Event management has become increasingly complex due to the growing scale of conferences, workshops, and large gatherings. Traditional event management systems often rely on manual attendance tracking, fragmented payment systems, and basic feedback collection methods that fail to generate actionable insights for organizers. This paper presents an AI-powered event management system designed to streamline event organization through the integration of real-time QR-based attendance tracking, intelligent feedback analytics, and secure payment processing. The system is developed using a modern client–server architecture where the frontend is implemented using React.js, while the backend utilizes FastAPI with RESTful APIs and JWT-based authentication. PostgreSQL is used as the database management system to ensure scalable and reliable data storage. The proposed system incorporates machine learning techniques such as sentiment analysis using TextBlob and statistical analytics using Pandas to evaluate participant feedback and generate automated event insights. Additionally, the platform integrates Razorpay for secure payment processing during event registration. A QR-based attendance system enables real-time participant entry verification and post-event feedback collection. The system also includes an event ranking and recommendation engine that evaluates event performance based on multiple feedback metrics. Experimental analysis demonstrates that the system improves event evaluation efficiency, enhances participant experience, and provides data-driven insights that assist organizers in improving future events.
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Aadhithya SV
Abhilash M
Ashwin B
Aims Community College
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SV et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69ddda0de195c95cdefd7803 — DOI: https://doi.org/10.5281/zenodo.19539445
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