用低成本硬件实现六参数水质实时监测，支持边缘计算与云端联动。
HydroSense: A Dual-Microcontroller IoT Framework for Real-Time Multi-Parameter Water Quality Monitoring with Edge Processing and Cloud Analytics
- 双微控制器架构：Arduino测精度，ESP32处理数据并连云端。
- 90天实测显示pH误差±0.08，TDS准确率±1.9%，云传输可靠率达99.8%。
- 总成本仅约300美元，比商用系统低85%，适合资源受限地区使用。
全球水危机亟需廉价、精准、实时的水质监测方案。传统依赖人工采样或昂贵商用系统的做法，在资源匮乏地区难以普及。本文提出HydroSense，一种集成pH、溶解氧（DO）、温度、总溶解固体（TDS）、估算氮含量和水位共六项关键参数的物联网框架。系统采用创新的双微控制器架构：Arduino Uno负责高精度模拟测量，结合五点校准算法；ESP32则承担无线通信、边缘处理与云端集成。通过中值滤波、温度补偿及鲁棒错误处理等信号处理技术提升性能。90天实验验证表明：pH测量在0~14范围内误差±0.08单位，DO稳定性控制在±0.2 mg/L，TDS在0~1000 ppm内准确率±1.9%，云数据传输可靠性达99.8%。系统总成本为32,983塔卡（约合300美元），相较商用系统降低85%，并通过Firebase实现实时数据库接入。本研究证明，通过智能架构与经济元件组合，可实现专业级水质评估，为可及性环境监测树立新范式。
原文摘要 · Abstract (English)
The global water crisis necessitates affordable, accurate, and real-time water quality monitoring solutions. Traditional approaches relying on manual sampling or expensive commercial systems fail to address accessibility challenges in resource-constrained environments. This paper presents HydroSense, an innovative Internet of Things framework that integrates six critical water quality parameters including pH, dissolved oxygen (DO), temperature, total dissolved solids (TDS), estimated nitrogen, and water level into a unified monitoring system. HydroSense employs a novel dual-microcontroller architecture, utilizing Arduino Uno for precision analog measurements with five-point calibration algorithms and ESP32 for wireless connectivity, edge processing, and cloud integration. The system implements advanced signal processing techniques including median filtering for TDS measurement, temperature compensation algorithms, and robust error handling. Experimental validation over 90 days demonstrates exceptional performance metrics: pH accuracy of plus or minus 0.08 units across the 0 to 14 range, DO measurement stability within plus or minus 0.2 mg/L, TDS accuracy of plus or minus 1.9 percent across 0 to 1000 ppm, and 99.8 percent cloud data transmission reliability. With a total implementation cost of 32,983 BDT (approximately 300 USD), HydroSense achieves an 85 percent cost reduction compared to commercial systems while providing enhanced connectivity through the Firebase real-time database. This research establishes a new paradigm for accessible environmental monitoring, demonstrating that professional-grade water quality assessment can be achieved through intelligent system architecture and cost-effective component selection.
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