Authors : Arijit Sardar

Volume/Issue : Volume 11 - 2026, Issue 7 - July

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Google Scholar : https://tinyurl.com/4csvth7s

Scribd : https://tinyurl.com/3r32stpk

DOI : https://doi.org/10.38124/ijisrt/26jul861

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Abstract : Food waste is a critical global issue, contributing to approximately 8% of total greenhouse gas emissions. This paper presents a comprehensive one-year longitudinal study (January–December 2025) of an AI-powered food waste reduction platform deployed across 15 hostels, 30 restaurants, and 5 banquet halls in West Bengal, India. The platform integrates three core AI components which include an LSTM-based demand forecasting model with an attention mechanism, a CNN-based food image classification system using EfficientNet-B3, and a Reinforcement Learning (RL) module for dynamic pricing and surplus redistribution. Over 12 months, the system processed 18,750 metric tons of food across 187,500 transactions.

Keywords : Food Waste Reduction, Deep Learning, LSTM, Computer Vision, Reinforcement Learning, Sustainability, IoT.

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