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@article{164434,
        author = {Dr. K. Phani Srinivas and M. Jyothi and S Reddy Hemanth and I Srikanth Reddy and A Gopi Krishna},
        title = {IoT-Based Depression and Mood Monitoring},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {748-753},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164434},
        abstract = {The IoT-based depression and mood monitoring system enhances mental health management by leveraging facial expression analysis and physiological data tracking. Utilizing a laptop camera and deep learning, it identifies users' emotions in real-time while monitoring heart rate, SpO2, and body temperature via an Arduino-equipped MAX30102 sensor. The system employs machine learning to predict mood and depression and integrates OpenAI's ChatGPT to generate personalized content like motivational quotes and jokes, delivered through the laptop speakers. This holistic approach provides continuous emotional support, promoting well-being for individuals with mood disorders.},
        keywords = {Arduino, IoT sensors, MAX30102sensor, OpenAI's},
        month = {},
        }