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. 2024 Sep 29;14(1):22589.
doi: 10.1038/s41598-024-69513-1.

Internet of things (IoT) based saffron cultivation system in greenhouse

Rabia Khan  1 , Muhammad Shoaib Farooq  1 , Adel Khelifi  2 , Umer Ahmad  3 , Faizan Ahmad  4 , Shamyla Riaz  1
Affiliations

Internet of things (IoT) based saffron cultivation system in greenhouse

Rabia Khan et al. Sci Rep. .

Abstract

Saffron is the world's most expensive and legendary crop that is widely used in cuisine, drugs, and cosmetics. Therefore, the demand for saffron is increasing globally day by day. Despite its massive demand the cultivation of saffron has dramatically decreased and grown in only a few countries. Saffron is an environment-sensitive crop that is affected by various factors including rapid change in climate, light intensity, pH level, soil moisture, salinity level, and inappropriate cultivation techniques. It is not possible to control many of these environmental factors in traditional farming. Although, many innovative technologies like Artificial Intelligence and Internet of Things (IoT) have been used to enhance the growth of saffron still, there is a dire need for a system that can overcome primary issues related to saffron growth. In this research, we have proposed an IoT-based system for the greenhouse to control the numerous agronomical variables such as corm size, temperature, humidity, pH level, soil moisture, salinity, and water availability. The proposed architecture monitors and controls environmental factors automatically and sends real-time data from the greenhouse to the microcontroller. The sensed values of various agronomical variables are compared with threshold values and saved at cloud for sending to the farm owner for efficient management. The experiment results reveal that the proposed system is capable to maximize saffron production in the greenhouse by controlling environmental factors as per crop needs.

Keywords: Agronomical factors; Architecture; Greenhouse; Internet of things; IoT sensors; Saffron.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Benefits of Saffron in cosmetology, health and food industry.
Figure 2
Figure 2
Circuitry diagram showing connection between sensors MCU and numerous devices.
Figure 3
Figure 3
Block diagram for IOT based greenhouse for monitoring and controlling saffron.
Figure 4
Figure 4
Architectural diagram of IOT based greenhouse for saffron.
Figure 5
Figure 5
(A) Saffron corms; (B) hardware components for greenhouse; (C) complete setup of greenhouse; (D) greenhouse system with pump on; (E) notification app for greenhouse; (F) saffron sprouting.
Figure 6
Figure 6
Flow chart diagram of IOT based greenhouse for saffron.
See this image and copyright information in PMC

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References

    1. Bragaglio, A. et al. A comparison between two specialized dairy cattle farms in the upper Po Valley. Precision agriculture as a strategy to improve sustainability. Clean. Environ. Syst.11(October), 100146. 10.1016/j.cesys.2023.100146 (2023).
    1. Zhao, W., Wang, X., Qi, B. & Runge, T. Ground-level mapping and navigating for agriculture based on IoT and computer vision. IEEE Access10.1109/ACCESS.2020.3043662 (2020). - PubMed
    1. Xu, J., Gu, B. & Tian, G. Review of agricultural IoT technology. Artif. Intell. Agric.6, 10–22. 10.1016/j.aiia.2022.01.001 (2022).
    1. Alzubi, A. A. & Galyna, K. Artificial intelligence and internet of things for sustainable farming and smart agriculture. IEEE Access11(June), 78686–78692. 10.1109/ACCESS.2023.3298215 (2023).
    1. “2023-Machine learning‑based optimal.pdf.”

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