International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Powered Mental Health Companion and Multimodal Personal Assistant with IoT-Driven Health Monitoring |
|---|---|
| ABSTRACT | Mental health challenges are becoming more common, but many people hesitate to seek help because of stigma, barriers to access, or a lack of awareness about early signs. This research introduces an AI-powered personal assistant aimed at supporting mental well-being and daily productivity. The system combines natural language processing (NLP), sentiment analysis, real-time facial emotion detection, and IoT-based physiological monitoring with ESP8266, a pulse sensor, and a DS18B20 digital thermometer. The assistant offers conversational support, emotional feedback, personalized suggestions, health alerts, and automated reminders through Twilio SMS scheduling. The project shows how AI, computer vision, and embedded sensing can come together in one intelligent assistant to improve wellness monitoring, self-awareness, and user engagement. |
| AUTHOR | HARISH KUMAR H C, SADATH KHAN, D SANGEETHA, SHASHANK H M, SHEIKH MUSKAN FATHIMA |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311101 |
| pdf/101_AI-Powered Mental Health Companion and Multimodal Personal Assistant with IoT-Driven Health Monitoring.pdf | |
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