TY - GEN
T1 - RECO
T2 - 10th North American Conference on Industrial Engineering and Operations Management – Computer Science Tracks, IEOM-CS 2025
AU - Sánchez-Gómez, Juan Sebastián
AU - Trujillo-Díaz, Johanna
AU - Mina, Carla Fernanda González
AU - Martinez, Cristian David Ayala
AU - Ruiz, Francy Valentina Gamba
AU - Becerra-Fernández, Mauricio
AU - Díaz-Piraquive, Flor Nancy
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Food waste management has become a critical global issue with significant economic, social, and environmental impacts. In Colombia, approximately 9.7 million tons of food are wasted annually, impacting food security and malnutrition. This research explores the role of artificial intelligence, particularly chatbots, in optimizing food distribution and minimizing waste. The proposed system, RECO Donation Manager, employs AI-powered chatbots integrated with PostgreSQL databases and geolocation services like Bing Maps to streamline food donations. The AI in the chatbots, powered by natural language processing (NLP) and machine learning (ML), improves user interaction, automates resource allocation, and ensures efficient food redistribution. The initial implementation highlights challenges in geolocation accuracy, data validation, and understanding NLP, emphasizing the need for further refinement. This study demonstrates the potential of AI-based solutions to mitigate food waste and foster sustainable resource management, offering a promising foundation for future advances in automated food donation systems.
AB - Food waste management has become a critical global issue with significant economic, social, and environmental impacts. In Colombia, approximately 9.7 million tons of food are wasted annually, impacting food security and malnutrition. This research explores the role of artificial intelligence, particularly chatbots, in optimizing food distribution and minimizing waste. The proposed system, RECO Donation Manager, employs AI-powered chatbots integrated with PostgreSQL databases and geolocation services like Bing Maps to streamline food donations. The AI in the chatbots, powered by natural language processing (NLP) and machine learning (ML), improves user interaction, automates resource allocation, and ensures efficient food redistribution. The initial implementation highlights challenges in geolocation accuracy, data validation, and understanding NLP, emphasizing the need for further refinement. This study demonstrates the potential of AI-based solutions to mitigate food waste and foster sustainable resource management, offering a promising foundation for future advances in automated food donation systems.
UR - https://www.scopus.com/pages/publications/105015726957
UR - https://www.scopus.com/inward/citedby.url?scp=105015726957&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-98235-4_14
DO - 10.1007/978-3-031-98235-4_14
M3 - Conference contribution
AN - SCOPUS:105015726957
SN - 9783031982347
T3 - Communications in Computer and Information Science
SP - 193
EP - 209
BT - Industrial Engineering and Operations Management - 10th North American Conference - Computer Science Tracks, IEOM-CS 2025, Proceedings
A2 - Florez, Hector
A2 - Rabelo, Luis
A2 - Diaz, Cesar
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 17 June 2025 through 19 June 2025
ER -
