Towards IoT-based Smart Mobility Framework for Proactive Road Stress Detection in Individuals with ASD
Résumé
Autism Spectrum Disorder (ASD) is a neurodevelopmental disability that significantly increases the difficulties and risks associated with driving. Individuals with ASD often face a variety of challenges, such as increased sensory sensitivities, difficulty adapting to changing environments, and struggles with unexpected situations on the road. These difficulties can lead to sensory overload, panic attacks, and impaired decision-making, all of which increase the risk of accidents and make driving an especially overwhelming task. In this paper, we propose a novel IoT-based smart mobility framework for predictive stress detection in drivers with ASD, enabling the early identification of potential stressors before they encounter them on the road. This approach leverages AI-based models, including LSTM and CNN-based architectures. Unlike existing methods that focus on reactive stress detection, which may be too late, our approach predicts stress triggers in advance, enabling timely and preventive support.
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