使用物联网传感器网络进行智能葡萄藤疾病检测
Mihaela Hnatiuc1, Simona Ghita1, Domnica Alpetri1
1Electronic and Telecommunication Departament, Constanta Maritime University, 104 Mircea cel Batran, 900663 Constanta, Romania.
Bioengineering (Basel, Switzerland)
|September 28, 2023
概括
本研究介绍了一种使用物联网 (IoT) 传感器和机器学习的智能葡萄藤疾病检测系统. 该系统通过分析环境和植物数据准确识别葡萄藤疾病,达到0.05的分类错误率.
科学领域:
- 农业技术 农业技术
- 葡萄种植 葡萄种植 葡萄种植
- 环境监测 环境监测
背景情况:
- 物联网 (IoT) 在农业中越来越重要,用于精确管理.
- 葡萄种植中的物联网应用可以实现自动化疾病监测和预防.
- 葡萄藤疾病的早期检测对于作物产量和质量至关重要.
研究的目的:
- 利用物联网传感器网络开发一种智能葡萄藤疾病检测方法.
- 为早期疾病预测确定关键的环境和植物参数.
- 将物联网传感器数据与经典疾病识别方法进行比较.
主要方法:
- 在罗马尼亚葡萄园部署物联网传感器网络.
- 收集环境和植物相关数据.
- 使用机器学习 (ML) 算法分析传感器数据,包括前神经网络.
- ML结果与经典疾病识别方法的相关性.
主要成果:
- 确定早期葡萄藤健康评估的关键参数.
- 使用feedforward神经网络实现了0.05的分类系统错误率.
- 疾病发生与特定的环境参数相关.
结论:
- 开发的物联网系统有效支持智能葡萄藤疾病检测.
- 与传感器数据集成的ML算法显示出预测葡萄藤疾病的前景.
- 计划在不同的葡萄园地区进行进一步的测试,以验证该系统的稳定性.
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