The Role of Artificial Intelligence in Aviation Construction Projects in the United Arab Emirates: Insights from Construction Professionals DOI Creative Commons

Mariam Abdalla Alketbi,

Fikri Dweiri, Doraid Dalalah

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 15(1), P. 110 - 110

Published: Dec. 27, 2024

The applications of Artificial Intelligence (AI) in the airport industry are significantly transforming operational efficiency, safety, and passenger experiences. This study investigates integration AI within aviation construction projects, with a focus on United Arab Emirates (UAE). While technologies such as facial recognition, IoT, biometric systems have advanced security operations, their use project management remains limited. A survey was conducted among 101 engineering professionals experts experience or involvement managing aviation-related projects. Participants, many whom had familiarity tools, provided insights into applicability areas planning, scheduling, safety monitoring. majority agreed that has potential to revolutionize processes, improving decision-making, efficiency. tools can predict delays, optimize workflows, enhance through real-time data analytics machine learning algorithms, reducing risks human error. Despite UAE’s leadership AI-driven advancements, its is still underdeveloped. research highlights for broader across entire lifecycle By adopting these areas, UAE airports could set new benchmarks cost effectiveness, sustainability, delivery, reinforcing region’s status leader technological innovation industry.

Language: Английский

A Framework for the Characterization of Aviation Construction Projects: The Case of UAE DOI Creative Commons

Mariam Abdalla Alketbi,

Doraid Dalalah, Fikri Dweiri

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(8), P. 2384 - 2384

Published: Aug. 1, 2024

This article contributes to the existing literature by modeling and automating learning process from previous aviation construction projects (ACPs) using artificial intelligence tools, where it will be easier characterize identify specifications of different aspects throughout their entire life cycle. An (AI) framework is proposed for categorization machine-learning (ML) methods with a focus on UAE as source data. Airport have been seen share good deal similar attributes, which should simplify decision-making regarding layouts, design, equipment, labor, budget, complexity, etc. However, gap in reality that huge scattered sources data, project specifications, characteristics, knowledge past are not utilized an automated way could navigation through better future decision-making. The utilization AI/ML tools expected useful here order reduce revisions design rework classifying elements managers need consider. planning, new can improved identifying attributes categorizing them according similarities, differences, complexities. Specifically speaking, hierarchical clustering neural networks integrated together form classification model. Upon implementing networks, was found demonstrate remarkable results; error minimal most cases. advantage such help decision-makers utilize best practice groups projects, were classified both models. With this classification, minimized, overhead costs may reduced, practices utilized.

Language: Английский

Citations

4
Artificial Intelligence in Open Innovation Project Management: A Systematic Literature Review on Technologies, Applications, and Integration Requirements DOI Creative Commons

Moonita Limiany Prasetyo,

Rosliyana Perangin-Angin,

Nada Martinovic

et al.

Journal of Open Innovation Technology Market and Complexity, Journal Year: 2024, Volume and Issue: unknown, P. 100445 - 100445

Published: Nov. 1, 2024

Language: Английский

Citations

4
Leveraging Artificial Intelligence in Project Management: A Systematic Review of Applications, Challenges, and Future Directions DOI Creative Commons

Dorothea S. Adamantiadou,

Loukas K. Tsironis

Computers, Journal Year: 2025, Volume and Issue: 14(2), P. 66 - 66

Published: Feb. 13, 2025

This article presents a systematic literature review exploring the integration of Artificial Intelligence (AI) methodologies in project management (PM). Key applications include cost estimation, duration forecasting, and risk assessment, which are critical factors for success. synthesizes findings from 97 peer-reviewed studies published between 2011 2024, using PRISMA methodology to ensure rigor transparency. AI techniques such as machine learning, deep hybrid models have exhibited their potential enhance PM across projects’ phases, including planning, execution, monitoring. Decision trees created represent application various stages tasks facilitate understanding real-world implementation. Among these that well categorization based on phases optimize integration. Despite advancements, there still gaps addressing dynamic environments, validating with data, expanding research into underexplored like closure.

Language: Английский

Citations

0
Advances and Challenges of Enhancing Operational Efficiency and Maintenance Protocols in the Construction Industry by Combining DT, AI, and Optimization DOI
Mateja Držečnik, Uroš Klanšek

Advances in business information systems and analytics book series, Journal Year: 2025, Volume and Issue: unknown, P. 225 - 284

Published: Feb. 14, 2025

The construction industry is undergoing a fundamental transformation with the introduction of advanced digital technologies such as twins (DT), artificial intelligence (AI) and optimization. These increase operational efficiency, improve maintenance, promote sustainability. DT enable real-time monitoring optimization projects, while AI analyzes large data sets for predictive maintenance resource Optimization algorithms support efficient planning, scheduling cost reduction. Despite benefits, challenges cybersecurity management remain. This chapter explores synergy between these technologies, their benefits successful implementation in provides recommendations future research.

Language: Английский

Citations

0
Applying Artificial Intelligence in Project Management: A Practitioner’s Perspective DOI Creative Commons

Greta Aleksandravičiūtė

Vilnius University Open Series, Journal Year: 2025, Volume and Issue: unknown, P. 6 - 17

Published: March 28, 2025

Organizations are deploying Artificial Intelligence (AI) solutions to manage project processes efficiently. Research shows that the potential of AI is growing. It predicted that, by 2030, 85% tasks will be performed using AI, thereby improving success rate 25% (Nieto-Rodríguez & Vargas, 2023).The aim this research paper analyze characteristics application in activities. To achieve goal, following objectives formulated: (1) applicability management, (2) identify benefits activities, and (3) investigate current situation integration management processes.To work, complex methods applied. For presentation theoretical part project, systematic comparative analysis foreign scientists’ works used. The exploratory carried out employing a questionnaire survey.The results study show applied planning implementation phases resource planning, scheduling tasks, risk management. allows controlling progress risks based on retrospective data. for more accurate prediction optimized decision making. face barriers terms such as lack staff skills, insufficiently prepared infrastructure, undefined legal ethical issues surrounding use which slows down scalability artificial intelligence.

Language: Английский

Citations

0
The race for AI skills as an obstacle course: Institutional challenges and low threshold suggestions DOI Creative Commons

Oliver Vettori,

Johanna Warm

Project Leadership and Society, Journal Year: 2025, Volume and Issue: unknown, P. 100183 - 100183

Published: April 1, 2025

Language: Английский

Citations

0
Reinforcing Organizational Resilience Through Ai: Evidence from Chinese Enterprises DOI
Li Li,

Huan He,

Lixin Li

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Project scheduling with resource considerations DOI
Ripon K. Chakrabortty

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Exploring Facilitators and Barriers to Managers’ Adoption of AI-Based Systems in Decision Making: A Systematic Review DOI Creative Commons
Silvia Marocco, Barbara Barbieri, Alessandra Talamo

et al.

AI, Journal Year: 2024, Volume and Issue: 5(4), P. 2538 - 2567

Published: Nov. 27, 2024

Introduction—Decision making (DM) is a fundamental responsibility for managers, with significant implications organizational performance and strategic direction. The increasing complexity of modern business environments, along the recognition human reasoning limitations related to cognitive emotional biases, has led heightened interest in harnessing emerging technologies like Artificial Intelligence (AI) enhance DM processes. However, notable disparity exists between potential AI its actual adoption within organizations, revealing skepticism practical challenges associated integrating into complex managerial scenarios. This systematic literature review aims address this gap by examining factors that influence managers’ DM. Methods—This study adhered PRISMA guidelines. Articles from 2010 2024 were selected Scopus database using specific keywords. Eligible studies included after rigorous screening quality assessment checklist tools. Results—From 202 articles screened, data synthesis 16 eligible revealed seven major interconnected acting as key facilitators or barriers integration organizations. These factors—Managers’ Perceptions AI, Ethical Factors, Psychological Individual Social Psychosocial Organizational External Technical Design Characteristics AI—were then organized analytical framework informed existing theoretical constructs. Discussion—This contribution provides valuable insights how managers perceive interact systems, well conditions necessary successful

Language: Английский

Citations

3
Approaches for Hybrid Scaling of Agile in the IT Industry: A Systematic Literature Review and Research Agenda DOI Creative Commons
Fernando Almeida,

Blaskovics Bálint

Information, Journal Year: 2024, Volume and Issue: 15(10), P. 592 - 592

Published: Sept. 28, 2024

Agile methodologies, initially designed for the project level, face challenges when applied at enterprise levels where complex projects and diverse stakeholders are involved. To meet this challenge, several large-scale agile methodologies have been proposed. However, these approaches not flexible enough or tailored to needs of organizations, projects, their teams. It is in context that hybrid emerged. This study aims conduct a systematic literature review trace evolution scaling characterize different implement it. starts by assessing 1509 studies through use PRISMA 2020 framework identifies 38 relevant field. The findings indicate majority from 2021 onwards qualitative supported case predominate, making it possible tailoring processes organizations. Moreover, implementation paradigm ambidextrous strategy, combination with traditional management continuous improvements. contributes insights into navigating complexities scaling, offering practical guidance organizations seeking optimize practices.

Language: Английский

Citations

1