Design and development of a Low-cost Sensor Network for indoor air quality and thermal insulation assessment
Résumé
This study presents the development of a cost-effective sensor network (LCSN) for indoor environmental monitoring, with a focus on air quality and thermal insulation assessment. The system utilizes a Raspberry Pi equipped with sensors to measure volatile organic compounds (VOCs), particulate matter, temperature, humidity, and heat flux. The prototype integrates hardware components, including VOC and particulate matter sensors, along with heat flux sensors connected to an analog-to-digital converter. The software implementation employes C++ programming, cloud-based data storage using InfluxDB on Amazon Web Services, and real-time data visualization through Grafana. The primary objective is to evaluate the performance of biobased insulation materials and their impact on indoor air quality under real-world conditions. Key features of the system include low-cost components, open-source design, real-time data acquisition, and cloud-based storage, enabling long-term environmental monitoring in buildings. The study identifies challenges related to the accuracy of heat flux measurements in biobased materials but also outlines potential improvements and highlights the system's suitability for detailed evaluation of indoor environmental conditions.
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