Psychosocial Digital Twins: Soft Computing Models for Worker Emotion, Stress, and Human Behavior in Smart Factories

Abstract:

As industries move toward adaptive and human-centric automation, understanding the emotional and behavioral states of workers has become critical for both safety and performance. This keynote introduces Psychosocial Digital Twins (PDTs), virtual models that replicate not only physical processes but also human stress, mood, fatigue, and decision behavior. Using soft computing techniques such as fuzzy logic, neuro-fuzzy inference, and fuzzy cognitive maps, PDTs help interpret ambiguous psycho-physiological data and model worker states under uncertainty. The talk presents a practical and forward-looking roadmap for integrating psychosocial modeling into IoT-enabled smart factories, enabling organizations to create emotionally aware, ethically aligned, and resilient Industry 5.0 ecosystems.

Profile:

Shrutika Mokashi is a Business Intelligence Developer at ASSA ABLOY Americas and an emerging multidisciplinary researcher specializing in Human-in-the-Loop AI, Psychosocial Digital Twins, IoT-driven smart manufacturing, and soft computing, based behavioral modeling. Her work integrates data engineering, industrial analytics, and computational intelligence to design automation systems that are transparent, safe, and deeply aligned with human well-being.

She has served as a judge, mentor, and reviewer for several global innovation programs, including the Prime Health Innovation Challenge, QS Reimagine Education Awards, and multiple international AI and engineering hackathons. Her research explores emotion-aware digital twins, cognitive fatigue analytics, and adaptive human-machine collaboration models for Industry 5.0.

Shrutika is also the founder of FriendLine, an emotional-wellness platform that strengthens her perspective on empathetic and psychologically aware AI systems. Combining industrial experience with behavioral insight, she advocates for the next evolution of smart factories, systems that not only optimize processes but also understand and support the humans operating within them.