1
Universidad Regional Autónoma de los Andes (UNIANDES), Ecuador
(ua.faustovizcaino@uniandes.edu.ec)
2
Universidad Regional Autónoma de los Andes (UNIANDES), Ecuador
(dir.santodomingo@uniandes.edu.ec)
3
Universidad Regional Autónoma de los Andes (UNIANDES), Ecuador
(uq.sistemas@uniandes.edu.ec)
Abstract :
The intersection of IoT technology and machine learning has ushered in a new era of precision agriculture, offering innovative solutions to the pressing challenges of food security and environmental sustainability. This paper presents a comprehensive study on the integration of IoT sensors and machine learning techniques for crop yield prediction, with a focus on the ten most consumed crops worldwide. Leveraging a wealth of historical data encompassing environmental variables, pest conditions, and crop-specific attributes collected by IoT sensors, we develop and rigorously evaluate a predictive model employing gradient-boosting regressors. Our findings reveal that the proposed model excels in capturing the intricate relationships between IoT sensor data and crop yield predictions, outperforming established ML regressors in a series of comprehensive experimental comparisons. These results underscore the potential of data-driven decision-making in agriculture, equipping farmers and policymakers with tools to optimize resource allocation, risk management, and sustainable farming practices. In the context of a growing global population and changing climate, the insights from this research hold significant promise for transforming precision agriculture and enhancing global food production.
Keywords :
Precision Agriculture , IoT Sensors; Agriculture Technology; Sensor Data Analysis; Data-driven Farming , Smart Farming; Predictive Analytics; Agricultural IoT; Sensor Networks.
References :
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| Style | # |
|---|---|
| MLA | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias. "Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach." Fusion: Practice and Applications, Vol. 13, No. 2, 2023 ,PP. 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |
| APA | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias. (2023). Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach. Journal of Fusion: Practice and Applications, 13 ( 2 ), 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |
| Chicago | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias. "Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach." Journal of Fusion: Practice and Applications, 13 no. 2 (2023): 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |
| Harvard | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias. (2023). Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach. Journal of Fusion: Practice and Applications, 13 ( 2 ), 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |
| Vancouver | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias. Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach. Journal of Fusion: Practice and Applications, (2023); 13 ( 2 ): 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |
| IEEE | Fausto Vizcaíno Naranjo, Fredy Cañizares Galarza, Edmundo Jalón Arias, Internet of Things based Predictive Crop Yield Analysis: A Distributed Approach, Journal of Fusion: Practice and Applications, Vol. 13 , No. 2 , (2023) : 106-113 (Doi : https://doi.org/10.54216/FPA.130209) |