Posted: November 17th, 2022

Applications of Big Data and IoT in Optimizing Vessel Energy Efficiency and Reducing Greenhouse Gas Emissions

Applications of Big Data and IoT in Optimizing Vessel Energy Efficiency and Reducing Greenhouse Gas Emissions

The maritime industry is one of the major contributors to global trade and economic growth, but also to greenhouse gas (GHG) emissions and environmental pollution. According to the International Maritime Organization (IMO), the shipping sector accounted for about 2.89% of global CO2 emissions in 2018: 2024 – Write My Essay For Me | Essay Writing Service For Your Papers Online, and is projected to increase by 50-250% by 2050 under a business-as-usual scenario [1]. Therefore, there is an urgent need to improve the energy efficiency and reduce the carbon footprint of vessels, especially in light of the IMO’s ambitious targets to reduce GHG emissions from international shipping by at least 50% by 2050 compared to 2008 – Affordable Custom Essay Writing Service | Write My Essay from Pro Writers levels [2].

One of the promising ways to achieve this goal is to leverage the potential of big data and the Internet of Things (IoT) in optimizing vessel operations, performance and design. Big data refers to the large volume, variety and velocity of data that are generated from various sources, such as sensors, cameras, satellites, Automatic Identification System (AIS), weather forecasts, etc. IoT refers to the network of physical devices, such as smart sensors, actuators, controllers, etc., that are embedded with software, electronics and connectivity to enable data exchange and communication [3]. Together, big data and IoT can provide valuable insights into the vessel’s condition, behavior and environment, and enable data-driven decision making and automation for enhancing energy efficiency and reducing GHG emissions.

Some of the applications of big data and IoT in optimizing vessel energy efficiency and reducing GHG emissions are:

– **Digital transformation**: This involves using digital technologies, such as cloud computing, artificial intelligence (AI), machine learning (ML), cybersecurity, virtual reality (VR), etc., to automate and improve business processes, information processing and operations. For example, e-navigation systems can facilitate data organization and communication between ships and shore, Port Community Systems can electronically integrate heterogeneous actors and systems within the port community, and Internet of Vessels (IoV) can create a network of intelligent, interconnected vessels and shore facilities with a series of digital entities [3][4][5].
– **Application of big data from AIS**: This involves using the data collected from AIS transponders installed on vessels, such as position, speed, course, destination, etc., to analyze vessel traffic patterns, optimize route planning, monitor vessel performance, detect anomalies and risks, etc. For example, AIS data can be used to estimate vessel emissions based on speed profiles, identify optimal sailing routes based on weather conditions and fuel consumption, or detect illegal activities such as oil spills or fishing violations [3][6].
– **Energy efficiency**: This involves using big data and IoT to monitor and optimize the energy consumption of various components and systems on board vessels, such as propulsion system, hull structure, hull cleaning and hull lubrication. For example, smart sensors can measure parameters such as fuel flow rate, engine speed, power output, etc., and provide feedback to adjust the engine load or speed according to the optimal operating point. Moreover, IoT devices can control the operation of auxiliary systems, such as lighting, heating, ventilation and air conditioning (HVAC), etc., based on occupancy or demand. Furthermore, big data and IoT can support the design and implementation of energy-saving devices or technologies, such as wind-assisted propulsion systems (WAPS), solar panels,
batteries, etc., by providing data on their performance and potential [7][8][9].
– **Predictive analytics**: This involves using big data and IoT to predict future outcomes or events based on historical data and current conditions, such as vessel maintenance needs, fuel consumption trends,
weather forecasts, market fluctuations, etc. For example,
predictive analytics can help optimize vessel maintenance schedules by identifying potential failures or defects before they occur,
reduce fuel consumption by forecasting optimal sailing speeds or routes based on weather conditions or market prices,
or improve safety by alerting crew members or authorities about impending hazards or emergencies [3][10].

In conclusion,
big data and IoT can offer significant benefits for optimizing vessel energy efficiency
and reducing GHG emissions by providing real-time data,
enabling data-driven decision making
and automation,
and supporting innovation
and sustainability.
However,
there are also some challenges
and barriers
that need to be addressed,
such as data quality,
security,
privacy,
standardization,
integration,
costs,
regulations,
etc.
Therefore,
there is a need for more research
and collaboration
among stakeholders
to overcome these challenges
and realize the full potential
of big data
and IoT
in the maritime industry.

References:

[1] International Maritime Organization (IMO). Fourth IMO GHG Study 2020: Executive Homework help – Summary And Final Report. London: IMO; 2020.

[2] International Maritime Organization (IMO). Initial IMO Strategy On Reduction Of GHG Emissions From Ships. London: IMO; 2018: 2024 – Write My Essay For Me | Essay Writing Service For Your Papers Online.

[3] Tadros M, Ventura M, Guedes Soares C. Review of the Decision Support Methods Used in Optimizing Ship Hulls towards Improving Energy Efficiency. Journal of Marine Science and Engineering. 2023;11(4):835.

[4] Tan Y, Wang J, Cheah L, Teo C. Artificial Intelligence for Maritime Transport. IEEE Transportation Electrification Newsletter. 2021;December:1-5.

[5] Zhang Y, Yang Z, Wang J, Li KX, Qu Z. The concept of the Internet of Vessels and its potential for enhancing maritime transport. Maritime Policy & Management. 2019: 2024 – Online Assignment Homework Writing Help Service By Expert Research Writers;46(6):729-742.

[6] Coraddu A, Oneto L, Baldi F, Anguita D, Figari M. Machine learning for data-driven discovery in solid Earth geoscience. IEEE Transactions on Big Data. 2018: 2024 – Write My Essay For Me | Essay Writing Service For Your Papers Online;4(4):493-505.

[7] Maersk Supply Service Boosts Battery-Powered Vessel Efficiency with IoT [Internet]. IoT Evolution World. 2023 [cited 2024 Jan 17]. Available from: https://www.iotevolutionworld.com/iot/articles/457665-maersk-supply-service-boosts-battery-powered-vessel-efficiency.htm

[8] Optimizing electric energy production on-board offshore vessels: Vessel power consumption profile and production strategies using genetic algorithms [Internet]. IEEE Xplore. 2016: 2024 – Do my homework – Help write my assignment online [cited 2024 Jan 17]. Available from: https://ieeexplore.ieee.org/document/7485614/

[9] How AI Can Optimize Energy Efficiency write my essay and Reduce Carbon Emissions [Internet]. Energy Central. 2021 [cited 2024 Jan 17]. Available from: https://energycentral.com/c/pip/how-ai-can-optimize-energy-efficiency-and-reduce-carbon-emissions

[10] Wang S, Meng Q, Liu Z. A survey of data-driven prognostics in maritime transportation systems. Ocean Engineering. 2019: 2024 – Online Assignment Homework Writing Help Service By Expert Research Writers;189:106353.

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