In classroom, teachers have a role to impart education and encourage learning to their students. More teachers are using various activities to make students keep focus on class but in the real situation teachers are facing a difficulty to make all student keep attention, because each student's mental activity and personal problem are different . To improve classroom management, we proposed a method to make teachers are able to keep monitoring and analyzing student's brain stress level by using 2-channels near-infrared spectroscopy (NIRS) sensor. This paper focuses on a method for observing a brain behavior under stress based on classroom activity. The data recorded from the experiment is analyzed in order to integrate with an internet of things architecture and to adapt deep learning algorithm in future development.