensors with a cloud based IoT solution. The increase in greenhouse efficiency is achieved in part, through rule based control and fuzzy logic as well as machine learning based predictive methods. Experimental results indicate that integration of cloud and machine learning based predictive control results in optimal environmental conditions which leads to 30 percent reduction in the water use and 25 percent reduction in the energy consumption compared to conventional methods. Utilizing this scalable system means it has provided a solution that is modern and sustainable for greenhouse operations, leading to better overall agricultural efficiency and the pursuit of smarter farming methods.
© 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.