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@article{194449,
        author = {Sanket Santosh Kanase and Tejaswini Gaurihar Mule and Vaishnavi Ravaso Mali and Pradnya Uddhav Nikam},
        title = {AIML-POWERED INTELLIGENT VEHICLE RENTAL SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {4133-4136},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194449},
        abstract = {Traditional vehicle rental systems rely on manual processes, static pricing mechanisms, and limited personalization features, leading to inefficiencies, revenue loss, and reduced customer satisfaction. This paper presents the design and implementation of an AI/ML-powered intelligent vehicle rental system that integrates machine learning algorithms with a scalable web-based architecture to automate booking operations, optimize pricing strategies, enhance fraud detection, and improve fleet management. The system incorporates demand forecasting, dynamic pricing using regression models, collaborative filtering-based vehicle recommendations, predictive maintenance modules, and anomaly detection techniques. The proposed solution enhances operational efficiency, ensures secure transactions, and provides a personalized user experience. Experimental evaluation demonstrates improved pricing accuracy, optimized fleet utilization, and enhanced fraud detection compared to traditional rental systems.},
        keywords = {Artificial Intelligence, Machine Learning, Vehicle Rental System, Dynamic Pricing, Recommendation Engine, Predictive Maintenance, Fraud Detection, Smart Mobility.},
        month = {March},
        }