Smart home monitoring in Node-RED emulator using Flutter mobile app and AI technology - Yap, Jun Hong (2025)
The limitations of static automation in current IoT-based smart home systems highlight a lack of flexibility and personalization. To address this gap, this project develops an adaptive smart home control and monitoring system that integrates Internet of Things (IoT) and Artificial Intelligence (AI) technologies for dynamic automation. The system is emulated using Node-RED with an SVG-based interface for device visualization, while a Flutter mobile app serves as the user interaction platform. MQTT provides realtime communication, and InfluxDB supports time-series data management. An AI module leverages both historical and real-time data to enable predictive decisionmaking, enhancing functions such as temperature regulation, lighting management, and air purification. The prototype demonstrates that adaptive automation improves comfort, responsiveness, and energy efficiency compared to traditional static methods. Project deliverables include the partial development of the Flutter mobile UI, Node- RED flows, and the SVG emulator, with future work focusing on full integration of InfluxDB for advanced analytics and AI-driven predictive control through machine learning.