From ethnographic research to big data analytics - A case of maritime energy-efficiency optimization

The shipping industry constantly strives to achieve efficient use of energy during sea voyages. Previous research that can take advantages of both ethnographic studies and big data analytics to understand factors contributing to fuel consumption and seek solutions to support decision making is rather scarce. This paper first employed ethnographic research regarding the use of a commercially available fuel-monitoring system. This was to contextualize the real challenges on ships and informed the need of taking a bigdata approach to achieve energy efficiency(EE).Then this study constructed two machine-learning models based on the recorded voyage data of five different ferries over a one-year period. The evaluation showed that the models generalize well on different training data sets and model outputs indicated a potential for better performance than the existing commercial EE system. How this predictive-analytical approach could potentially impact the design of decision support navigational systems and management practices was also discussed. It is hoped that this inter disciplinary research could provide some enlightenment for a richer methodological framework in future maritime energy research.\ua0\ua9 2020 by the authors

From ethnographic research to big data analytics - A case of maritime energy-efficiency optimization

The shipping industry constantly strives to achieve efficient use of energy during sea voyages. Previous research that can take advantages of both ethnographic studies and big data analytics to understand factors contributing to fuel consumption and seek solutions to support decision making is rather scarce. This paper first employed ethnographic research regarding the use of a commercially available fuel-monitoring system. This was to contextualize the real challenges on ships and informed the need of taking a big data approach to achieve energy efficiency (EE). Then this study constructed two machine-learning models based on the recorded voyage data of five different ferries over a one-year period. The evaluation showed that the models generalize well on different training data sets and model outputs indicated a potential for better performance than the existing commercial EE system. How this predictive-analytical approach could potentially impact the design of decision support navigational systems and management practices was also discussed. It is hoped that this interdisciplinary research could provide some enlightenment for a richer methodological framework in future maritime energy researc

"Are You Planning to Follow Your Route?" The Effect of Route Exchange on Decision Making, Trust, and Safety

The Sea Traffic Management (STM) Validation project is a European based initiative which focuses on connecting and updating the maritime world in real time, with efficient information exchange. The purpose of this paper is to evaluate two functions developed during the project: a ship to ship route exchange (S2SREX) function and rendezvous (RDV) information layer, collectively referred to as S2SREX/RDV. S2SREX displays the route segment consisting of the next seven waypoints of the monitored route of a collaborating ship and the RDV layer that predicts a meeting point. S2SREX/RDV provides supplementary information to data acquired by existing navigation systems and is intended to improve situational awareness and safety through a more comprehensive understanding of the surrounding traffic. Chalmers University of Technology and Solent University completed an experiment using twenty-four experienced navigators in bridge simulators. Six traffic scenarios were developed by subject matter experts and tested with and without S2SREX/RDV functionalities. Qualitative data were collected using post-test questionnaires and group debriefs to evaluate the participants\u27 perceptions of S2SREX/RDV in the various traffic scenarios, and quantitative data were collected to assess the ship distances and behavior in relation to the International Regulations for Preventing Collisions at Sea (COLREGs). The results revealed that participants generally trusted the S2SREX/RDV information, and most used S2SREX/RDV for decision support. The quantitative assessment revealed that the COLREGs were breached more often when S2SREX/RDV was used. Experimental findings are discussed in relation to safety, trust, reliance, situational awareness, and human-automation interaction constructs

Towards a Pluralistic Epistemology: Understanding the Future of Human-Technology Interactions in Shipping

The rapid advance of technologies is revolutionizing the way people work and transforming society into a digital world. In the shipping domain, many innovative technical systems have been designed and developed in the past decades, aiming to enable the maritime users to achieve the goal of safety, efficiency and effectiveness. The introduction of advanced technologies into workplaces that are intended to aid humans have also created unprecedented challenges. As their workplaces are inundated with new artefacts that cause confusion and information overloading, human users frequently find themselves in a supporting role to serve technology, being responsible for automation issues and blamed for “human errors” that sometimes result in tragic results. Today’s work in shipping is generally getting more distributed, complex and demanding. These challenges are closely associated with the design and use of technologies. Human-technology interactions in the context of sociotechnical systems has become an important research topic. It explores the relation between humans and machines to illustrate how interface design could address the human limitations, shape social interactions and provide ecological implications. This thesis considers the context of the shipping domain to investigate the impact of innovative technology, design issues and opportunities in various projects that attempt to increase safety or/and efficiency. The exploration and discourse in these applied projects are positioned in sociotechnical systems which include human, technology and organisational constituents. The thesis aims to achieve a deeper understanding of human-technology interactions from psychological, sociological and ecological perspectives, reflecting the ways in which technology interacts with humans. It aims to form a pluralistic epistemology to provide design implications and enlighten knowledge and organisational management within sociotechnical systems. The results have identified many issues related to situation awareness, attention and automation bias. It suggests the importance of adapting interfaces to the human limitations and accommodating the context change to support decision making. Perspectives of Activity Theory, distributed cognition and situated learning have high reference value in human-computer interaction research, providing insightful understanding about the nature of knowledge and interaction design, particularly how tool mediation could facilitate social interaction. In addition, technology-centric design that only concerns “user-interface” interaction is identified having significant limitations in complex systems. “Human errors” and organisational failures should be perceived via a holistic thinking. The results have presented the importance of adopting pluralistic approaches to understand the sociological factors and the nature of the work that is undergoing transitions along the shipping industry’s ecology. Overall, the thesis has identified the need to go beyond the pure cognitivist approach to better understand the complexity of human-computer interaction and human factors research, forming a deepened understanding towards an emerging interdisciplinary language of sociotechnical systems. To truly contribute to safety, efficiency, effectiveness and sustainability, it is critical to develop a pluralistic epistemology and a comprehensive human-centric vision regarding design and technological innovation in the digital revolution

Improving Energy-Efficiency of Location-Triggered Applications On Smartphones

Numerous Location-Based Applications (LBAs) have been emerging in our smartphones over the past several years. Most of them are user-triggered LBAs which heavily depend on manual operations of end users, therefore  easy to lose their accessibility and usability when fail to get instructions in time. While periodic duty cycling of location sensing can guarantee the accuracy of the location and reliability of the desired triggered events, this pattern brings severe battery draining problem caused by power-intensive sensor, let alone redundant high-energy-consumption sensing operation from multiple LBAs without coordination. In contrast, location-triggered applications take the responsibility to manage the location sensing intelligently. They bring better  user experiences by performing actions automatically when reaching predefined locations. This paper proposes adaptive approaches to design energy-efficient location-triggered applications and further models the middleware to build integrated application framework for multiple location-triggered applications in general for energy concern. In the evaluation, business-independent location-triggered applications are implemented in the unified application framework and tested under various scenarios. The results have verified improved usability, higher customization capability and energy efficiency validity of the location-triggered applications and underlying application framework. The establishment of the unified location-triggered application framework provides the reference model for general intelligent energy-efficient LBA development in the future, while broadening the actual use of location-based service for mobile cloud computing

Situation awareness in remote control centres for unmanned ships

The feasibility of unmanned, autonomous merchant vessels is investigated by the EU project MUNIN (Maritime Unmanned Navigation through Intelligence in Networks). The ships will be manned during passage to and from port and unmanned during ocean-passage. When unmanned, the ships will be controlled by an automatic system informed by onboard sensors allowing the ship to make standard collision avoidance manoeuvres according to international regulation. The ship will be continuously monitored by a remote shore centre able to take remote control should the automatic systems falter. For the humans in the shore control centre the usual problems of automations remains as well as a pronounced problem of keeping up adequate situation awareness through remote sensing