The Future of Smart Home Through Intranet Wan Connectivity

Abstract

The increasing demand for secure, cost-effective, and efficient smart home systems has led to the development of a novel solution that integrates intranet and WAN connectivity. Our project leverages the ESP32 micro- controller as the cornerstone of the hardware interface, combined with the Home Assistant platform to deliver a comprehensive smart home experience. This system ensures privacy, security, and user convenience by implementing advanced communication protocols and centralized control through various devices. Additionally, the project addresses potential security vulnerabilities by establishing a private local network (intranet) and incorporating voice control functionalities via Google Home. To further enhance accessibility, the system integrates the Tail scale App, enabling secure remote control globally through VPN technology. This app allows users to manage their smart home environment from anywhere, providing significant advantages in terms of security and ease of use. The implemented system successfully controls four lights, one fan, and monitors room temperature in real-time, supporting both manual and automated operations. The system demonstrated high reliability, with response times consistently under one second, and received positive feedback for its user-friendly interface and flexibility. Security measures such as strong encryption protocols and robust authentication mechanisms ensure data privacy and protection against cyber threats. The integration of VPN technology with the Tail scale App enhances security by encrypting remote connections, thus maintaining the integrity and confidentiality of user data. This project contributes to the field of smart home technology by showcasing the practical integration of intranet and WAN connectivity, emphasizing security and user convenience. It provides a model for future developments, highlighting the benefits of combining local and global control mechanisms. Despite the successful implementation, the system is currently limited to a small number of devices, indicating the need for future expansions to support a wider range of smart home applications. Future work should focus on enhancing the system's scalability, integrating more devices, and exploring advanced automation capabilities using AI algorithms