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ESP32 TinyML On-Device Water Quality Monitor

Water Quality & SensorsEst. CapEx: $35 USDLifespan: 7–15 Years


Technical Overview

A low-cost, real-time water quality monitoring system built around the ESP32 microcontroller that measures pH, TDS, temperature, and turbidity. It integrates an on-device neural network (TinyML via TensorFlow Lite for Microcontrollers) to classify water impurity events locally without requiring constant cloud connectivity, making it ideal for decentralized and remote deployments.


Key Specifications & Engineering Parameters

Parameter Specification
Category Water Quality & Sensors
Capital Cost (CapEx) $35 USD
Power / Energy Solar PV / Thermal
Target Scale Community Scale
Standard Lifespan 7–15 Years
Technology Maturity Field Tested
Primary Mechanism Analog and digital sensors feed parameter data into an ESP32 microcontroller, where a trained neural network processes the readings in real time to categorize water as ‘Normal’, ‘Rainwater Runoff’, or ‘Chemical’ with 99.28% accuracy. An intelligent fluctuation-based logging algorithm drastically reduces storage writes, and an automated pump control actuator enables autonomous response when anomalies are detected.

Cross-Reference & Interactive Tools

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