Hermes Logistics Technologies (HLT) is working with researchers at the IT University of Copenhagen (ITU) in Denmark and with Dnata Australia to explore new machine learning models aimed at delivering predictive business analytics for the air cargo handling operator and improve efficiencies, costs, and services.
The Artificial Intelligence (AI) algorithms will run data from Dnata Australia’s air cargo handling activities. This will be managed and recorded via the new Hermes Digital Ecosystem that Dnata has deployed within its air cargo handling operations, which includes a full ‘data lake’ infrastructure that “captures and stores all of Dnata’s Hermes New Generation (NG) Business Intelligence events”.
The partners said the machine learning models will enable Dnata, the Dubai-headquartered global air cargo handling specialist, “to make predictive business process decisions providing key insights on efficiencies, costs, and new services”.
Alex Labonne, Chief Technology Officer at HLT, said: “Machine learning is part of HLT’s digital agenda and our data lakes are a fantastic source of events and data, which are always up to date and ready to inform and train AI models in the Hermes Cloud. Successfully trained models will form new predictive functionalities for Dnata and help them refine an already competitive cargo handling offering.”
The ITU team, headed by Professor Philippe Bonnet and working with HLT, will create, test, and develop the predictive models over the coming months to explore the design of cloud-native enterprise machine learning solutions.
“This is the future of enterprise machine learning envisaged by cloud providers, where any enterprise can incorporate data-driven predictions into their business processes,” said Bonnet. “Collaborating with HLT and Dnata is a unique opportunity for us to explore the capabilities and limitations of cloud-based enterprise machine learning.”
Dnata recently went live with HLT’s H5 Cargo Management System (CMS) at six airports across Australia in Melbourne, Sydney, Adelaide, Darwin, Perth, and Brisbane. Terence Yong, Cargo Development Director for the Asia Pacific at Dnata, commented: “Dnata is looking forward to using predictive modeling to enhance our cargo planning and operational processes.
This data science not only benefits our interaction with customer airlines, but it also enables us to anticipate the demand patterns in advance for more efficient operations.”
Hermes said the Dnata machine learning prototype “is part of HLT’s digital agenda to deliver value-added services using Big Data Analytics”.
