ESP32-Based Smart Storage System with Fingerprint and HMI Integration for Workspaces

Management of laboratory equipment in higher education institutions often faces challenges such as lack of supervision, difficulties in inventory tracking, and an unstructured system. To address these issues, this research designs a Laboratory Component Storage Management System that integrates fingerprint technology, proximity sensors, HMI, and a database. The proximity sensor shows a success rate of 75% in detecting objects up to a distance of 10 cm. The stepper motor system on the X, Y, and Z axes has an average error of less than 1%, supporting movement precision. The VB.NET-based interface has proven successful through black box testing, with an Admin borrowing time of 47–50 seconds and a User borrowing time of 55–70 seconds, as well as a return time of 42–45 seconds and 52–62 seconds, respectively. This system enhances security, efficiency, and user experience in the practical process and can be an alternative solution to the weakness of the manual inventory system in the laboratory.

Authors

Institutions

Publication Details

Journal
Journal of Applied Electrical Engineering
Published
2025-06-28
DOI
https://doi.org/10.30871/jaee.v9i1.9420
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ESP32-Based Smart Storage System with Fingerprint and HMI Integration for Workspaces

Nanta Fakih Prebianto, Sheng Jin, Muhammad Ihsan
Journal of Applied Electrical Engineering
IoT-based Smart Home Systems
article

ESP32-Based Smart Storage System with Fingerprint and HMI Integration for Workspaces

Nanta Fakih Prebianto, Sheng Jin, Muhammad Ihsan
article en

Abstract

Management of laboratory equipment in higher education institutions often faces challenges such as lack of supervision, difficulties in inventory tracking, and an unstructured system. To address these issues, this research designs a Laboratory Component Storage Management System that integrates fingerprint technology, proximity sensors, HMI, and a database. The proximity sensor shows a success rate of 75% in detecting objects up to a distance of 10 cm. The stepper motor system on the X, Y, and Z axes has an average error of less than 1%, supporting movement precision. The VB.NET-based interface has proven successful through black box testing, with an Admin borrowing time of 47–50 seconds and a User borrowing time of 55–70 seconds, as well as a return time of 42–45 seconds and 52–62 seconds, respectively. This system enhances security, efficiency, and user experience in the practical process and can be an alternative solution to the weakness of the manual inventory system in the laboratory.

Journal of Applied Electrical EngineeringVol. 9(1)
Universitas Batam (ID)
Openalex Percentile: Top 86%
IoT-based Smart Home Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ESP32-Based Smart Storage System with Fingerprint and HMI Integration for Workspaces — Nanta Fakih Prebianto, Sheng Jin, et al. · Journal of Applied Electrical Engineering (2025) | TGRS Research Map | TGRS