• Tanu
• Disha Deshwal
• Abhishek Tiwari

Stress and anxiety have become common challenges in today’s fast-paced world, often affecting both mental and physical well-being. Traditional ways of assessing stress—like clinical consultations and self-reported questionnaires—tend to be reactive and lack the ability to provide real-time support. To address this, we introduce CalmSense, an Internet of Things (IoT)-based system designed to continuously detect stress and automatically deliver personalized relief. The system uses a wearable device equipped with PPG, GSR, and temperature sensors to monitor key physiological signals. These signals are processed locally on an ESP32 edge device, where a Support Vector Machine (SVM) model analyzes heart rate variability and skin conductance to determine whether a person is calm or stressed. When stress is detected, CalmSense activates soothing interventions—such as guided breathing exercises, ambient lighting changes, and relaxing audio—through a connected mobile app. In a study with 25 participants, the system achieved 92.7% accuracy with an average response time under 5 seconds, and 80% of users reported feeling calmer after using it. Overall, CalmSense demonstrates how IoT and machine learning can work together to create a smart, real-time solution for supporting mental well-being in everyday life.

Keywords— Internet of Things (IoT), Stress Detection, Anxiety Relief, Physiological Signals, Edge Computing, Machine Learning, Real-Time Intervention

"CalmSense: An IOT-Based Stress & Anxiety Detection and Relief System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.c663-c672, November-2025, Available :http://www.jetir.org/papers/JETIR2511282.pdf

"CalmSense: An IOT-Based Stress & Anxiety Detection and Relief System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppc663-c672, November-2025, Available at : http://www.jetir.org/papers/JETIR2511282.pdf