Hasanuzzaman, G.; Buchwald, T.; Schunk, C.; Egbers, C.; Schröder, A.; Hampel, U. Dynamics of Aerosol Transport for Indoor Ventilation–Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi-Based Distributed Sensors. Sensors2024, 24, 4314.
Hasanuzzaman, G.; Buchwald, T.; Schunk, C.; Egbers, C.; Schröder, A.; Hampel, U. Dynamics of Aerosol Transport for Indoor Ventilation–Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi-Based Distributed Sensors. Sensors 2024, 24, 4314.
Hasanuzzaman, G.; Buchwald, T.; Schunk, C.; Egbers, C.; Schröder, A.; Hampel, U. Dynamics of Aerosol Transport for Indoor Ventilation–Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi-Based Distributed Sensors. Sensors2024, 24, 4314.
Hasanuzzaman, G.; Buchwald, T.; Schunk, C.; Egbers, C.; Schröder, A.; Hampel, U. Dynamics of Aerosol Transport for Indoor Ventilation–Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi-Based Distributed Sensors. Sensors 2024, 24, 4314.
Abstract
Enclosed public spaces are the hotspots for airborne disease transmission. To measure and maintain indoor air quality in terms of airborne transmission, an open source, low cost and distributed array of Particulate Matter Sensors has been developed and named as Dynamic Aerosol Transport for Indoor Ventilation or DATIV system. This system can use multiple Particulate Matter Sensors (PMS) simultaneously and can be remotely controlled using a Raspberry Pie based operating system. The data acquisition system can be easily operated using the GUI within any common browser installed on a remote device such as a PC or Smartphone with corresponding IP address. The software architecture and validation measurements are presented together with possible future developments.
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