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@article{201270,
        author = {Subash Yadav and Sushant Yadav and Priya Sah and Sejal Patro and Dr. Jerald Nirmal Kumar S},
        title = {Leveraging Real-Time Weather Data and Rule-Based Modeling for Automated Outfit Recommendations: A Machine Learning-Oriented Framework},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {3077-3083},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201270},
        abstract = {In this project we are introducing a Weather Based Outfit Recommendation System. It recommends clothes as per the current day weather, information pulled from the OpenWeather API. It contains a rules-based engine to deal with temperature, rain and humidity. It spits out outfit advice based on the context it’s given I.e.: recommending to layer up when it’s chilly and keep clothing light on hot days. The user interface of the application, built with React.js, is fast and user-friendly. It is responsive, so weather conditions and the related clothing suggestions will appear on all devices. The scope of testing was quite extensive and it proved that the system’s accuracy and reliability were the same throughout all weather scenarios and thus it is practically useful for daily use. This solution not only saves decision-making time but also increases comfort by suggesting weather-appropriate clothes. The entire implementation with source code and documentation can be found on GitHub, which is open for community sharing and further development. This implementation is a perfect example of how automated systems can indeed enhance the quality of life of people by making their day-to-day tasks easier, at the same time laying down a ground for future improvements like the use of machine learning and personalized style recommendations.},
        keywords = {Outfit Recommendation, Weather API, React.js, Rule-Based System, Automated Fashion, Decision Support System},
        month = {May},
        }