A data analytics, decision support and circular economy – based multi-layer optimisation platform towards a holistic energy efficiency, fuel consumption and emissions management of vessels

Informacje na temat projektu

SmartShip

Identyfikator umowy o grant: 823916

DOI

10.3030/823916

Projekt został zamknięty

Data podpisania przez KE 25 Września 2018

Data rozpoczęcia 1 Kwietnia 2019

Data zakończenia 31 Marca 2024

Finansowanie w ramach

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Koszt całkowity

€ 1 472 000,00

Wkład UE

€ 1 472 000,00

Koordynowany przez

DANAOS SHIPPING COMPANY LIMITED
Cyprus

Periodic Reporting for period 2 - SmartShip (A data analytics, decision support and circular economy – based multi-layer optimisation platform towards a holistic energy efficiency, fuel consumption and emissions management of vessels)

Okres sprawozdawczy: 2022-04-01 do 2024-03-31

Podsumowanie kontekstu i ogólnych celów projektu

The SmartShip project capitalizes on available COTS technologies and limited RTD, and delivers an ICT & IoT-enabled holistic cloud-based maritime performance & monitoring system, for the entire lifecycle of a ship, by optimizing energy efficiency, emissions reduction, fuel consumption, and in parallel includes circular economy concepts in the maritime field. SmartShip is motivated by the necessity of bringing together Information and Communication Technologies (ICT) of focused Universities, Research Institutions and Companies from the maritime sector. SmartShip introduces a holistic integrated ICT-based framework for the sustainable, individualized and completely automated energy management of ships, offering a multi-layer optimization in the fields of fuel consumption, energy efficiency and emissions control, in full respect to the implementation of the requirements of maritime regulations (Annex VI of the IMO MARPOL Convention and of Directive 2012/33/EU). The Specific objectives of the SmartShip project were fully met: 1. Marine market needs in energy efficiency and emissions control in parallel with end users’ requirements, towards the definition of accurate, industry-driven case scenarios were accurately described 2. Knowledge exchange between academic and non-academic experts was fostered 3. A Data Analytics and a Decision Support Tool were developed which compile data from existing sensing devices in vessels, manage the operation of the whole IoT environment, and run optimization algorithms to provide suggestions related to the operation of the ship 4. Existing infrastructure in ships and the technologies investigated and developed in Objective #2 were fully exploited in order to enhance the implementation of Circular Economy in the maritime field, in terms of management of engines’ components 5. A holistic framework for energy efficiency and emissions control in maritime through the implementation and validation of new tools (see objectives #3) was offered and integrated with the existing ones (objective #2), for optimizing the efficiency of daily operations 6. The system's effectiveness based on real-life use cases towards the reinforcement of the European Maritime Industry was demonstrated 7. New long-lasting research collaborations were developed and the transfer of knowledge between participating organizations was achieved while an improved research and innovation potential, through the development of training material towards long-term sustainability and exploitation, was fostered

Prace wykonane od początku projektu do końca okresu sprawozdawczego oraz najważniejsze dotychczasowe rezultaty

In WP2 fifteen user requirements have been elicited and four use cases have been identified, namely weather routing optimization, vessel route monitoring, condition-based (predictive) maintenance, and visualization. The marine vessel management optimization roadmap was designed to incorporate circular economy principles in maritime business models. In WP3 SmartShip architecture was designed and comprised of data sourcing, core systems for data analysis, decision support, visualization layer and users' applications for system validation based on the identified use cases in WP2. In WP4, work focused on reviewing the state-of-the-art in the fields of IoT/Data Analytics and reporting any relevant market-ready tool and technology already applied in the maritime industry. Trajectory classification, clustering and anomaly detection techniques in the maritime domain were the focus of the investigation. A SmartShip advanced data analytics module was designed and integrated into the SmartShip core system as a built-in system function. In WP5, an internal report about the market-ready maritime application has been prepared introducing a discussion of the improvement vectors (gap analysis) of the existing applications. A SmartShip decision support module was developed and integrated into the SmartShip core system as a built-in system component. In WP6, both modules (advanced data analytics and decision support system) were integrated into one holistic framework in two iterated versions. The SmartShip platform was developed on top of the existing DANAOS system for fleet performance monitoring. Principles and practices of Circular Economy were taken into consideration to meet the challenges of modern maritime with respect to sustainability and green economy. In pilot testing rounds that followed the release of SmartShip versions, a group of end-users evaluated the system in order to validate functional and non-functional requirements as drafted and elicited in WP2. Most of the designated KPIs and the evaluation criteria have been satisfied. The SmartShip users offered their recommendations for continuous improvements of the SmartShip system supporting an incremental change towards a market-ready digital service to be provided to the industry through a comprehensive and solid business model. Project communication (WP7) was rich and productive and materialized through a variety of channels including the organization of training sessions and demonstrations, publication of newsletters, participation in conferences and production of promotional material. The project's social media networking was strong whilst synergies with affiliated projects were established.

Innowacyjność oraz oczekiwany potencjalny wpływ (w tym dotychczasowe znaczenie społeczno-gospodarcze i szersze implikacje społeczne projektu)

SmartShip is capitalizing on existing data-driven fleet monitoring systems applied to the maritime industry and based on IoT and data analytics. All interactions through the project's secondments between academia and non-academia in a multi-disciplinary environment generate value in aspects of 1. Knowledge of maritime business/operational needs in fleet management for improvements in energy consumption and emission control 2. Innovative ideas for a data and ICT-driven framework to monitor the daily operation of a shipping company 3. Design of use-cases that pave the way toward an environmentally friendly, green, sustainable and digitalized/smart vessel 4. Familiarization with new technologies/advanced methodologies in IoT networks, decision support systems, data analytics/optimization algorithms 4. Incorporation of circular economy principles and LCA concept in maritime ICT systems, maintenance of machinery and management of the vessel 5.Design of agile release plans to deliver value proposition in maritime digital systems 6. Development of an integrated and circular by design software 7. Planning and deployment of pilots to formally test and evaluate the system against end-users’ requirements 8.Creation of solid business models for the promotion of the project product to the market. The most important result of these interactions is two-fold: 1 Industry utilizes/embraces research/knowledge transfer from the academia/institutions or/and ICT companies to enhance features, functionalities and performance of the existing infrastructure with a principal target: a. to reduce emissions/carbon footprint of vessel operation b. comply with the newly introduced environmental indicators of IMO toward the goal of zero emission waterborne transport.2. Academia or ICT companies gain insights on maritime business logic enabling better fit of technologies in real business needs or further training of algorithms to better match with real challenges of the vessel operation. The relationship between research institutions and industry builds the trust for future exploitation of resources in both arenas, enhances the skillset of seconded staff and enables the build-up of new collaborations beyond the project boundaries.

Architecture of the SmartShip infrastracture