Angalakuditi, A.Bhowmik, B.R.2026-02-062022INDICON 2022 - 2022 IEEE 19th India Council International Conference, 2022, Vol., , p. -https://doi.org/10.1109/INDICON56171.2022.10040216https://idr.nitk.ac.in/handle/123456789/29794Depression is a significant problem in our society, as it is the cause of many health problems. The ongoing burden of intellectual function and continuous technological development, leading to constant change and the need for flexibility, makes the situation even more significant for people. It is necessary to see it early to prevent stress from becoming chronic and irreversible irritability. Unfortunately, a way to detect automatic, continuous, invisible pressure does not exist. This work involves monitoring a person's attention and emotional state across the ages. An IoT-enabled unobtrusive real-time monitoring system is developed to detect the person's emotional states by analyzing facial expression videos. The proposed method identifies individual emotions in each video frame, and a decision on the level of stress is made at the sequence level. © 2022 IEEE.Deep LearningFace RecognitionIoTStressStress Levels