AI & IOT enabled Eco Friendly Proactive GRS S...

AI & IOT enabled Eco Friendly Proactive GRS System for People Sustainable Health Management (Smart city)

Author Name : Polamarasetty Raju, Chakka Mohanarao, Dadi Ravivarma, Kalyan Chakravarthi.Malla

ABSTRACT

Deteriorating levels of in/outdoor air quality is a prominent environmental issue that results in long-lasting harmful effects on human health and wellbeing.In recent times indoor/outdoor Environment  quality has attracted the attention of policy makers and researchers as an important similar to that of external air pollution for smart cities wealth management. In a certain sense, indoor air quality must be paid more attention than outdoor air quality as people spend more time indoors than outdoors. The indoor environments are confined and closed compared to external environments providing less opportunity for the pollutants to dilute.  A concurrent multi-parameter monitoring approach accounting for most crucial indoor pollutants is critical and essential. The challenges faced by existing conventional equipment in measuring multiple real-time pollutant concentrations include high cost, limited deployability, and detectability of only select pollutants. The aim of this project is to present a comprehensive indoor Environment  quality monitoring system using a low-cost Raspberry Pi with Seed studio grove pi Hat-based GPS air quality sensor modules. The custom-built system measures 10 indoor environmental conditions including pollutants: AirQuality(AQI), Temperature, Relative Humidity, Pressure, Altitude, Radiation level, Light intensity, Carbon monoxide (CO), Oxygen(O2), Carbon dioxide (CO2), and Total Volatile Organic Compounds (TVOCs). Residential units and Educational offices,Traffic signal points were selected and monitored over a span of several months.  The recorded mean Air Quality  concentrations were significantly higher in the residential unit compared to the office building. The mean O2, CO2, and TVOC concentrations were comparatively similar for both locations. Spearman rank-order analysis displayed a strong correlation between particulate matter and Air Quality for both residential unit and the office building while the latter depicted strong Temperature and Humidity, Pressure, Altitude, correlation with sound noise levels, O2, CO2, AirQuality, Radiation level, Ambient light levels,IR levels, pm 2.5 air concentration when compared to the former for Smart city sustainable health management.