UPU

Detection of counterfeit philatelic products and stamp identification

Global Not Applicable

Relying on the data within the UPU’s digital database of certified stamps , the UPU has developed an AI-based tool presented on a mobile application , which will enable customs and law enforcement officers to check the legality of a seized stamp in just a few steps. This counterfeit detection functionality is reserved for customs, however the same tool also allows collectors to identify stamps and thus enhance their philatelic hobby.

Activity Type AI Tools/Solutions

UPU

Detection of dangerous (and prohibited) goods in the UPU postal network

Global

The UPU postal network is sometimes used for illegal traffic (such as: drugs, counterfeit items) and dangerous items (such as: inflammable/explosive products) that may get injected into the network. The Dangerous Goods Search tool (DGST) uses machine learning models trained on postal big data, to score the likelihood of the item to be dangerous (or prohibited). At the time of this report, the system is still under User Acceptance Tests (UAT) and we do not have as yet metrics to report. In the future, there are plans to interface the DGST with other intelligence databases, and offer a comprehensive tool to postal officers in charge of protecting the postal network.

Activity Type AI Tools/Solutions

UPU

State of the Postal Sector Report

Global Not Applicable

Artificial intelligence (AI) is at the forefront of revolutionizing the next wave of postal services. The "State of the Postal Sector" report, UPU’s flagship publication, delves into AI's transformative role in fostering enhanced collaboration among postal sector stakeholders worldwide. Spanning two dedicated chapters, the report explores the vast, yet to be fully realized, potential of AI within the sector and among UPU member states. It outlines a strategic roadmap to capitalize on AI, detailing pivotal use cases that could significantly elevate the efficiency and innovation of postal services at all development levels.

Activity Type Research/Reports/Assessments

UPU

Prediction of postal item delivery day on the UPU global track and trace system

Global

The UPU’s global postal supply chain consists of almost 700,000 postal access points and reaches 95% of the world’s population for the delivery of postal items; mail, parcels and postal payments. In the delivery process to the addressee, the provision of reliable information on the expected delivery date of the postal item is a challenge, especially so for postal operations in least developing, developing countries and small island developing states. Using machine learning models trained on postal big data, the UPU’s global track and trace solution (

Activity Type AI Tools/Solutions