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@article{195798,
        author = {Dip Acharya and Yuvraj Shah and Dr. S. Saravanakumar},
        title = {Machine Learning-Based Smart Grocery Planner with Dynamic Budgeting and Waste Analytics Under Climate Variability},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {1431-1437},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195798},
        abstract = {Food waste is a big problem for homes, stores, and food service providers. It costs money and hurts the environment. Most grocery planning tools still use fixed expiration dates, which don't account for how food changes when it's stored and for changes in the weather.  This project creates a smart grocery planner that leverages food science, machine learning, and practical budgeting tips to help people waste less food. The system uses daily weather data from Delhi (2022–2023) along with important information about each grocery item, such as how long it usually lasts, the temperature at which it should be stored, and its sensitivity to temperature changes (measured by the Q10 coefficient). Instead of using fixed estimates, the shelf life is updated daily based on current temperature and humidity. A Combined Spoilage Factor (CSF) indicates the level of stress the food is under in its environment. Regression models estimate how long each item will last, while classification models flag items that are close to spoiling. 
A dynamic budgeting tool helps users decide what to buy and when, so they can avoid spending money on food that might go to waste. Tests show that ensemble machine learning models make more accurate predictions than traditional methods, especially during seasons with large changes in temperature and humidity. Temperature is the main factor, but humidity also has a clear impact during the monsoon.
Overall, this system is designed to be practical and user-friendly, providing a real way to reduce food waste as the weather becomes less predictable.},
        keywords = {Food waste analytics, shelf-life prediction, Q10 model, climate-aware systems, random forest, smart grocery planning, dynamic budgeting},
        month = {April},
        }