Hermes

Hermes Logistics Technologies (HLT) is a leading provider of a Cargo Management Ecosystem to the air cargo industry.

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    Hermes Logistics Technologies teams up with the IT University of Copenhagen and dnata for machine learning trials


    The research team will use Artificial Intelligence algorithms to analyse data about dnata cargo activity in order to develop predictive business analytics models

    London, UK, Tuesday 3rd November 2020 – Hermes Logistics Technologies (HLT) is working with researchers at the IT University of Copenhagen (ITU), Denmark, and dnata Australia to explore new machine learning models aimed at delivering predictive business analytics.

    The Artificial Intelligence (AI) algorithms will run data from dnata Australia’s  new Hermes Digital Ecosystem, which has a full datalake infrastructure that captures and stores all of dnata’s Hermes New Generation Business Intelligence events.

    The machine learning models will enable dnata to make predictive business process decisions providing key insights on efficiencies, costs, and new services.

    “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,” said Alex Labonne, Chief Technology Officer at HLT.

    “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 Prof. 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.

    “dnata is looking forward to using predictive modelling to enhance our cargo planning and operational processes. This data science not only benefits our interaction with customer airlines, it enables us to anticipate the demand patterns in advance for more efficient operations,” said Terence Yong, Cargo Development Director, Asia Pacific, dnata.

    The dnata machine learning prototype is part of HLT’s digital agenda to deliver value added services using Big Data analytics.

    ENDS

    About Hermes

    Hermes Logistics Technologies (HLT) is a provider of Cargo Management Systems to the air cargo industry. Its core application suite includes Hermes CMS (Cargo Management System), Hermes HMS (Hub Management System) and HBI (Hermes Business Intelligence).

    Hermes CMS manages all import, export, messaging, service monitoring and accounting processes for traditional cargo ground handling agents. Hermes HMS steers all inbound, outbound, messaging, SLA and accounting processes for airline hubs or transit shed operators. HBI is a comprehensive big data analytical tool, enabling informed management and operational decisions.

    Headquartered in the United Kingdom, HLT has been pioneering, developing and evolving cargo management systems for air cargo since 2002.

    All HLT applications are designed and driven by the HLT team of air cargo experts. Built with the specific requirements of air cargo handlers and airlines in mind, HLT products streamline cargo ground handling processes and maximise profits by using inbuilt best practice to reduce handling and operational errors.

    Visit www.hermes-cargo.com for more information.


    Download Files Here

    • 1 jpg Yuval Baruch
      Yuval Baruch, Chief Operating Officer, HLT.
      File size: 126 KB Downloads: 24
    • 2 jpg ITU
      The ITU team, headed by Professor Philippe Bonnet and working with HLT, will create, test, and develop the predictive models over the coming months.
      File size: 2 MB Downloads: 12
    • 3 png dnata
      dnata is looking forward to using predictive modelling to enhance cargo planning and operational processes
      File size: 531 KB Downloads: 14

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    Hermes Logistics Technologies teams up with the IT University of Copenhagen and dnata for machine learning trials

    The research team will use Artificial Intelligence algorithms to analyse data about dnata cargo activity in order to develop predictive business analytics models

    London, UK, Tuesday 3rd November 2020  Hermes Logistics Technologies (HLT) is working with researchers at the IT University of Copenhagen (ITU), Denmark, and dnata Australia to explore new machine learning models aimed at delivering predictive business analytics.

    The Artificial Intelligence (AI) algorithms will run data from dnata Australia’s  new Hermes Digital Ecosystem, which has a full datalake infrastructure that captures and stores all of dnata’s Hermes New Generation Business Intelligence events.

    The machine learning models will enable dnata to make predictive business process decisions providing key insights on efficiencies, costs, and new services.

    “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,” said Alex Labonne, Chief Technology Officer at HLT.

    “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 Prof. 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.

    “dnata is looking forward to using predictive modelling to enhance our cargo planning and operational processes. This data science not only benefits our interaction with customer airlines, it enables us to anticipate the demand patterns in advance for more efficient operations,” said Terence Yong, Cargo Development Director, Asia Pacific, dnata.

    The dnata machine learning prototype is part of HLT’s digital agenda to deliver value added services using Big Data analytics.

    ENDS

    About Hermes

    Hermes Logistics Technologies (HLT) is a provider of Cargo Management Systems to the air cargo industry. Its core application suite includes Hermes CMS (Cargo Management System), Hermes HMS (Hub Management System) and HBI (Hermes Business Intelligence).

    Hermes CMS manages all import, export, messaging, service monitoring and accounting processes for traditional cargo ground handling agents. Hermes HMS steers all inbound, outbound, messaging, SLA and accounting processes for airline hubs or transit shed operators. HBI is a comprehensive big data analytical tool, enabling informed management and operational decisions.

    Headquartered in the United Kingdom, HLT has been pioneering, developing and evolving cargo management systems for air cargo since 2002.

    All HLT applications are designed and driven by the HLT team of air cargo experts. Built with the specific requirements of air cargo handlers and airlines in mind, HLT products streamline cargo ground handling processes and maximise profits by using inbuilt best practice to reduce handling and operational errors.

    Visit www.hermes-cargo.com for more information.

    Our Vision

    The objective of SESAR is to modernise European ATM by defining, developing and delivering new or improved technologies and procedures (SESAR Solutions).

    SESAR’s vision builds on the notion of trajectory-based operations’ and relies on the provision of air navigation services (ANS) in support of the execution of the business or mission trajectory — meaning that aircraft can fly their preferred trajectories without being constrained by airspace configurations.

    SESAR Deployment Manager

    The SESAR Deployment Manager (SDM) function is defined by the Article 9 of Commission Implementing Regulation (EU) N°409/2013. Under the oversight of the European Commission, the SDM function consists of the synchronisation and the coordination of the deployment of the Common Projects. A Common Project is a Commission Implementing Regulation which mandates the implementation of the most essential operational changes in the European ATM Master Plan by the Member States of the European Union and their operational stakeholders. The first Common Project is known as the Pilot Common Project (PCP) and is defined by the Regulation (EU) N°716/2014. The SDM synchronises and coordinates implementation against the SESAR Deployment Programme which is a project view of the Common Projects organizing their implementation into optimum sequences of activities by all the stakeholders required to implement. To develop and maintain the SESAR Deployment Programme in close consultation with all the stakeholders is another important task under the SDM function.