Determination of Indoor Air Quality (IAQ) requires measurement and analysis of all the indoor air parameters. Often, the contribution of some parameters is substantial while that of others is meagre. This work aims to develop an IoT system for monitoring the concentrations of indoor air pollutants. Grey Relational Analysis (GRA) is then used to evaluate all the measured indoor air pollutants and select the ones which influence IAQ the most. The selected parameters are then used to build IAQ forecast model using Artificial Neural Networks (ANN). The accuracy of the ANN based forecast model is measured using mean absolute percentage error (MAPE) and coefficient of determination.