MODEL FOR IMPROVING SHIPMENT MANAGEMENT EFFICIENCY BY INTEGRATING ARTIFICIAL INTELLIGENCE AND IoT TECHNOLOGIES IN THE POSTAL-LOGISTICS SYSTEM

This paper investigates the integration of artificial intelligence (AI) and the Internet of Things (IoT) for real-time monitoring, sorting and delivery management in postal logistics. The study considers the transformation of postal services under digital economy and e-commerce conditions and proposes a conceptual architecture consisting of IoT sensing, a unified data platform and an AI-based decision-support module. A set of indicators is developed to jointly evaluate service quality, delay, routing cost and data accuracy. Scenario-based calculations are used to demonstrate the practical applicability of the proposed approach without presenting hypothetical values as empirical field results.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-08
DOI
https://doi.org/10.5281/zenodo.23228056
Primary Topic
Transport and Logistics Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MODEL FOR IMPROVING SHIPMENT MANAGEMENT EFFICIENCY BY INTEGRATING ARTIFICIAL INTELLIGENCE AND IoT TECHNOLOGIES IN THE POSTAL-LOGISTICS SYSTEM

Mamatovich Juraev Nurmakhamad, Muhabbat Akbarjon qizi Aliqosimova
Zenodo (CERN European Organization for Nuclear Research)
Transport and Logistics Innovations
article

MODEL FOR IMPROVING SHIPMENT MANAGEMENT EFFICIENCY BY INTEGRATING ARTIFICIAL INTELLIGENCE AND IoT TECHNOLOGIES IN THE POSTAL-LOGISTICS SYSTEM

Mamatovich Juraev Nurmakhamad, Muhabbat Akbarjon qizi Aliqosimova
article en

Abstract

This paper investigates the integration of artificial intelligence (AI) and the Internet of Things (IoT) for real-time monitoring, sorting and delivery management in postal logistics. The study considers the transformation of postal services under digital economy and e-commerce conditions and proposes a conceptual architecture consisting of IoT sensing, a unified data platform and an AI-based decision-support module. A set of indicators is developed to jointly evaluate service quality, delay, routing cost and data accuracy. Scenario-based calculations are used to demonstrate the practical applicability of the proposed approach without presenting hypothetical values as empirical field results.

Zenodo (CERN European Organization for Nuclear Research)
Kurgan State University (RU)
Openalex Percentile: Top 12%
Transport and Logistics Innovations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.