Fraunhofer IML is developing algorithms and predictive analytics to support IATA while expanding AI and autonomous robot technology in the air cargo sector.

When natural disasters or extreme weather events hit, delivering aid quickly and efficiently to those affected is crucial. Humanitarian relief efforts commonly rely on the combination of trucks and ...

AI-driven software is helping owners to shape future-ready, data-driven tugs and workboats to improve fleet efficiencies and lower emissions from operations Tug and workboat owners are turning to ...

This project aims to detect and classify 16x16 pixel drawings into 10 categories (Sun, Moon, Tree, etc.) using linear and probabilistic models. The main focus was not just to use high-level libraries, ...

QXO, Inc. continues to redefine the building-products distribution industry via a strong combination of consolidation and digital transformation. Under the guidance of Brad Jacobs’ proven roll-up and ...

AI personalization tailors menus, suggestions, and payment experiences to customer preferences in real time. Predictive inventory systems using AI reduce food waste by up to 25% through accurate ...

Photo source: iMile. iMile CEO Rita Huang explains how the Dubai-based company rebuilt its systems after 2023’s warehouse chaos. As Mexico’s annual online shopping event, Hot Sale has become a window ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

The U.S. logistics industry has no shortage of software promising full automation of time-consuming tasks, dashboards, and efficiency gains. Yet for many companies, the real bottleneck comes in ...

When the maritime trade union Nautilus International asked memberswhat they thought of AI at a forum in January, there was some positive sentiment: “We shouldn’t automatically assume there will be ...

🫀 A machine learning project using logistic regression to predict heart disease risk from clinical data. Built with Python, scikit-learn, and Jupyter notebooks. Achieves 85%+ accuracy on 303-patient ...