IoT devices generate data at a remarkable speed which requires near real-time processing. Such need has inspired a new computing paradigm that advocates moving computation to the edge, closer to where data is generated for ensuring low-latency and responsive data analytics. This paper aims at monitoring indoor environment parameters inside the classroom in real time and estimate the occupancy of that room based on the collected data This is done by measuring different environmental parameters like temperature, CO2 etc. and then by performing regression on the collected data. For the purpose of real time monitoring an android application is used which uses MQTT for communication with the edge node. The estimation is then verified against the actual attendance in the classroom at that duration and it gives accuracy between 90\%-95\%. © 2018 IEEE.