Page 165 - AI for Good Innovate for Impact
P. 165

AI for Good Innovate for Impact



                   Use Case 23: Empowering Student Mental Well-being with AI:

               Intelligent Journaling, Emotional Insights, and Personalized
               Growth                                                                                               4.1-Healthcare








               StudentSphere - Fostering peace, nurturing minds

               Country: India

               Organization: Vellore Institute of Technology, Chennai, India

               Contact Person(s):

                    Mohammed Sayeed A, mohammedsayeed.a1@ gmail .com
                    Bushra Sabreen, bushra.sabreen02@ gmail .com
                    Dr Suganya G, suganya.g@vit.ac.in


               1      Use case summary table


                Items                Details
                Category             Healthcare

                Problem Addressed    Students across India are experiencing a significant increase in mental
                                     health challenges, yet they lack access to personalized and affordable
                                     emotional support. This gap leaves many students struggling in isolation,
                                     potentially impacting their academic performance, social well-being,
                                     and long-term mental health [1].
                Key Aspects of Solu- AI-powered journaling, Sentiment Analysis, Mood Tracking, person-
                tion                 alised affirmations, and Goal Setting
                Technology Keywords Natural Language Processing, Sentiment Analysis, Emotion Detection,
                                     Data Encryption,

                Data Availability    Private
                Metadata (Type of  Text (journal entries), Emotional labels, Timestamps, Biometric metadata
                Data)
                Model  Training  and  Sentiment models leverage pre-trained transformers (RoBERTa [7] and
                Fine-Tuning          EmpathBERT [8]), with performance assessed through manual validation
                                     on carefully curated emotional text samples that simulate real-world
                                     diversity in gender, regional language, slang, and socio-economic
                                     context. This approach helps identify and mitigate potential bias in early
                                     development stages.

                Testbeds or Pilot  Under development as part of the StudentSphere platform—internal
                Deployments          VIT pilot planned
                Code Repositories    Not Available








                                                                                                    129
   160   161   162   163   164   165   166   167   168   169   170