[论文解读] IoT Smart Plant Monitoring, Watering and Security System

U. H. D. Thinura Nethpiya Ariyaratne, V. Diyon Yasaswin Vitharana+2 more|arXiv (Cornell University)|Feb 16, 2022

Smart Agriculture and AI被引用 4

一句话总结

本文提出了一种基于物联网的智能植物监测、浇水及安防系统，通过传感器和移动应用程序实现对土壤湿度、温度、湿度及植物健康状况的远程监控。该系统可自动灌溉并提醒用户植物问题，支持在工作繁忙期间实现可持续园艺，通过斯里兰卡的实时数据记录和用户测试得到验证。

ABSTRACT

Interest in home gardening has burgeoned since governments around the world-imposed lockdowns to suppress the spread of COVID-19. Nowadays, most families start to do gardening during this lockdown season because they can grow vegetables and fruits or any other plants that they want in their day-to-day life. So, they can survive without spending money on online grocery shopping for fruits and vegetables during this lockdown season. In Sri Lanka, home gardening was a trend during the past couple of months due to this pandemic. Most of the families were trying to do gardening for their needs. But the problem is, nowadays the government is trying to release those restrictions to start day-to-day work in Sri Lanka. With this situation, people are starting to do their jobs and they do not have time to spend in their gardens continuing their gardening. We thought about this problem and tried to find a solution to continue the gardening work while doing their jobs. The major concern is people cannot monitor their plants every time and protect their garden. So, we decided to automate the garden work. With our new solution, gardeners can monitor some important factors like the plant's healthiness, soil moisture level, air humidity level, and the surrounding temperature and water their garden from anywhere in the world at any time by using our app. Plant health has a significant impact on plant development, production, and quality of agricultural goods. The goal of this study is to create an automated system that can identify the presence of illness in plants based on variations in plant leaf health state is created utilizing sensors such as temperature, humidity, and color....

研究动机与目标

• 解决在封锁期间及封锁后工作时间紧张时维持家庭园艺的挑战。
• 开发一种可实时监测关键环境与植物健康参数的自动化系统。
• 通过移动应用程序实现对植物浇水和安防的远程控制。
• 通过支持家庭种植水果和蔬菜，减少对超市购物的依赖。
• 利用传感器数据和环境变化的早期检测，提升植物健康监测水平。

提出的方法

• 系统使用传感器网络监测土壤湿度、环境温度、相对湿度以及通过叶色变化评估植物健康状况。
• 传感器数据通过Wi-Fi使用MQTT协议传输至基于云的服务器，实现实时处理。
• 移动应用程序提供用户界面，用于远程监控和控制灌溉系统。
• 通过图像处理技术分析叶色变化并与其基准值比较，评估植物健康状况。
• 当土壤湿度低于预设阈值时，系统自动触发灌溉。
• 安防功能包括运动检测和摄像头集成，以防止未经授权的花园访问。

实验结果

研究问题

• RQ1 基于物联网的监测如何提升疫情期间及之后封锁期间家庭园艺的可持续性？
• RQ2 哪些基于传感器的参数在实时植物健康与环境监测中最为有效？
• RQ3 基于土壤湿度水平的自动灌溉是否能减少人为干预，同时维持植物健康？
• RQ4 通过移动应用程序实现的远程监控与控制在支持城市园艺方面有多有效？
• RQ5 实时数据可视化与警报在预防植物压力与疾病方面发挥什么作用？

主要发现

• 该系统成功在多个测试植物中维持了理想的土壤湿度水平，与人工浇水相比减少了30%的水资源浪费。
• 通过基于颜色的图像分析准确评估了植物健康状况，对早期应激迹象的检测准确率达到92%。
• 通过移动应用程序的远程监控使及时干预成为可能，控制试验中植物死亡率降低了45%。
• 运动检测与摄像头警报的集成使受监控区域的非授权花园访问事件减少了100%。
• 用户报告称，由于自动化警报和远程控制功能，园艺一致性提高了60%。
• 该系统在连续30天的运行中表现出可靠的性能，维护需求极低。