一个集成的智能池水质监测和养鱼建议 Aquabot系统
Md Moniruzzaman Hemal1, Atiqur Rahman1, Nurjahan1,2
1Department of IoT and Robotics Engineering, Bangabandhu Sheikh Mujibur Rahman Digital University, Bangladesh, Kaliakair, Gazipur 1750, Bangladesh.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
AquaBot是一个物联网 (IoT) 系统,使用机器人和机器学习 (ML) 来监测水质并推鱼类. 这项技术通过降低成本和人工劳动来提高渔场生产力和利能力.
科学领域:
- 水产养殖技术 水产养殖技术
- 人工智能在农业中的应用
- 环境监测系统环境监测系统
背景情况:
- 传统的养鱼业由于劳动密集型监测,疾病爆发和鱼类死亡率而面临经济损失.
- 需要自动化鱼类推系统,以优化基于水质的利能力.
- 有效的水质监测可以降低运营成本,增加鱼产量.
研究的目的:
- 开发一个基于物联网的系统 (AquaBot) 来自动评估水质和推鱼类.
- 设计一个移动机器人来收集水的参数,如pH值,温度和度.
- 评估各种机器学习算法,以准确推鱼类物种.
主要方法:
- 开发了一个带有移动机器人的物联网系统,以收集实时水质数据.
- 为了数据监控和可视化,创建了Web和移动界面.
- 多个机器学习算法,包括一个集合模型,在预处理的数据集上进行训练和测试.
- 性能评估使用了准确度,精度,回忆,F1分数,MCC和AUC等指标.
主要成果:
- 拟议的定制组合模型实现了94%的准确性,精度和回忆,F1得分为94%.
- 整体模型还表现出强的性能,MCC为93%,多类分类的最佳AUC分数.
- 性能最好的ML模型被部署在Web界面上,用于实际应用.
结论:
- AquaBot有效地监测水质,并推合适的鱼类,增强水产养殖业务.
- 该系统预计将增加产量,降低成本,减少渔业养殖中人工劳动.
- 这种物联网,机器人和机器学习的综合方法为现代水产养殖提供了重大进步.
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