Voice-controlled smart home system with real-time scheduling and localized device control

Abstract

Voice-controlled smart home system with real-time scheduling and localized device control, including: a speech processing unit configured to receive and interpret user voice commands locally via an AI assistant; a web-based user interface configured to allow users to add, remove, and manually control devices and define scheduling rules; a backend processing module comprising a server implementing a RESTful API and configured to validate user commands, interact with a centralized database, and communicate with device control units; a cloud-hosted NoSQL database configured to store device metadata, schedules, voice commands, and system logs; a scheduling module integrated into the backend, configured to perform one-time and recurring device actions at predefined times; a variety of microcontrollers, including ESP8266 and ESP32 units, configured to communicate using the ESP-NOW wireless protocol; where the ESP8266 receives control commands from the backend and forwards them to the ESP32, which switches the physical state of the connected devices; and The system operates without requiring a continuous internet connection and validates each command before execution based on the real-time device status.

Description

[0001] The present invention relates to the field of intelligent home automation systems. More specifically, the invention relates to a voice-activated and web-controlled smart home system that operates independently of a continuous internet connection, integrates real-time device scheduling, and utilizes local communication protocols for device control and management.

[0002] The development of smart home technologies has spawned various systems that allow users to remotely control household appliances via mobile applications, cloud-based platforms, and voice-controlled assistants. Well-known commercial solutions such as Amazon Alexa, Google Home, and Apple HomeKit enable voice-controlled automation and smart scheduling for electrical appliances and systems. These platforms typically rely on a continuous internet connection and cloud-based services to process commands, store user settings, and communicate with connected devices. However, current systems have significant limitations.A major problem is their dependence on external internet services, which not only increases latency and service outages in areas with poor or unreliable connectivity, but also poses data protection concerns due to continuous data transfer to cloud servers. Furthermore, many existing solutions lack flexibility in device management, so adding or removing devices often requires hard-coded configurations or technical intervention. Furthermore, common platforms rarely have intelligent command validation, leading to redundant or unnecessary device switching, which can impact both the user experience and the longevity of the hardware. Another critical deficiency is the limited or complex scheduling capabilities in existing systems.Users often struggle to configure recurring automation or one-time tasks in a user-friendly manner. Furthermore, most systems lack decentralized control or offline functionality, making them unsuitable for deployment in rural or internet-limited environments. Therefore, there is a need for a decentralized, user-configurable, voice-activated smart home system that operates effectively without cloud-based infrastructure, provides dynamic device control and intelligent scheduling, and ensures efficient local communication between components. The present invention addresses these limitations through an integrated system design that combines local AI-driven speech recognition, a dynamic web interface, real-time scheduling, and low-latency peer-to-peer communication between microcontrollers using the ESP-NOW protocol.

[0003] To solve this problem, the present invention provides a system for AI-assisted code review and explanation using integrated static analysis and language models.

[0004] The system integrates multiple technologies to improve usability, offline reliability, scalability, and intelligent automation.

[0005] The system allows users to operate connected devices via natural language voice commands and a web-based user interface.

[0006] The system uses the ESP-NOW protocol for low-latency peer-to-peer communication between microcontroller-based nodes.

[0007] The system includes a scheduling module that supports both one-time and recurring automation rules.

[0008] The system connects to a cloud-hosted NoSQL database such as MongoDB Atlas to enable real-time logging of events, including user commands, device status changes, and scheduled tasks.

[0009] In one embodiment, the present invention provides a voice-activated smart home system with real-time scheduling and localized device control.

[0010] The present invention relates to a voice-activated smart home automation system that combines offline device control, dynamic web-based configuration, and real-time scheduling to provide a robust and user-centric solution for residential, commercial, and institutional environments. The system enables users to operate multiple electrical appliances via natural language commands processed locally by an AI assistant named Alex, or via an intuitive, browser-accessible web dashboard. Unlike conventional smart home platforms that rely on internet connectivity and cloud infrastructure, the disclosed system uses the ESP-NOW protocol for local, low-latency communication between ESP8266 and ESP32 microcontrollers.This allows the system to operate independently of a continuous internet connection, making it particularly reliable in areas with limited or unstable connectivity.

[0011] The system includes a real-time scheduler that supports both one-time and recurring automation triggers, which are executed directly by the ESP nodes to ensure high efficiency and minimal latency. The AI ​​assistant validates voice commands against real-time device statuses in the database, avoiding redundant actions and improving energy efficiency. Furthermore, all user interactions, device status changes, and scheduled events are logged with timestamps in the central database, promoting transparency and enabling advanced analytics. The modular architecture—consisting of the AI ​​processor, the Flask-based backend, the frontend dashboard, and the ESP-based control plane—facilitates scalability, maintainability, and customization, making it suitable for homes, offices, classrooms, hospitals, and industrial facilities. The invention is explained again below.

[0012] The present invention discloses a voice-activated smart home system that allows users to control household appliances via natural language voice commands or a responsive web-based dashboard. Designed for high reliability, especially in low-connectivity environments, the system operates without constant internet access by leveraging ESP-NOW, a low-latency wireless protocol for communication between ESP8266 and ESP32 microcontrollers. A locally operating AI assistant named Alex interprets voice commands and checks the status of devices via a Flask-based backend before executing actions, while the web interface allows users to manually control devices, manage schedules, and monitor status updates.The backend processes all inputs, validates commands, and updates device status in real time using MongoDB Atlas, which stores device metadata, user schedules, voice input, and action logs for traceability and synchronization.

[0013] The system supports up to eight devices and features a built-in scheduler for automating one-time or recurring tasks without voice input. Commands—whether issued by voice or over the internet—are only executed when a state change is required, reducing energy consumption and wear and tear on devices. The hardware layer ensures offline functionality by forwarding validated commands from the backend to the ESP8266, which communicates directly with the ESP32 to switch devices. The modular architecture allows for easy integration of future extensions such as mobile apps, user authentication, or advanced analytics, making the solution highly scalable and adaptable to the evolving needs of the smart home.

Claims

[1] Voice-controlled intelligent home system with real-time scheduling and localized device control, comprising: a speech processing unit configured to receive and interpret user voice commands locally via an AI assistant; a web-based user interface configured to allow users to add, remove, and manually control devices and define scheduling rules; a backend processing module comprising a server implementing a RESTful API and configured to validate user commands, interact with a centralized database, and communicate with device control units; a cloud-hosted NoSQL database configured to store device metadata, schedules, voice commands, and system logs; a scheduling module integrated into the backend, configured to perform one-time and recurring device actions at predefined times; a variety of microcontrollers, including ESP8266 and ESP32 units, configured to communicate using the ESP-NOW wireless protocol; where the ESP8266 receives control commands from the backend and forwards them to the ESP32, which switches the physical state of the connected devices; and The system operates without requiring a continuous internet connection and validates each command before execution based on the real-time device status. [2] The system of claim 1, wherein the speech processing unit is configured to check the current status of a device from the database before issuing a control command, thereby avoiding redundant operations. [3] The system of claim 1, wherein the web interface is configured to display a dynamic dashboard that displays device status, names, and switch numbers, and enables control over switching and scheduling options. [4] The system of claim 1, wherein the ESP-NOW communication protocol enables peer-to-peer wireless transmission between the ESP8266 and ESP32 modules without relying on Wi-Fi or the Internet. [5] The system of claim 1, wherein the backend module is implemented using a Python-based Flask framework and is configured to communicate with the AI ​​assistant, the web frontend, and the database simultaneously. [6] The system of claim 1, wherein the scheduler module supports real-time execution of both one-time and recurring actions without going through the voice assistant, thereby reducing latency.