DEVELOPMENT OF MECHATRONICS INVENTORY SYSTEM USING ARDUINO MCU, ESP32 AND GOOGLE SHEET APPLICATION WITH SMS MODULE

Abstract

This study presents the development of a Mechatronics Inventory System designed to offer an innovative solution for real-time inventory tracking in canned item production. The system categorizes canned items based on their weights (100g, 150g, and 210g) and displays real-time item status through an LCD interface. Pilot lamps indicate whether a bin is full or ready, while an ultrasonic sensor monitors bin levels. An SMS module alerts operators when bins reach capacity, and Google Sheets integration allows for centralized inventory management. Additionally, an RFID module resets the bin status, authorizing users to clear the "full" indicator and mark the bin as "ready" for the next cycle. Powered by Arduino MCU and ESP32 microcontrollers and supplemented by solar energy, this system addresses issues such as manual sorting errors, inventory mismanagement, and inefficient communication in the canned goods industry. The researchers applied the Experimental Prototyping Methodology to develop the system. Hardware designs were created using 2D and 3D modeling in SketchUp. Software implementation was carried out using Arduino IDE and C++ for microcontroller functionality, while Google Script was utilized for integrating inventory data with Google Sheets. The GSM module was programmed to send SMS notifications when bins reached full capacity. A Purposive Sampling Technique was used to collect feedback from 50 respondents, and responses were analyzed using a descriptive-type questionnaire based on a 4-point Likert scale. Functional testing demonstrated a high level of accuracy in sorting canned items by weight. The SMS module and Google Sheets integration worked seamlessly, providing real-time updates and reliable communication. The LCD display and pilot lamp indicators effectively conveyed bin status, offering immediate feedback when a bin was full. The entire system operated as intended, showcasing dependable performance in both item classification and inventory tracking. The prototype successfully achieved its objectives by automating canned item classification, enabling real-time monitoring, and improving inventory accuracy. The integration of Arduino MCU, ESP32, and Google Sheets, along with SMS notification and RFID-based control, contributed to enhanced efficiency and operational convenience. This system demonstrates strong potential as a scalable and sustainable inventory solution for the canned production industry, particularly through its use of renewable energy and streamlined automation features.