<![CDATA[Water quality is a vital factor in maintaining public health and environmental sustainability. Turbidity is a primary parameter used to evaluate physical water quality. However, optical turbidity sensor readings are sensitive to water temperature variations, which cause measurement drift and reduce accuracy. This study aims to design and implement an Internet of Things (IoT)-based water turbidity measurement system equipped with a multi-temperature calibration algorithm. The system utilizes an ESP32 microcontroller, a photo-interrupter turbidity sensor, a DS18B20 waterproof temperature sensor, an LCD 16x2 I2C display, and the Blynk platform. Linear regression models obtained across multiple temperature conditions were embedded into the ESP32 firmware to compensate for thermal influence dynamically. Experimental results demonstrate that all hardware modules and IoT communication work reliably. The multi-temperature calibration successfully stabilizes Nephelometric Turbidity Unit (NTU) readings across different water temperatures and reduces measurement errors. The proposed system provides accurate, continuous, and real-time remote water quality monitorin]]>
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