An energy-efficient hybrid model with adaptive sampling technique for air quality monitoring system in the cremation center

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Vinod Kumar Ahuja et. al.


In the recent past internet of things (IoT) has become promising technology due which it has grabbed the attention of the research community, industry, and end-user. Energy management is one of the massive constraints with an IoT sensor node because sensor nodes are often battery operated. In India, cremation centers are located within the city premises, due to the continuous emission of harmful gases such as carbon monoxide (CO), ammonia (NH3), it will deteriorate the people's health those who are closely located. In this paper, we have designed an energy-efficient Mobile Air Quality Monitoring System (MAQMS) and installed it in the cremation center in Hyderabad, India. MAQMS can measure harmful pollutants released into the environment during the cremation process. The proposed system measures the five different gases, such as carbon monoxide (CO), particulate matter 2.5, particulate matter 10, ammonia (NH3), and nitrogen dioxide (NO2). To reduce the power consumption of MAQMS, we proposed an algorithm that allows MAQMS to operate in a hybrid model that is a combination of two modes, namely hibernation and active mode. For every one minute, we allowed the system to switch between a hibernation mode and active mode with adaptive sampling to ensure data quality with efficient power consumption. The experimental results show that the power consumption by MAQMS per day before applying the hybrid model is 613.72A, whereas after applying the hybrid model, power consumption has a dropdown to 289.58A.

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