Adaptive Transmission Strategies for Energy-Efficient Long-Term Outdoor IoT Monitoring

Authors

  • Jaratpong Tepmanee Department of Electrical Engineering, Faculty of Engineering, Chiangrai College
  • Dumrongsak Wongta Department of Electrical Engineering, Faculty of Engineering, Chiangrai College
  • Satawat Muangchuen Department of Electrical Engineering, Faculty of Engineering, Chiangrai College
  • Kittikom Nontprasat Department of Industrial Management, Graduate School, Chiangrai College

DOI:

https://doi.org/10.14456/jeit.2026.15

Keywords:

Internet of Things, Adaptive Sampling, Data Reduction, PM2.5 Monitoring, Energy-Efficient Transmission, Environmental Sensing, ESP32, Edge Computing

Abstract

Continuous high-resolution data transmission in Internet of Things (IoT)-based environmental monitoring systems leads to significant communication overhead and energy consumption, particularly in long-term outdoor deployments. This study aims to evaluate and compare energy-efficient data transmission strategies for long-term outdoor IoT environmental monitoring systems under real-world conditions. A system-level evaluation was conducted using a real-world environmental sensing platform deployed in Chiang Rai, Thailand. The system, built on an ESP32 microcontroller with SHT20 and PMS3003 sensors, collected temperature, humidity, and PM2.5 data at 30-second intervals from March 2024 to May 2025, resulting in 1,048,406 transmission events under the baseline configuration. Two transmission reduction strategies were evaluated: fixed downsampling and adaptive sampling based on signal variability. Performance was assessed using Data Reduction Ratio (DRR) and Event Preservation Ratio (EPR), including both PM-only and multi-parameter event detection. The fixed downsampling approach achieved the highest data reduction (90.00%) but preserved only 15.91% of multi-parameter environmental events. In contrast, adaptive sampling reduced transmission by 78.89% while preserving 56.76% of combined environmental events. The results demonstrate that maximizing transmission reduction alone is not suitable for dynamic environmental monitoring. Variability-aware adaptive transmission provides a more balanced trade-off between energy efficiency and event preservation. This study proposes a practical evaluation framework for designing energy-constrained IoT monitoring systems under real long-term outdoor conditions.

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Published

2026-06-29

How to Cite

[1]
J. Tepmanee, D. . Wongta, S. . Muangchuen, and K. . Nontprasat, “Adaptive Transmission Strategies for Energy-Efficient Long-Term Outdoor IoT Monitoring”, JEIT, vol. 4, no. 3, pp. 1–21, Jun. 2026.

Issue

Vol. 4 No. 3 (2026): Journal of Engineering and Industrial Technology, Kalasin University, Vol. 4 No. 3 (May – June 2026)

Section

Research Article

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Copyright (c) 2026 Journal of Engineering and Industrial Technology, Kalasin University

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