Reliable water quality monitoring is essential for protecting ecosystems, ensuring public health, and supporting sustainable resource management. This study introduces a modular IoT-based framework designed for real-time monitoring of water parameters, specifically pH and temperature, using an ESP32-S microcontroller integrated with calibrated sensors. Data is transmitted via Wi-Fi to the Blynk cloud platform, enabling continuous access, visualization, and alerting through remote interfaces. The system was validated through field deployment in a natural freshwater setting, demonstrating high accuracy, environmental robustness, and consistent performance. Over a seven-day period, pH levels ranged from 6.0 to 8.7, while temperatures varied between 26.0°C and 30.3°C. A strong correlation between temperature fluctuations and pH variation was observed, underscoring the importance of continuous monitoring in detecting dynamic water quality changes. The framework supports the integration of additional sensors for broader parameter coverage and complies with regulatory benchmarks such as the National Water Quality Standards (NWQS). Its modular and scalable architecture ensures adaptability across different environmental conditions and application domains. This research contributes a replicable and cost-effective solution for smart water quality management, suitable for deployment in agricultural, aquacultural, rural, and urban infrastructure contexts. By enabling real-time, data-driven decision-making, the system directly supports Sustainable Development Goal 6 (SDG 6), promoting access to clean water and efficient environmental stewardship.