Abstract
The prevalence of autism spectrum disorder (ASD) has recently risen; people are frequently confronted with patients who have been diagnosed with autism spectrum disorder, which is a lifelong neurodevelopmental condition that affects many areas of behavior and cognition. It is frequently difficult for family members, providers, around an ASD patient to interact and communicate with them, necessitating professional assistance. A problem has arisen regarding the lack of automated systems designed especially for people with ASD as well as a lack of experience for neuro-typical people and engaging with these individuals. Existing solutions are restricted, rarely address ASD communities, and use cases. Therefore, we propose and validate an intelligent system called Tantrum-Track to assist in maintaining contact and improving communication with people with ASD and facilitating their integration into their environments and society. This approach can monitor desired outcomes and help in the decision-making process e.g. the system makes a decision about how to handle a certain scenario. For that purpose, we fully detail a comprehensive recommendation system to support people with ASD and support their communication with those in their environment (design phase). This recommendation system model makes two contributions: (1) modelling the autistic person’s context, and (2) representing this context as an ontological knowledge organization system. After assessing the (dis)similarities between two gathered settings, we incorporate these data into our recommendation system. This system suggests actions that are likely to help and calm the autistic person and control a situation before it escalates, and/or prevent a potential tantrum from occurring.
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Mcheick, H., Ezzeddine, F., Lakkis, F., Msheik, B., Ezzeddine, M. (2023). Tantrum-Track: Context and Ontological Representation Model for Recommendation and Tracking Services for People with Autism. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_46
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