International Journal of Technology and Applied Science

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AI Interview Coach System with IOT Stress and Posture Detection

Author(s) Dr. M. Thejovathi, A.Pushpa Hasini, M.Mithra, N.Sampurna, G.Kaveri
Country India
Abstract Traditional interview preparation methods, such as mock interviews and coaching sessions, primarily emphasize answer quality and presentation skills, often neglecting the candidate’s internal mental state during the interview process. This project proposes an intelligent interview coaching system that continuously monitors stress variations and behavioral responses while a candidate participates in a simulated interview environment. By detecting patterns of nervousness, hesitation, and confidence loss, the system provides deeper insights into the impact of stress on interview performance.The proposed system leverages artificial intelligence and real-time analysis techniques to evaluate emotional and behavioral cues, enabling the identification of critical moments that affect candidate performance. Based on this analysis, the system delivers personalized and real-time feedback aimed at improving emotional regulation, response effectiveness, and overall interview readiness.This approach addresses a significant gap in placement preparation by integrating technical training with mental resilience development. It enhances self-awareness among candidates, helping them understand and manage stress patterns, thereby improving confidence and performance in real-world interview scenarios.
Keywords Intelligent Interview Coaching System, Stress Detection, Behavioral Analysis, Artificial Intelligence, Real-time Feedback, Emotional Intelligence, Interview Preparation, Mental State Monitoring, Performance Analysis, Self-awareness (Placeholder1) [1] [6] [8]
Field Engineering
Published In Volume 17, Issue 4, April 2026
Published On 2026-04-12
Cite This AI Interview Coach System with IOT Stress and Posture Detection - Dr. M. Thejovathi, A.Pushpa Hasini, M.Mithra, N.Sampurna, G.Kaveri - IJTAS Volume 17, Issue 4, April 2026. DOI 10.71097/IJTAS.v17.i4.1255
DOI https://doi.org/10.71097/IJTAS.v17.i4.1255
Short DOI https://doi.org/hbxc4s
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