Abstract

This study endeavors to design and implement an innovative asset detection device and inventory system utilizing Radio Frequency (RF) technology to bolster asset monitoring and inventory management in school laboratories. The primary objectives are twofold: developing an RF tracker device capable of detecting passive RF tags within a designated area and creating an asset inventory system software tailored for the Electronics Laboratory at the university. The study’s first phase focuses on the design and fabrication of the RF tracker device engineered to detect passive RF tags within a 6.5x6.5-meter space. Through meticulous design considerations, the device aims to provide precise asset-tracking capabilities within the laboratory environment. The second phase involves the development of asset inventory system software customized to meet the specific needs of the University’s Electronics Laboratory. This software will facilitate efficient asset management by accurately capturing and storing each asset’s X and Y coordinates within the room. Evaluation metrics encompass the accuracy of asset localization, the efficiency of inventory management processes, and the system’s overall operational efficiency and user-friendliness. The recorded results show that the scanned positions of assets closely match their real positions, with only minor deviations observed. ANOVA analysis confirms that there is no significant difference between real and scanned coordinates, validating the accuracy of the RF-based asset tracker. Efficiency comparison highlights that the designed tracker drastically reduces borrowing and returning time compared to the traditional manual method. Overall, the tracker improves asset management by ensuring precise location tracking and significantly enhancing operational efficiency.

Authors

Josh Marc R. Ricalde, Ruben Christopher L. Macabata, Mariciel M. Teogangco
University of Perpetual Help System Dalta, Molino Campus, Philippines

Keywords

Radio Frequency, long-range RF, Asset Tracker, Asset Monitoring, RFID, Raspberry Pi 3, Arduino Uno