Abstract: This project proposes an AI-powered web application intended for effective event inspection and automatic report generation. Developed with Streamlit, the system allows the uploading of event-related images from which essential metadata like date and geolocation are parsed using EXIF data. The application uses natural language processing (NLP) methods, in this case, sentiment analysis through TextBlob, to assess the emotional tone of event descriptions. Via a secure admin login, event information—name, organizer, description, and location—can be entered and tracked. In-review events are inspected and digitally signed by authorized individuals via an upload or real-time drawing canvas. Upon approval, the system creates a professional PDF report with inlined images, metadata, sentiment summary, and signatures via ReportLab, and securely stores it on Cloudinary. This automation is not only onerous to documentation but also accurate, standardized, and easily accessible. The combination of AI and cloud services converts conventional event reporting into an intelligent, quick, and dependable process that is appropriate for institutional and organizational settings.
Keywords- AI-driven application, event inspection, automated report generation, Streamlit, image metadata extraction, EXIF data, sentiment analysis, natural language processing (NLP), TextBlob, geolocation, digital signature, PDF report generation, ReportLab, Cloudinary, web-based system, administrative approval, event management automation, user authentication, institutional documentation.
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DOI:
10.17148/IJARCCE.2025.144103
