Food Wastage Collection

Abstract

Food wastage presents critical social, environmental, and economic challenges globally. This paper presents the design and development of a digital food wastage collection system to streamline the donation and redistribution of surplus food. By connecting donors such as restaurants and households with receivers such as food banks and shelters, the system uses a centralized application to coordinate pickup, distribution, and communication. The solution includes scheduling, geolocation, and notification services, encouraging user participation and enhancing operational efficiency. This work demonstrates the practical potential of ICT-based solutions to reduce food waste and foster a more sustainable and equitable society.

Introduction

• Over 1.3 billion tons of food is wasted globally every year, worsening environmental issues and global hunger.

• There is a paradox: massive food waste coexists with widespread food insecurity.

• Traditional food donation systems are manual, inefficient, and lack transparency.

• Solution Proposed: A centralized digital platform to automate and streamline food donation and redistribution.

???? Literature Review Highlights

• Studies support systemic interventions and technology-enabled coordination.

• Successful platforms like Olio and SeVa show promise, but adoption and scalability are challenges.

• Key success factors include:

  • Usability

  • Security (e.g., GDPR, ISO/IEC 27001)

  • Agile development

• A gap remains in real-time logistics integration, which this project aims to address.

???? System Overview: Food Wastage Collection Application

Platform Components:

• Mobile App (iOS/Android): For donors and receivers

• Web Dashboard: For administrators

• Backend: RESTful APIs + MySQL database

Core Features:

1. User registration & login

2. Food listing & donation scheduling

3. GPS-based routing

4. Push/email notifications

5. Feedback and rating system

6. Admin-controlled approval workflow

Architecture:

• Connects Donors, Receivers, Admins, and Database

• Ensures secure, role-based, and real-time communication

???? Development & Technology Stack

• Agile methodology used (with iterative sprints and stakeholder input)

• Frontend: JavaScript via Visual Studio Code

• Tools: Microsoft Visio (ER diagrams), Microsoft Project (Gantt charts)

• Emphasis on usability, security, and modular design

???? Results from Pilot Testing

• Participants: 10 restaurants + 3 NGOs over 3 weeks

• Key Outcomes:

  • 35% reduction in coordination time

  • 20% decrease in pickup delays

  • 100+ meals successfully donated

  • High user satisfaction (app rated 4.5/5 for usability)

Performance Metrics:

• API response time: 1.2 seconds

• System uptime: 99.8%

• Load tested with 500 concurrent users (minimal latency increase)

???? Security & Compliance

• AES-256 encryption for data protection

• Role-Based Access Control (RBAC)

• Complies with:

  • GDPR

  • CCPA

  • ISO/IEC 27001

• Additional protections: firewalls, secure APIs, SQL injection prevention

• No breaches during pilot

???? User Feedback

• Donors: Liked donation history & pickup tracking

• NGOs: Valued map-based donation view

• Notifications: Increased action completion by 30%

• Suggested improvements: better onboarding experience (e.g., tutorials)

?? Limitations

1. Limited geographic coverage (pilot only in urban areas)

2. Network dependency affects real-time tracking

3. Manual food quality checks (no automation yet)

4. No integration with commercial inventory/POS systems

5. Legal variability in donation laws across regions

Conclusion

This paper presented the design, development, and preliminary evaluation of a centralized food wastage collection application aimed at streamlining the donation and redistribution of surplus food. By integrating mobile and web interfaces, geolocation services, real-time scheduling, and a secure backend infrastructure, the platform addresses key inefficiencies in traditional food donation systems. Pilot testing demonstrated measurable improvements in coordination time, pickup efficiency, and user satisfaction. To further enhance the platform’s effectiveness and scalability, future iterations will explore the integration of drone-assisted food pickups, enabling rapid and contactless delivery in hard-to-reach or underserved areas. Additionally, the incorporation of AI-driven demand prediction and smart routing algorithms is expected to optimize donation matching and resource allocation based on historical patterns and real-time data. These enhancements will support the system’s long-term goal of enabling intelligent, sustainable, and equitable food redistribution at scale.

References

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Copyright

Copyright © 2025 Ashrithaa Kulkarni. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.