Development of a Scalable End-to-End Multi-Device IoT System for Smart Home Automation, Security, and Remote Monitoring

This thesis presents the design, implementation, and evaluation of a scalable, end-to-end IoT ecosystem for smart home automation, security, and remote monitoring. The research addresses key challenges in existing commercial solutions, such as vendor lock-in, privacy issues, high costs, limited interoperability, and cloud dependency. The work develops and evaluates multiple independent yet interoperable IoT frameworks. Home Assistant and ESPHome are utilized as open-source platforms for local control and automation, while Tasmota provides firmware-level customization for MQTT-based devices. In parallel, ESP RainMaker, a proprietary cloud-based platform, is implemented separately to demonstrate industry-grade device management and secure remote access. The system integrates a wide range of ESP32-based sensors for motion detection, temperature and humidity monitoring, gas and smoke detection, vibration measurement, and magnetic reed switch security. Enhanced security is achieved through fingerprint recognition (R307 sensor), RFID modules (RC522), and ESP32-CAM-based surveillance. Custom-designed PCBs reduce costs and improve reliability, while the system seamlessly supports voice assistants (Amazon Alexa and Google Home) and a Flutter-based mobile application for real-time local and remote control. Remote access is secured through a Cloudflare tunnel with a custom domain, enabling continuous and privacy-preserving operation. Experimental evaluation confirms the system’s scalability, stability, and cost efficiency. Overall, the thesis contributes a modular, replicable framework for open-source and hybrid IoT systems that balance privacy, flexibility, and user control—bridging the gap between academic research and practical smart home deployment.