Ship Operation Analysis and Optimization via Mobile Application
DOI:
https://doi.org/10.13052/jmm1550-4646.2034Keywords:
Operation efficiency analysis, data analytics, mobile applications, ship safety, onboard measurement, green fuels, hybrid structure, cloud calculations, edge computationsAbstract
This paper is devoted to studying the structure and prospects of ship operations analysis and optimization via mobile applications, focusing on integrating multiple existing onboard monitoring and control systems. The main parts of the paper describe the current state of the most essential components of future overall shipping and ship design optimization using onboard and cloud-based monitoring systems from a dual transition point of view. Special attention is paid to the ship’s and its equipment’s efficiency improvements, fuel consumption and emissions reduction, cost-effectiveness enhancement, metrological accuracy, and compliance with current regulations. Timely development and deployment of the proposed onboard monitoring systems, in combination with up-to-date mobile applications and cloud computing, should play a crucial role in promoting sustainable and environmentally friendly shipping practices, improving operational performance, and reducing risks to human life at sea and the environmental impact of shipping. Another objective of this research is to review the current state of infrastructure used for fuel control, focusing on measurement systems and related analytics using appropriate mobile applications. The recommendations for integrating new and adopting existing monitoring systems and equipment for promising alternative fuels must be given to meet current regulations and provide required safety levels and measurement quality.
Downloads
References
Initial IMO Strategy on Reduction of GHG Emissions from Ships, Resolution MEPC.304 (72) adopted on 13 April 2018; International Maritime Organization, London, UK, 2018.
E. Whieldon, ‘Your climate change goals may have a maritime shipping problem’, S&P Global, Published June 2021, Accessed November 15, 2023. [URL] https://www.spglobal.com/esg/insights/your-climate-change-goals-may-have-a-maritime-shipping-problem.
I. Parry et al. ‘Carbon Taxation for International Maritime Fuels: Assessing the Options,’ IMF, Sep 11, 2018, Business & Economics, 39 p.
J. Hansson et al. ‘The Potential Role of Ammonia as Marine Fuel – Based on Energy Systems Modelling and Multi-Criteria Decision Analysis’, Sustainability 2020, 12, 3265. https://doi.org/10.3390/su12083265.
C. McKinlay et al. ‘A Comparison of hydrogen and ammonia for future long distance shipping fuels. LNG/LPG and Alternative Fuel Ships,’ Royal Institute of Naval Architects, HQ, 8–9 Northumberland Street, London WC2N 5DA, London, United Kingdom. 29–30 Jan 2020. pp. 53–65.
S. Ryzhkov, et al. Creation of universal transport vessels and offshore structures. III International Conference “Innovations in Shipbuilding and Ocean Technology. – NUOS, Mykolaiv, 2012, pp. 7–17.
M. Alexandrov et al. Instrumental control of Stability and Operational Safety of Seagoing Ships. – Proc. of STAB-90. – Naples, 1990. – pp. 512–518.
Yu. Zhukov et al. ‘Sensory expert system for ship safety monitoring,‘ Athens, 1990, pp. 207–212.
Y. Zhukov et al. ‘Polymetric Sensing in Intelligent Systems’, in R. J. Duro, Y. P. Kondratenko (eds) Advances in Intelligent Robotics and Collaborative Automation, River Publishers, Aalborg, 2015, pp. 211–234.
K. Reichert et al. ‘X-Band Radar as a Tool to Determine Spectral and Single Waves Properties.’ in Proc. of 5th Intern. Symposium WAVES 2005, Madrid, Spain, 2005. doi: 10.1115/OMAE2006-92015.
Y. Zhukov et al. ‘Intelligent Polymetric Systems Industrial Applications,’ CEUR Workshop Proceedings, Vol. 2762, 2020, pp. 122–137. https://ceur-ws.org/Vol-2762/paper8.pdf.
Y. Kondratenko et al. ‘Towards Implementing the Strategy of Artificial Intelligence Development: Ukraine Peculiarities’, CEUR Workshop Proceedings, vol. 3513, 2023, pp. 106–117, https://ceur-ws.org/Vol-3513/paper09.pdf.
Y. Kondratenko et al. ‘Inspection mobile robot’s control system with remote IoT-based data transmission,’ Journal of Mobile Multimedia, Vol. 17, Is. 4. pp. 499–522, 2021. doi: 10.13052/jmm1550-4646.1742.
O. Kozlov, et al. ‘Swarm Optimization of Fuzzy Systems for Mobile Robots with Remote Control,’ Journal of Mobile Multimedia, 2023, 19(3), pp. 839–876.
O. Striuk et al. ‘Implementation of Generative Adversarial Networks in Mobile Applications for Image Data Enhancement,’ Journal of Mobile Multimedia, 2023, 19(3), pp. 823–838.
V. Kuntsevich, et al. (Eds). Control Systems: Theory and Applications. River Publishers, Gistrup, Delft, 2018. https://www.riverpublishers.com/book_details.php?book_id=668.
R. Duro et al. (Eds). Advances in intelligent robotics and collaborative automation. River Publishers, Aalborg, 2015, https://doi.org/10.13052/rp-9788793237049. Last accessed 2023/01/11.
V. Timchenko et al., ‘Decision support system for the safety of ship navigation based on optical color logic gates.’ CEUR Workshop Proceedings, vol. 3347, 2022, pp. 42–52, https://ceur-ws.org/Vol-3347/Paper_4.pdf.
Y. Kondratenko, S. Sidorenko, ‘Ship Navigation in Narrowness Passes and Channels in Uncertain Conditions: Intelligent Decision Support’, in P. Shi, et al. (eds), ‘Complex Systems: Spanning Control and Computational Cybernetics: Foundations. Studies in Systems, Decision and Control,’ vol. 414, 2022, pp. 475–493, Springer, Cham, https://doi.org/10.1007/978-3-030-99776-2_24.
Y. Zhukov et al. Building System of Seafaring Safety Assurance on the Basis of Holonic Agents. Shipbuilding & Marine Infrastructure, No. 2(4), 2015, pp. 74–83.
V. Domova et al. “An Interactive Surface Solution to Support Collaborative Work Onboard Ships,” in Proc. of the 2013 ACM Int. Conf. on Interactive Tabletops and Surfaces (ITS ’13), St. Andrews, Scotland, United Kingdom, 2013, pp. 265–272, doi: 10.1145/2512349.2512804.
M. Höyhtyä et al. ‘Connectivity for autonomous ships: Architecture, use cases, and research challenges,’ 2017 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea (South), 2017, pp. 345–350, doi: 10.1109/ICTC.2017.8191000.
S. Aslam et al., ‘Internet of Ships: A Survey on Architectures, Emerging Applications, and Challenges,’ in IEEE Internet of Things Journal, vol. 7, no. 10, pp. 9714–9727, Oct. 2020, doi 10.1109/ JIOT.2020.29 93411.
‘OCTOPUS-Onboard. Ship Motions Monitoring and Advisory System.’ – URL: https://www.wartsila.com/encyclopedia/term/octopus-onboard-system.
G. Pada. ‘Meet data-centric engineering: Engineering better relationships and more sustainable capital projects,’ White paper: https://discover.aveva.com/nurture-design-build-stream1/whitepaper-meet-data-centric-engineering.
Be mobile and stay safe with the Wärtsilä BridgeMate app. – URL: https://www.wartsila.com/insights/article/be-mobile-and-stay-safe-with-the-wartsila-bridgemate-app.
N. Madusanka et al. ‘Digital Twin in the Maritime Domain: A Review and Emerging Trends,’ Journal of Maritime Science and Engineering, 2023, 11, 1021. https://doi.org/10.3390/jmse1105102.
G. Koutitas et al. ‘A review of energy efficiency in telecommunication networks,’ Proc. In Telecomm. Forum (TELFOR), pp. 1–4, Serbia, Nov. 2009.
I. Cerutti et al. ‘Designing power-efficient WDM ring networks’, ICST Int. Conf. on Networks for Grid Applic., Athens, 2009.
O. Vynogradov et al. ‘Sensor mapping automation for ship remote monitoring systems. (in Ukrainian) Proceedings of the X International Conference «Sensors, Instruments, Systems – 2023», Cherkasy, Sept. 2023. pp. 57–60.
W. Vereecken et al., ‘Energy Efficiency in thin client solutions’, ICST Int. Conf. on Networks for Grid Applic., Athens, 2009.
S. Thombre et al., ‘Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review,’ in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 1, pp. 64–83, Jan. 2022, doi: 10.1109/TITS.2020.3023957.
A. García-Domínguez, ‘Mobile applications, cloud and bigdata on ships and shore stations for increased safety on marine traffic; a smart ship project,’ 2015 IEEE International Conference on Industrial Technology (ICIT), Seville, Spain, 2015, pp. 1532–1537, doi: 10.1109/ICIT.2015. 7125314.
A. Garcia Dominguez, ‘Smart Ships: Mobile Applications, Cloud and Bigdata on Marine Traffic for Increased Safety and Optimized Costs Operations,’ in 2014 2nd International Conference on Artificial Intelligence, Modelling and Simulation, 2014, pp. 303–308.
S. Mallam et al. ‘Rethinking Maritime Education, Training, and Operations in the Digital Era’, in Applications for Emerging Immersive Technologies, J. Mar. Sci. Eng. 2019, 7, 428. https://doi.org/10.3390/jmse7120428.
P. Sanchez-Gonzalez et al. ‘Toward Digitalization of Maritime Transport,’ Sensors, 19(4), 926, 2019, https://doi.org/10.3390/s19040926.
Improving the energy efficiency of ships. IMO WEB: URL https://www.imo.org/en/OurWork/Environment/Pages/Improving%20the%20energy%20efficiency%20of%20ships.aspx.
Resolution MEPC.308(73)) – 2018 Guidelines on the method of calculation of the attained Energy Efficiency Design Index (EEDI) for new ships.
Resolution MEPC.346(78) – 2022 Guidelines for the Development of a SEEMP.
Resolution MEPC.347(78) – Guidelines for the Verification and Company Audits by the Administration of SEEMP Part III.
Resolution MEPC.348(78) – 2022 Guidelines for Administration Verification of Ship Fuel Oil Consumption Data and Operational Carbon Intensity.
Resolution MEPC.352(78) – 2022 Guidelines on Operational Carbon Intensity Indicators and the Calculation Methods (CII Guidelines, G1).
Resolution MEPC.353(78) – 2022 Guidelines on the Reference Lines for Use with Operational Carbon Intensity Indicators (CII Reference Lines Guidelines, G2).
Resolution MEPC.354(78) – 2022 Guidelines on the Operational Carbon Intensity Rating of Ships (CII Rating Guidelines, G4).
D. Memos, ‘Shaking up the Maritime Industry through Open Data and Crowdsourcing,’ in Journal of Continuous and Disruptive Innovation, vol. 1, pp. 16, 2017.
R. Hijdra. ‘Autonomous underwater maintenance dredger (AUMD).’ URL: https://c-job.com/research-and-development/autonomous-shipping/autonomous-underwater-maintenance-dredger/.
M. Bakker et al. ‘A model predictive control approach towards the energy efficiency of submerged dredging,’ in Ocean Engineering, v. 287, 2023, 115770.
Tian Y. et al. ‘Adaptive coordinated path tracking control strategy for autonomous vehicles with direct yaw moment control’, Chin. J. Mech. Eng., 35, 2022, pp. 1–15.
Gudyma I. et al. ‘Flexible Measurement System for Online Monitoring and Control of Various Liquids,’ in Innovations in shipbuilding and ocean engineering: Proc. of the XII international scientific conference, – Mykolaiv: NUoS, 2022, pp. 355–358.
Directive 2014/94/EU of the EU Parliament 22 October 2014 ‘On the deployment of alternative fuels infrastructure,’ https://eur-lex.europa.eu/eli/dir/2014/94/oj. Accessed on 01.11.2023.
Y. Kondratenko, A. Shevchenko, Y. Zhukov, V. Slyusar, G. Kondratenko, M. Klymenko, O. Striuk, ‘Analysis of the Priorities and Perspectives in Artificial Intelligence Implementation’, 2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT), Athens, Greece, 2023, pp. 1–8, doi: 10.1109/DESSERT61349.2023.10 416432.
