The problem MyJournalAI solves

In response to a recent tragedy involving the suicide of a student due to mental harassment, we aim to address this pressing issue by leveraging technology. MyJournalAI is an innovative web-based application that combines the power of AI and personal journaling to mitigate mental stress and provide valuable feedback for individuals. By securely inputting and storing their journal entries on our platform, users can gain insights and actionable feedback based on AI analysis. Our machine learning models analyze the journal data to identify emotional patterns, enabling users to deepen their self-reflection and emotional awareness. Through personalized feedback and resources, MyJournalAI empowers users to manage their mental health effectively. By encouraging regular journaling and providing a secure environment for data storage, the app offers individuals a means to reduce mental stress and enhance their overall well-being. Our commitment is to raise awareness, support personal growth, and foster a community that prioritizes mental health.

Challenges we ran into

• The unavailability of Docker Hub (due to IP rate limiting issue) during the hackathon severely impacted the product's quality as it hindered the team from accessing necessary images, resulting in manual file downloads and increased complexity.
• Navigating diverse domains and acquiring in-depth knowledge posed a significant challenge, demanding substantial time and effort to ensure a comprehensive understanding of the project's intricacies.
• Insufficient emphasis on frontend development, due to a primary focus on the AI components, resulted in an incomplete implementation and compromised user experience.
• Lack of UI expertise in the team resulted in an overburdened individual handling the UI development, leading to potential workload imbalances.
• Addressing privacy concerns and implementing robust data security measures for sensitive personal journal information.
• Ensuring authentic and personalized entries from the AI model while avoiding generic or fabricated content.
• Striking a balance between meaningful journal entries and user privacy posed significant challenges.