Next Article in Journal
Single Shot High-Accuracy Diameter at Breast Height Measurement with Smartphone Embedded Sensors
Previous Article in Journal
Enhanced Disease Segmentation in Pear Leaves via Edge-Aware Multi-Scale Attention Network
Previous Article in Special Issue
Vega: LLM-Driven Intelligent Chatbot Platform for Internet of Things Control and Development
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

AIoT-Based Eyelash Extension Durability Evaluation Using LabVIEW Data Analysis

1
Department of Electrical and Mechanical Technology, College of Technology, National Changhua University of Education, Bao-Shan Campus, No. 2, Shi-Da Rd., Changhua City 500208, Taiwan
2
Department of Electronic Engineering, National Yunlin University of Science and Technology, Douliu 64002, Taiwan
*
Authors to whom correspondence should be addressed.
Sensors 2025, 25(16), 5057; https://doi.org/10.3390/s25165057
Submission received: 19 July 2025 / Revised: 11 August 2025 / Accepted: 11 August 2025 / Published: 14 August 2025
(This article belongs to the Special Issue AI-Empowered Internet of Things)

Abstract

This study introduces a novel platform, the Artificial Intelligence of Things Experimental Device Platform (AIoTEDP), to evaluate the durability of eyelash extensions under various environmental factors, including temperature, wind speed, and compression frequency. The experiment employs a three-factor full factorial design, utilizing LabVIEW to collect and analyze independent variables. The retention rate of eyelash extensions is the dependent variable for evaluating the durability. The proposed AIoTEDP regulates thermostats, stepper motors, and heating fans to simulate real-world eyelash extension usage conditions. Quantitative analyses are performed through visual assessments and image recognition technologies. The experimental results indicate that high temperatures and strong winds significantly reduce the durability of eyelash extensions. However, moderate bending damage (3000 repetitions) still allows for sufficient retention. This study validates the practicality and accuracy of the proposed AIoTEDP, showcasing its potential for innovative cosmetic testing systems to assess eyelash extension durability.
Keywords: AIoT; eyelash extensions; LabVIEW; durability; cosmetic testing AIoT; eyelash extensions; LabVIEW; durability; cosmetic testing

Share and Cite

MDPI and ACS Style

Chiang, S.; Chang, S.-H.; Yao, K.-C.; Kuo, P.-Y.; Hsu, C.-T. AIoT-Based Eyelash Extension Durability Evaluation Using LabVIEW Data Analysis. Sensors 2025, 25, 5057. https://doi.org/10.3390/s25165057

AMA Style

Chiang S, Chang S-H, Yao K-C, Kuo P-Y, Hsu C-T. AIoT-Based Eyelash Extension Durability Evaluation Using LabVIEW Data Analysis. Sensors. 2025; 25(16):5057. https://doi.org/10.3390/s25165057

Chicago/Turabian Style

Chiang, Sumei, Shao-Hsun Chang, Kai-Chao Yao, Po-Yu Kuo, and Chien-Tai Hsu. 2025. "AIoT-Based Eyelash Extension Durability Evaluation Using LabVIEW Data Analysis" Sensors 25, no. 16: 5057. https://doi.org/10.3390/s25165057

APA Style

Chiang, S., Chang, S.-H., Yao, K.-C., Kuo, P.-Y., & Hsu, C.-T. (2025). AIoT-Based Eyelash Extension Durability Evaluation Using LabVIEW Data Analysis. Sensors, 25(16), 5057. https://doi.org/10.3390/s25165057

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop