DEVELOPMENT OF MULTI-FUNCTIONAL COMPUTER TABLE USING ESP-32 AND ARDUINO MCU WITH LINEAR ACTUATOR AND VOICE COMMAND

Abstract

The increasing demand for adaptable, efficient, and sustainable workspaces has generated interest in the development of smart furniture. Traditional computer tables often lack automation, integrated control systems, and energy-saving features, creating a gap between user needs and available designs. This study addresses that gap through the development of a Multi-Functional Computer Table using ESP-32 and Arduino microcontrollers. The prototype incorporates linear actuators and voice command systems to automate routine functions and enhance user convenience. Key features include a voice-controlled lifting mechanism, RFID and keypad-secured storage compartments, RGB lighting, and a solar-powered Automatic Transfer Switch (ATS) to maintain operation during power outages. The goal is to improve productivity, accessibility, and energy efficiency while ensuring safety and security. This study utilizes the Experimental Prototype Methodology, which involves system visualization through 2D/3D CAD modeling and schematic diagrams. Hardware and software integration was performed using the Arduino IDE and MIT App Inventor. Components underwent extensive testing to verify performance and reliability. A survey involving 50 respondents was conducted to evaluate the system's usefulness, sustainability, reliability, economy, and safety, using a 4-point Likert scale for analysis. Findings revealed a high level of user acceptance and satisfaction. Respondents agreed that the prototype was user-friendly, innovative, secure, and well-suited for modern work environments. The system met both local and international engineering standards while remaining cost-effective and portable. The integration of IoT, automation, and renewable energy into furniture design significantly enhanced the functionality and sustainability of the prototype. The results indicate that the developed Multi-Functional Computer Table offers a scalable solution for improving workspace efficiency in various settings such as homes, offices, and educational institutions. This research contributes to the advancement of smart furniture technologies by offering a practical and energy-efficient model for future applications.