As the level of stress, anxiety and emotional imbalance increases, we need more intelligent systems to provide mental health assistance. Current methods of music therapy and EEG monitoring have problems such as depending upon manual supervision, not providing personalized treatment and lack of real-time adaptability. Because of these limitations, there is a lack of effectiveness with therapy and keeping track of your emotional state while not in the clinic is very difficult. Traditional systems also have limitations because they are bulky and don’t have good remote access. The purpose of this study is to create an IoT-based music therapy system that collects EEG signals, preprocesses and analyse to identify the brain state. This system allows real-time brainwave analysis, provide personalized treatment and allow remote monitoring. Experimental data display greater regulation of emotional states, decreasing brainwave activity related to stress and increasing the user comfort level and confirming the effectiveness of EEG based automated music therapy.