使用深度学习,物联网和移动应用程序,用于园艺农业的强大的水耕系统.
Nadim Nawshad1, Md Asraf Ali1,2, Ku Nurul Fazira3
1Department of Computer Science, American International University - Bangladesh, Dhaka, Bangladesh.
PloS one
|September 8, 2025
概括
这项研究为孟加拉国农民开发了一种易于使用的水培系统,具有自动指导方针和疾病检测. 智能农业技术改善了作物监测和管理,提高了农业效率.
科学领域:
- 农业技术 农业技术
- 智能农业系统 智能农业系统
- 培技术是一种水培技术.
背景情况:
- 在孟加拉国,有限的农民素养给采用先进的水培农业技术带来了挑战.
- 需要用户友好的系统来帮助农民监控和运行智能水培装置.
研究的目的:
- 引入一个强大的水培系统,自动指导,监测和疾病检测.
- 为了提高农民在水培种植过程中的便利性和减轻压力.
主要方法:
- 硬件实现使用WeMos控制器进行系统操作.
- 使用深度学习模型集成的疾病检测.
- 开发一个用于分析传感器数据和自动警报的移动应用程序.
主要成果:
- 该系统实现了98.5%的高疾病检测精度.
- 大约80%的受访农民表示,该系统对种植,可用性和监测都有好处.
结论:
- 拟议的系统显著提高了水培农业的运营效率和可持续性.
- 该技术显示出改善资源管理和有效预防农业疾病战略的潜力.
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