Comparative analysis of Internet of Things (IOT) implementation: A case study of Ghana and the USA - vision, architectural elements, and future directions

World Journal of Advanced Engineering Technology and Sciences, Journal Year: 2024, Volume and Issue: 11(1), P. 180 - 199

Published: Feb. 14, 2024

This paper presents a comprehensive comparative analysis of the Internet Things (IoT) implementation in Ghana and USA, focusing on their respective visions, architectural elements, future directions. The study begins with an introduction to IoT's significance modern society, followed by detailed methodology outlining research design, data collection methods, criteria for analysis. findings reveal distinct approaches IoT reflecting varying levels technological infrastructure, economic impact, societal influence. delves into aspects vision, including strategic goals advancements, examines elements such as hardware, software, network solutions, management. also addresses challenges barriers implementation, highlighting technical, policy, constraints. Furthermore, it explores emerging trends, opportunities, recommendations development, providing final thoughts trajectories both countries. contributes understanding role different national contexts offers valuable insights initiatives policies.

Language: Английский

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Harnessing AI for Sustainable Shipping and Green Ports: Challenges and Opportunities

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(14), P. 5994 - 5994

Published: July 9, 2024

The maritime industry, responsible for moving approximately 90% of the world’s goods, significantly contributes to environmental pollution, accounting around 2.5% global greenhouse gas emissions. This review explores integration artificial intelligence (AI) in promoting sustainability within sector, focusing on shipping and port operations. By addressing emissions, optimizing energy use, enhancing operational efficiency, AI offers transformative potential reducing industry’s impact. highlights application fuel optimization, predictive maintenance, route planning, smart management, alongside its role autonomous logistics management. Case studies from Maersk Line Port Rotterdam illustrate successful implementations, demonstrating significant improvements emission reduction, monitoring. Despite challenges such as high implementation costs, data privacy concerns, regulatory complexities, prospects industry are promising. Continued advancements technologies, supported by collaborative efforts public–private partnerships, can drive substantial progress towards a more sustainable efficient industry.

Language: Английский

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Machine Learning-enhanced loT and Wireless Sensor Networks for predictive analysis and maintenance in wind turbine systems

International Journal of Intelligent Networks, Journal Year: 2024, Volume and Issue: 5, P. 133 - 144

Published: Jan. 1, 2024

Wind power (WP) represents a Renewable Energy Source (RES) that has noticed substantial development as people continuously search for green energy sources. Utilizing predominantly Predictive Maintenance (PM) of Turbines (WT), this research analyzes the potential benefits could be generated by (WE) through use Internet Things (IoT) and Wireless Sensor Networks (WSN). This recommends an Things-WSN model PM comprised three distinct phases: primary phase is collection data via sensors, second transmission connection to Internet, final implementation analytics on in context cloud computing. For analytics, work introduces Convolutional Long Short-Term Memory (PM-C-LSTM) combines spatial pattern recognition capabilities Neural Network with sequential prowess LSTM networks. The PM-C-LSTM CNN recognizing patterns networks analyzing way doesn't affect accuracy WT-PM. A Failure Sample Generator also fused into study measure soft failure hard factors improve predictive Machine Learning (ML) model. Data became available over 16 months while was applied Farm (WF) positioned Qinghai-Tibet Plateau. It been demonstrated possesses enhanced comparing its efficiency other standard models using selection performance metrics. result test indicates there probability hybrid IoT ML will methods WT, which subsequently help effectiveness sustainability WE generation.

Language: Английский

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Data privacy and security challenges in environmental research: Approaches to safeguarding sensitive information

International Journal of Applied Research in Social Sciences, Journal Year: 2024, Volume and Issue: 6(6), P. 1193 - 1214

Published: June 13, 2024

This study provides a comprehensive examination of data privacy and security within the realm environmental research, highlighting evolving challenges innovative solutions in safeguarding sensitive data. Employing systematic literature review content analysis, this research scrutinizes peer-reviewed articles, legal documents, policy papers published from 2014 to 2024. The study's objectives were explore fundamental principles, assess key developments cutting-edge solutions, understand impact international standards regulatory bodies on protection studies. Key findings reveal growing emphasis robust governance frameworks, driven by advancements digital technologies global diffusion regulations such as GDPR. Innovations encryption anonymization techniques have emerged critical tools enhancing security. However, identifies pressing need for interdisciplinary collaboration stakeholder engagement navigate complex landscape effectively. concludes that future is intricately linked strategic integration measures. It recommends proactive approach protection, emphasizing importance compliance with regulations, adoption privacy-by-design development education training programs. Future should focus advancing exploring socio-ethical implications use studies, ensuring ethical stewardship information. Keywords: Data Privacy, Environmental Research, Security Solutions, International Regulations.

Language: Английский

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Internet of Things-Based Control of Induction Machines: Specifics of Electric Drives and Wind Energy Conversion Systems

Energies, Journal Year: 2024, Volume and Issue: 17(3), P. 645 - 645

Published: Jan. 29, 2024

The Internet of Things (IoT) is introduced in systems with electrical machines, such as electric drive systems, wind energy generating and small special to remote monitor control the operation for data acquisition analysis. These can integrate equipment retrofit existing installations. At end loops there are always motors, or actuators, big ratings, rotating linear movements, nonelectrical, which must produce motion. This article analyses selected aspects research applications IoT-based conversion induction machines. Various study cases machines IoT technology described. With machine operators remotely parameters obtain accurate real-time feedback during fast changing duty cycle operation. Thus, creates multipurpose instruments paper offers a comprehensive analysis field technical details design, construction, experimental testing, prototyping, that useful engineering specialists sector drives systems.

Language: Английский

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Optimization of Water Quantity Allocation in Multi-Source Urban Water Supply Systems Using Graph Theory

Water, Journal Year: 2024, Volume and Issue: 17(1), P. 61 - 61

Published: Dec. 29, 2024

The optimization of urban multi-source water supply systems is essential for addressing the growing challenges allocation, cost management, and system resilience in modern cities. This study introduces a graph-theory-based model to analyze structural operational dynamics systems, incorporating constraints such as quality, pressure, connectivity. Using Lishui City case study, evaluates three allocation plans meet projected 2030 demand. Advanced algorithms, including Floyd’s shortest path algorithm GA-COA-SA hybrid algorithm, were employed address pipeline quality attenuation, nonlinear flow dynamics. Results indicate 1.4% improvement cost-effectiveness compared current strategy, highlighting model’s capability enhance efficiency. Among evaluated options, Plan 2 emerges most cost-effective solution, achieving capacity 4.5920 × 105 m3/d with lowest annual 5.7015 107 yuan, improve both efficiency resilience. prioritizes cost-efficiency tailored regional challenges, distinguishing itself from prior research that emphasized redundancy analysis. findings demonstrate potential graph-theoretic approaches combined advanced techniques decision-making sustainable management.

Language: Английский

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An insight into the Application of AI in maritime and Logistics toward Sustainable Transportation

JOIV International Journal on Informatics Visualization, Journal Year: 2024, Volume and Issue: 8(1), P. 158 - 158

Published: March 31, 2024

This review article looks at the developing field of artificial intelligence and machine learning in maritime marine environment management. The industry is increasingly interested applying advanced AI ML technologies to solve sustainability, efficiency, regulatory compliance issues. paper examines applications using a deep literature case study analysis. Modeling ship fuel consumption, which impacts operating expenses, top responsibility. demonstrates that approaches such as Random Forest Tweedie models can estimate use. Statistical analysis model beats regarding accuracy consistency. For training testing datasets, has high R2 values 0.9997 0.9926, indicating solid match. Low Root Mean Square Error (RMSE) average absolute relative deviation (AARD) suggest accurately reflects use variability. While still performing well, lower higher RMSE AARD values, suggesting reduced precision consumption prediction. These findings provide light on potential Advanced analytics enables decision-makers analyze patterns better, increase operational decrease environmental impact, thus improving sustainability.

Language: Английский

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Securing Sustainability Through Artificial Intelligence and Blue Economy

Practice, progress, and proficiency in sustainability, Journal Year: 2025, Volume and Issue: unknown, P. 37 - 82

Published: Jan. 17, 2025

The blue economy has gained considerable significance as a critical global catalyst for sustainable economic growth through the practical usage of marine resources. In this context, artificial intelligence researchers can substantially contribute to growing field knowledge. This work discusses new technology developments that facilitate establishment successful strategies digital transformation essential economy, where role in securing sustainability within maritime sector is explored. further need advanced environmental protection and related impacts. Moreover, study will explain various facets applications digitization sustainability. Furthermore, case studies on implementing technologies context be explained.

Language: Английский

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Digital Transformation in Logistics and Supply Chain Management Practices

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 27 - 48

Published: Feb. 25, 2025

In recent years, the rise of digital transformation in logistics and supply chain management (SCM) has become quintessential for organizations; accelerated all more with how COVID-19 induced an upheaval across global chains. The chapter discusses pandemic-induced disruptions were beyond what traditional models, largely manual processes, data silos could accommodate. need strong infrastructure is also apparent through use next-gen technologies including blockchain, AI/ML, intelligent automation. These provide real-time visibility, predictive analytics, improved coordination. This examines reasons why necessary, it affords, challenges that include legacy system trouble, issues, cybersecurity skills gaps. It finishes by offering some strategic guidelines successful implementation SCM.

Language: Английский

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Enhancing maritime education for digital sustainability

International Journal of Innovation Science, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

Purpose Digital sustainability involves the ability of industries and professionals to adapt rapidly changing technological landscapes. Digitalisation artificial intelligence (AI) are expected radically change maritime industry’s job landscape, especially with autonomous ships. International organisations currently do not formalise education deck officers need new formal modules. This study aims contribute this aspect by investigating learners’ experiences knowledge gaps in fundamentals of, as supported andragogy theory, topics such computer programming, cybersecurity statistics. Design/methodology/approach The research was carried out at Southampton Solent University, samples 105 students attending various MSc courses operations cadet courses. data collected through an online survey. two groups were compared analysed using a chi-square test. Findings results show that percentage previous training statistics, programming 37%, 13% 16%, respectively. officers’ same areas 06%, 09% 09%. used develop digital module focus on these topics. Originality/value paper highlights sustainability’s significance adapting Ship management companies higher institutions must urgently meet demands digitalisation AI industry. It necessity addressing current implementing educational modules ensure sustainable development skills among cadets.

Language: Английский

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