ENHANCED ESP32 CLOUD CONNECTIVITY IN WATER MONITORING SYSTEM WITH AI

The increasing demand for efficient water management systems, driven by environmental concerns and population growth, necessitates advanced monitoring solutions. The Internet of Things (IoT) plays a pivotal role in enabling real-time water quality monitoring, particularly through the integration of microcontrollers such as the ESP32. This paper investigates the expansion of ESP32 connectivity with cloud platforms, facilitating seamless transmission of water quality data (e.g., pH, turbidity, and temperature) to enhance monitoring, analytics, and decision-making. The study explores several cloud services, including ThingSpeak, AWS IoT Core, and Google Cloud IoT Core, highlighting their advantages and integration methods with ESP32. Factors such as cost, scalability, security, and real-time data processing are discussed to guide platform selection for various water management applications. By leveraging cloud computing, the system can store and process large volumes of sensor data, ensuring resource efficiency, predictive maintenance, and improved decision-making. The paper also addresses challenges in secure data transmission, energy efficiency, and sensor compatibility, while demonstrating how IoT technologies can drive innovation in water quality management.