Informasi Umum

Kode

24.05.176

Klasifikasi

006.32 - Neural networks, perceptrons, connectionism, neural computers

Jenis

Karya Ilmiah - Thesis (S2) - Reference

Subjek

Indoor Air Pollution

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Abstraksi

<p>Indoor air quality (IAQ) significantly impacts health and productivity, influenced by building materials, furniture, and outdoor air quality. Fine particles (PM_2.5) are a major pollutant posing respiratory and health risks. IAQ-related diseases contribute to premature deaths, emphasizing the public health concern. Research gaps persist in microsensor-based IAQ evaluation methods, their accuracy, measurement reliability, and performance assessment within sensor networks. This study aims to propose a Wireless Sensor Network (WSN)-based IAQ monitoring system. The system includes sensor calibration for accuracy, a 7-day measurement period, data validation, and daily averaging based on PM_2.5concentration standards. Quality of service assessment determines system specifications. Calibration tests show an R² value of 0.99 and a standard deviation of 11.65 µg/m&sup3; for PM_2.5sensors. PM_2.5concentrations range from 48 µg/m&sup3; to 75 µg/m&sup3; indoors and 41 µg/m&sup3; to 105 µg/m&sup3; semi-indoors, influenced by environmental factors and air infiltration effects. Post-measurement sensor validation reveals a minimal error of 0.005%. The system achieves consistent data transmission up to 24 meters, even in obstructed environments.</p>

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