智能作物种植系统使用自动化农业监测环境在孟加拉国背景下农业农业
Md Bayazid Rahman1, Joy Dhon Chakma1, Abdul Momin2
1Department of Computer Science and Engineering, Faculty of Science and Technology, Notre Dame University Bangladesh, Dhaka 1000, Bangladesh.
Sensors (Basel, Switzerland)
|October 28, 2023
概括
这项研究为孟加拉国农业引入了物联网 (IoT) 框架,将作物预测精度提高到87.38%,并提高了农民的决策能力.
科学领域:
- 农业技术 农业技术
- 数据科学数据科学数据科学
- 云计算 云计算 云计算
背景情况:
- 孟加拉国的农业部门在生产率和资源管理方面面临着挑战.
- 像物联网 (IoT) 这样的变革性技术为农业增强提供了潜在的解决方案.
研究的目的:
- 为孟加拉国农业开发和评估一个强大的框架,整合物联网,数据挖掘和云系统.
- 提高作物生产率,优化水资源管理,并实现实时作物预测.
主要方法:
- 实施一个综合框架,结合物联网设备,数据挖掘算法和基于云的监控.
- 对拟议的农业物联网模型进行严格的实验和绩效评估.
主要成果:
- 拟议的框架在预测作物收获数据方面实现了87.38%的准确性.
- 在提高农业经营的有效性和透明度.
结论:
- 物联网框架具有改变孟加拉国农业的巨大潜力,特别是在依赖季风的地区.
- 赋予农民以数据驱动的洞察力,以改善决策和增加农业产量.
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