Proposal of model for prediction of grape processing and spraying time by using IoT smart agriculture sensor data

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Jakup Fondaj, Mentor Hamit, Samedin Krrabaj, Xhemal Zenuni, Jaumin Ajdari
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引用次数: 0

Abstract

The grape industry's impact on agriculture and the economy requires precise forecasting for processing and spraying schedules to optimize production. This article introduces an innovative IoT-based model for predicting optimal timings in grape processing and spraying. By integrating real-time environmental and viticultural data, the model improves decision-making, enhancing product quality, reducing energy consumption, and increasing operational efficiency. Crucially, SARIMA predictive algorithms forecast parameters like temperature, humidity, wind speed, and air pressure. This comprehensive model transforms the grape industry, offering advanced decision support and promoting sustainable, resource-efficient production. The research signals a potential shift to precision agriculture, balancing economic viability with environmental stewardship in grapes.
利用物联网智能农业传感器数据预测葡萄加工和喷洒时间的模型建议
葡萄产业对农业和经济的影响要求对加工和喷洒计划进行精确预测,以优化生产。本文介绍了一种基于物联网的创新模型,用于预测葡萄加工和喷洒的最佳时间。通过整合实时环境和葡萄栽培数据,该模型可改善决策,提高产品质量,降低能耗,提高运营效率。最重要的是,SARIMA 预测算法可预测温度、湿度、风速和气压等参数。这一综合模型改变了葡萄产业,提供了先进的决策支持,促进了可持续的资源节约型生产。这项研究预示着向精准农业的潜在转变,在葡萄的经济可行性与环境管理之间实现平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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