Design and development of intelligent indoor air quality monitoring and prediction system vayuveda

Abstract

In the view of critical consequences associated to degraded indoor air quality levels, the present work focuses on the Design and development of intelligent indoor air quality monitoring and prediction system Vayuveda . The proposed system can monitor the potential pollutant concentrations from the target indoor environment on real-time basis and provide relevant insights about changing conditions to the building occupants through an online portal. The field data is further processed and analysed with the help of fuzzy inference tree model to provide forecasts related to specific pollutant conditions. A preliminary analysis was first conducted to describe the background of the problem domain while highlighting the health consequences, stats and technological aspects associated to indoor air quality management. Literature based on indoor air quality monitoring and forecasting system development was studied with a goal to find answers to the inherent questions and to draw critical inferences from the problem domain. The design of an Internet of Things-based indoor air quality monitoring system was implemented using low-cost, factory-calibrated sensors while focusing on PM10, PM2.5, CO2, CO, NO2, VOC, Temp, and Hum parameters. Further, the feature analysis and extraction of statistical, descriptive, and correlation information was executed relevant to field data and benchmark dataset. A novel approach (Adaptive Dynamic Fuzzy Inference System Tree - ADFIST) for the prediction of potential IAQ parameters was proposed using different feature reordering techniques, optimization algorithms, and model tuning methods. The thesis work also involved the comparative analysis of model performance with validation dataset and development of an online portal for Vayuveda . Ultimately, an in-depth analysis on findings, outcomes, limitations and future scopes of the designed approach was performed that can guide future researchers to work on further improvements in this direction. newline