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@article{169635,
        author = {Mrs.Selvi A and Prasanth K R and Churchill L and Pragadheesh M},
        title = {AI-Driven Mobile Application for Water Footprint Calculation: Integrating Image Recognition and Regional Agricultural Data for Sustainable Consumption},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {1325-1331},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169635},
        abstract = {As water scarcity continues to intensify globally, understanding and managing water consumption at both individual and community levels has become a critical challenge. This paper presents an innovative solution through a mobile application designed to quantify and track the water footprint of agricultural products and consumer goods. By providing real-time, region-specific data on water usage, the app empowers users to make informed decisions based on the water footprint of their daily purchases and activities. The solution leverages advanced data analytics to offer personalized water conservation tips, facilitating a more sustainable lifestyle. Additionally, the app incorporates geospatial analysis to tailor recommendations for farming practices in water-scarce regions, further extending its impact beyond consumer usage. This research explores the design and functionality of the app, focusing on how it can educate users on the hidden water costs of products and promote water-saving behaviours. By offering actionable insights and fostering awareness of virtual water, this solution seeks to contribute significantly to global water conservation efforts and environmental sustainability.},
        keywords = {Water footprint, sustainable development, mobile application, water conservation, consumer behaviour, geospatial analysis, environmental awareness},
        month = {November},
        }