WAVES & Environmental Sustainability

WAVES & Environmental Sustainability

Associating Performance/Efficiency & Environmental Sustainability

The concept of environmentally-friendly shipping is embraced by more and more companies and Organizations, worldwide. WAVES™ Fleet Performance Management goes beyond efficiency and performance. By utilizing maritime data analytics accentuates and optimizes clean technologies as well as environmental initiatives in order to achieve greener terrain and bluer seas.

WAVES Big Data Analytics is a sensor agnostic streaming analytics software framework that allows design and launching of customized dashboards that encompass neural algorithms. A system above all systems.

Depending on its given business logic WAVES can:

  • MEASURE

Accurately monitoring and reporting the carbon footprint across all direct and non-direct port generated emissions.

  • lead any Port Organization to ecotransit

mapping port-shipping-cluster activities in order to enable Port Authorities to discover hidden patterns. WAVES neural algorithms harmonize daily port operations by eliminating systems digital fallacy and technology pitfalls.

How can be achieved?

WAVES enables the data collection from heterogeneous systems that exist either within the infrastructure and superstructure of the port, or will be integrated on-demand. Upon a thorough automated data cleansing procedure, collected data from sensors, will be organized by tagging on a pre-defined detailed ontology in order to disregard unnecessary technical details –as noise- and through a level of abstraction to achieve the data fusion. Data fusion will produce meaningful metrics and will transform data into useful information where smart algorithms coupled with industry expertise will address the domains in quest: hidden pattern recognition, energy efficiency, environmental sustainability and optimal operating profile of any Port Authority.

WAVES is a big data innovation framework that awarded 2015 Loyds Big Data Awards due to the successful orchestration of:

  • sophisticated algorithms deployment,
  • ease of launching of new algorithms via a tailor-made maritime specific programming language,
  • a user friendly and role specific data visualization dashboards and
  • advanced reporting tool.

As a Maritime Intelligence framework WAVES encapsulates big data techniques enabling

  • Handy-casting (reflecting the past)
  • Now-casting (respond to the present) and
  • For-casting (prepare for the future)

whilst neural algorithms provide machine shelf-learning capabilities that set the baseline for a continuous maritime business evolution.

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