Abstract

One of the air emission mitigation efforts is the development of electrostatic precipitator (ESP)-based filtration. On the other hand, this method requires further identification of the effect of flow rate on the resulting efficiency level. Therefore, this study aims to identify the best flow rate in a low-power, small-scale miniature ESP system based on ESP, with the application of IoT technology in real-time and accurate data monitoring. The study was conducted in a closed chamber using an IoT-based flow rate measurement system (anemometer). The flow rate was varied into two categories, namely inlet and outlet. Measurements were made for 100 s consecutively on both air flow paths. Work efficiency was calculated based on the difference between the inlet and outlet flow rates, which was then compared with the inlet flow rate. Data communication efficiency was analyzed using RSSI parameters based on the IoT system using a 4G internet network. The measurement results showed similarity in data between the inlet and outlet flow rates, with an efficiency level of 87%. RSSI in data communication is above -60 dBm with a strong transmission signal category. These results conclude that flow rate can affect air flow efficiency performance. The quality of an IoT network can be analyzed using the RSSI parameter.

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