Stress Detection using Convolutional Neural Network and Internet of Things

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Dhatri Raval, et. al.


Survival amid today’s highly competitive world has become an integral and inevitable part of life. People from all walks of life today find it extremely difficult to cope with their hectic schedule, work pressures, and compete with their peers that often results in stress. Prolonged exposure to stressful environments could severely disturb emotional and psychological wellbeing in humans thereby resulting in long term health implications. The advent of Artificial Intelligence (AI) and Internet of Things (IoT) in the modern era has proved to be extremely effective in prompt and precise detection and diagnosis of stress based on certain predefined/ specified algorithms which could immensely aid in timely diagnosis and treatment of stress related disorders. Studies reveal that by integrating IoT and AI backed by deep learning (DL) technologies it is possible to proactively detect stress much before its implications could manifests on human health. This study investigates the effectiveness and viability of AI backed DL techniques and IoT in prompt and precise detection of stress in humans.


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How to Cite
et. al., D. R. . (2021). Stress Detection using Convolutional Neural Network and Internet of Things. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(12), 975–978.