The increasing global demand for sustainable agriculture necessitates intelligent monitoring systems that optimize resource utilization and plant health management. Traditional farming methods rely on manual observation and periodic watering, often leading to water wastage, inconsistent plant growth, and delayed response to environmental changes. This paper presents a comprehensive IoT-based smart plant monitoring system that integrates multiple environmental sensors with automated irrigation and cloud analytics. The proposed system utilizes an ESP32 microcontroller to collect real-time data from DHT22 (temperature/humidity), HC-SR04 (water level), and soil moisture sensors, with visual feedback through an OLED display and auditory alerts via a buzzer. All sensor data is wirelessly transmitted to the ThingSpeak cloud platform for remote monitoring, historical analysis, and automated alert generation. Experimental results demonstrate the system's effectiveness in maintaining optimal soil moisture levels (with 92\% accuracy), providing real-time environmental monitoring, and reducing water consumption by approximately 40\% compared to conventional irrigation methods. The integrated web dashboard offers comprehensive visualization of plant health parameters, making it suitable for both small-scale gardening and commercial agriculture applications. With a total implementation cost of \$45.20, this system provides an affordable, scalable solution for precision agriculture and smart farming.

翻译：全球对可持续农业日益增长的需求催生了能够优化资源利用和植物健康管理的智能监测系统。传统耕作方法依赖人工观察和定期灌溉，常导致水资源浪费、植物生长不均以及对环境变化的响应延迟。本文提出一种基于物联网的综合智能植物监测系统，该系统将多种环境传感器与自动化灌溉及云端分析功能相集成。所提出的系统采用ESP32微控制器，从DHT22（温湿度）、HC-SR04（水位）和土壤湿度传感器采集实时数据，并通过OLED显示屏提供视觉反馈、通过蜂鸣器发出听觉警报。所有传感器数据均无线传输至ThingSpeak云平台，以实现远程监控、历史数据分析和自动化警报生成。实验结果表明，该系统能有效维持最佳土壤湿度（准确率达92%），提供实时环境监测，与传统灌溉方法相比可减少约40%的用水量。集成的网络仪表板可全面可视化植物健康参数，使其既适用于小型园艺也适用于商业农业应用。该系统总实施成本为45.20美元，为精准农业和智慧农业提供了经济可扩展的解决方案。