ARCHITECTURE AND DEPLOYMENT OF A CLOUD-BASED MULTI-TIER IOT SYSTEM FOR REAL-TIME AIR QUALITY MANAGEMENT INTEGRATED WITH GENERATIVE AI

Authors

  • DANG XUAN HOAI
  • NGUYEN VAN THUAN

DOI:

https://doi.org/10.51453/3093-3706/2026/1476

Abstract

Air pollution within micro-environments poses severe, direct threats to human occupational health and well-being. Traditional monitoring stations are financially prohibitive and lack spatial granularity, while standalone hand-held devices fail to provide persistent time-series data storage and proactive, multi-channel alerting mechanisms. This paper presents the design, architectural topology, and empirical evaluation of AQMS PRO (Air Quality Monitoring System), a comprehensive multi-tier Internet of Things (IoT) ecosystem engineered for micro-climate air quality management. Built upon an ESP32 edge computing platform integrated with a multi-parametric sensor array, the system orchestrates real-time telemetry ingestion via custom PHP-native RESTful APIs into a normalized MySQL relational database. Furthermore, we implement an innovative contextual injection mechanism leveraging Large Language Models (LLMs) via the Gemini API, transforming complex environmental datasets (PM2.5, VOC Index, CO, LPG) into personalized, actionable medical infographics and cognitive health recommendations. Empirical field testing validates the ecosystem's structural stability, network latency efficiency, and high fidelity in dynamic multi-channel push notification alerts.

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References

[1] Government of Vietnam (2023), Decree No. 13/2023/ND-CP on Personal Data Protection.

[2] R. Buyya, C. Vecchiola, and S. T. Selvi (2013), Mastering Cloud Computing: Foundations and Applications Programming, Morgan Kaufmann.

[3] A. McEwen and H. Cassimally (2013), Designing the Internet of Things, Wiley.

[4] S. Russell and P. Norvig (2021), Artificial Intelligence: A Modern Approach (4th Edition), Pearson.

[5] C. Alippi (2006), "Intelligence in Cyber-Physical Embedded Systems," IEEE Transactions on Instrumentation and Measurement, Vol. 55, No. 4, pp. 1110-1119.

[6] Ministry of Information and Communications, Vietnam (2025), Annual Report on National Cybersecurity and IoT Standards Development.

[7] Nguyen, H. V., & Tran, D. T. (2024). "Development of low-cost multi-parametric sensor nodes using ESP32 for real-time micro-climate tracking." IEEE Sensors Journal, 24(8), pp. 11204-11215.

[8] Wang, J., & Liu, X. (2025). "Characterization and dynamic humidity compensation models for metal-oxide semiconductor gas sensors in industrial environments." Analytica Chimica Acta, 1241, 340-352.

[9] Al-Khafajiy, M., & Baker, T. (2023). "Performance optimization of relational databases for high-frequency time-series IoT data ingestion." Journal of Cloud Computing, 12(1), pp. 45-58.

[10] Fielding, R. T. (2024). "Architectural Styles and the Design of Network-based Software Architectures: Re-evaluated for Modern RESTful Cloud APIs." ACM Transactions on Internet Technology, 24(2), pp. 15-32.

[11] Brown, T. B., et al. (2024). "Contextual Injection and Dynamic Prompt Engineering in Cyber-Physical Systems: Converting Sensor Telemetry into Cognitive Action." Artificial Intelligence Review, 57(3), pp. 289-311.

[12] Martinez, C., & Zhang, Y. (2025). "Bridging the Semantic Gap in IoT Ecosystems through Large Language Models: A Health and Safety Perspective." International Journal of Medical Informatics, 182, 105-119.

[13] K. Saito and J. Miller, "Hybrid Containerization with Capacitor: Maintaining Kernel-level Background WebSockets for Real-time OS Push Notifications," IEEE Software, vol. 43, no. 2, pp. 64-72, 2026.

[14] Flanagan, D. (2025). JavaScript & Frameworks: Deep Dive into Component-Based Architectures with React and Vite. O'Reilly Media.

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Published

2026-07-06

How to Cite

DANG XUAN HOAI, & NGUYEN VAN THUAN. (2026). ARCHITECTURE AND DEPLOYMENT OF A CLOUD-BASED MULTI-TIER IOT SYSTEM FOR REAL-TIME AIR QUALITY MANAGEMENT INTEGRATED WITH GENERATIVE AI. SCIENTIFIC JOURNAL OF TAN TRAO UNIVERSITY, 12(2). https://doi.org/10.51453/3093-3706/2026/1476

Issue

Vol. 12 No. 2 (2026): T.12, S.2 (2026): Khoa học Tự nhiên  - Kĩ thuật - Công nghệ

Section

Natural Science and Technology

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