2025

The Study of Various Aspects of User Perception on the Mobile Application of AIoT-Based Air Quality Monitoring and Prediction for PM2.5

SAU JOURNAL OF SCIENCE & TECHNOLOGY

2025-12-13 | Journal article | Conceptualization, Formal analysis, Methodology, Writing - original draft

Contributors: Nuth Otanasap

Language: English

Homepage URL

https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/264058 

Contributors

Nuth Otanasap (Conceptualization, Formal analysis, Methodology, Writing - original draft, 0000-0002-8713-3951)

Southeast Asia University

https://orcid.org/0000-0002-8713-3951

Pornpimol Bungkomkhun

Tanainan Tanantpapat

Tida Jindamanee

Natthawat Saengsupphaseth

Citation (formatted-apa)

Otanasap, N., Bungkomkhun, P., Tanantpapat, T., Jindamanee, T., & Saengsupphaseth, N. (2025). The Study of Various Aspects of User Perception on the Mobile Application of AIoT-Based Air Quality Monitoring and Prediction for PM2.5. SAU JOURNAL OF SCIENCE & TECHNOLOGY, 11(2), 94–110. retrieved from https://ph01.tci-thaijo.org/index.php/saujournalst/article/view/264058  

Country/Location of publication

Thailand

Abstract

This research investigates the key factors that affect user satisfaction with the “AIoT-based Air Quality Monitoring System for Real-time PM2.5 Prediction in Urban Environments” mobile application. Conducted in the Nong Khaem District of Bangkok, the study employs a quantitative research methodology with a sample of 411 respondents who have used the application. The main objective was to identify the factors that influence user satisfaction.

The study's conceptual framework categorizes 17 independent variables into four primary criteria: Core Functionality & Data Reliability, Information & Presentation Quality, Actionable Insights & User Impact, and User Experience & Social Impact.

Data analysis, which employed descriptive statistics and multiple regression, revealed that respondents generally reported high satisfaction with the system, with a mean satisfaction score of 4.34 (SD = 0.74). The multiple regression model demonstrated a strong fit (R-squared = 0.7909), indicating that the four groups of variables explain a significant portion of the variance in user satisfaction.

In conclusion, the research emphasizes the importance of a well-designed mobile application that not only provides accurate and reliable data but also effectively communicates information through clear visuals, offers actionable advice for personal protection, and ensures a positive overall user experience. The findings present valuable insights for developers and policymakers aiming to enhance the effectiveness and user adoption of environmental monitoring technologies in urban areas.