A SURVEY ON HOPEBITE: AI-POWERED SMART FOOD DISTRIBUTION FOR COMMUNITIES IN NEED

Computer Science and Engineering

Food wastage and hunger remain two of the most pressing global challenges, with millions of tonnes of edible food discarded daily while vulnerable communities such as orphanages, old age homes, and underprivileged families continue to face acute shortages. Conventional donation mechanisms—relying on manual coordination, telephone calls, or basic NGO networks—suffer from critical shortcomings including absence of real-time tracking, delayed collection, lack of donor-beneficiary verification, inefficient volunteer management, and no predictive intelligence for food expiry. These limitations result in continued wastage, inequitable distribution, and low community participation. To address these gaps, the present survey introduces HopeBite — an AI-powered smart food distribution platform specifically engineered for urban and semi-urban communities in India. The system establishes a unified digital ecosystem that seamlessly connects four primary stakeholders: donors, volunteers, beneficiary organisations (old age homes and orphanages), and administrators through a dual web (Django) and mobile (Flutter) architecture. At its core, HopeBite integrates advanced artificial intelligence and machine learning techniques: Gemini AI for accurate food expiry prediction, natural language processing-based review mining for automatic identification of top-performing volunteers, and K-Means clustering for location-based detection of high-demand zones. The platform implements a strict role-based verification workflow ensuring authenticity of all participants, real-time status tracking of every donation request, automated feedback and rating mechanisms, and intelligent ranking of best donors and volunteers. Comprehensive literature analysis of fifteen contemporary food donation applications reveals that while several mobile and web solutions exist, none combine AI-driven expiry forecasting, ML-based performance analytics, and geospatial clustering within a single verified ecosystem. HopeBite overcomes these deficiencies by providing end-to-end transparency, optimised routing, and data-driven decision support for administrators. Implemented and tested in Phase-2 with full module integration and MySQL backend, the system demonstrates measurable reduction in food spoilage, faster response times, and enhanced stakeholder engagement. By transforming surplus food into a sustainable social resource, HopeBite exemplifies the practical application of AI and ML in addressing humanitarian challenges. The survey concludes that such intelligent, technology-driven redistribution platforms represent a scalable and replicable model for achieving zero hunger and environmental sustainability across developing nations.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.