Smart Home Water System: AI‑Enhanced ESP8266 IoT Platform for Faucet Automation, Leak Detection, and Purification

Abstract

This research paper presents the development and implementation of an IoT-based water management system designed for domestic environments, incorporating smart faucets, an automated leak detection mechanism, and an AI-powered water purification unit. With the increasing urgency of global water scarcity, there is a growing need for intelligent, automated solutions to manage household water consumption efficiently. The proposed system utilizes the ESP8266 Wi-Fi module integrated with the ATMEGA 328 microcontroller to monitor water usage, detect leakages, and ensure the quality of water through real-time data analytics. The smart faucet employs infrared (IR) sensors for touchless control, helping to reduce unnecessary water flow. Leak detection is achieved via flow and moisture sensors installed along water pipelines. Upon detecting abnormalities, the system automatically triggers alerts and can shut off valves to prevent water loss. The AI-based purifier is equipped with sensors to monitor essential water quality parameters such as pH, Total Dissolved Solids (TDS), and turbidity. An embedded AI algorithm interprets these metrics and recommends corrective actions or maintenance alerts, ensuring safe water for consumption. Data from all modules is transmitted through the ESP8266 via MQTT protocol to a cloud server, allowing users to access water usage trends, receive real-time alerts, and interact with the system through a mobile or web-based dashboard. Experimental trials and performance evaluations indicated significant improvements in water conservation and quality monitoring, with detection times under 10 seconds and potential water savings of up to 25%. By addressing inefficiencies in traditional manual monitoring systems, this smart solution enhances user awareness, promotes sustainable usage, and aligns with modern smart home architectures. While connectivity and sensor maintenance remain potential challenges, the system’s modularity, affordability, and scalability make it suitable for widespread residential adoption. Future enhancements may include voice assistant integration, solar-powered components, and advanced predictive analytics for even more proactive water management.