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@article{169659,
        author = {Mrs. Bharani Nayagi S and Deepana D and Gayathri V and Kiruthika R},
        title = {ENHANCING RAIL MADAD WITH AI-POWERED COMPLAINT MANAGEMENT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {2015-2017},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169659},
        abstract = {The Rail Madad platform, aimed at streamlining passenger complaints, faces challenges in efficiently managing and resolving issues. To address this, our project proposes an innovative complaint management system integrating Natural Language Processing (NLP) and automated task allocation. Our system harnesses AI-powered technologies to automatically detect emergency cases, categorize and prioritize complaints, allocate department-specific tasks, and provide real-time progress updates to passengers. To (1) develop a robust NLP-based complaint categorization model, (2) design an automated task allocation framework, (3) improve complaint resolution speed and accuracy, and (4) enhance passenger satisfaction through transparent progress updates and timely resolutions.},
        keywords = {Automated complaint categorization, NLP-based emergency case detection, Predictive maintenance integration, Real-time passenger notifications, Task allocation frameworks.},
        month = {November},
        }