Utilizing geographic information systems in pavement maintenance applications: Baghdad university as case study

Hashim, Mahmood S.; Abdulhadi, Ahmed M.; Taher, Muntadher J.

doi:10.21533/pen.v9i1.1788

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is an essential academic exercise since it draws attention to numerous applications of AI in other allied engineering fields besides highlighting prospects for trans-discipline innovations (Kraus and Drass, 2021). The University of Baghdad was chosen as the focus for an in-depth look at the use of GIS for the maintenance of pavements, within the scope of a comprehensive research project carried out by Hashim et al (2021). Their work consisted in developing a special Pavement Maintenance Management System aimed at the University road lanes and parking spaces control.…”

Section: Case Studies Of Ai Integration In Pavement Engineeringmentioning

confidence: 99%

Advancing Infrastructure in Developing Nations: A Synthesis of Ai Integration Strategies for Smart Pavement Engineering

Eche Samuel Okem,

Emmanuel Adikwu Ukpoju,

Abayomi B. David

et al. 2023

Eng. sci. technol. j.

View full text Add to dashboard Cite

This research focuses on the transformational potential of artificial intelligence (AI) towards the field of pavement engineering, particularly considering underdeveloped nations. This exploratory study aims to shed light on the complex effects AI has on pavement engineering and management processes, as well as various strategic, policy, and ethical perspectives underpinning its implementation. By using a systematic process, the study builds on information from academic papers, case studies, and industry research to create more enriching knowledge on this topic. Through a robust study, it is shown that AI helps improve the composition of pavement materials building and maintenance routines. Such a study shows that AI can improve the level of economic benefits in the pavement infrastructure of underdeveloped countries. These key findings emphasize how AI reduces the costs of design, predictive maintenance models, and sustainable materials use. In addition, the study traverses through the difficult routes of policy and institutional frameworks, stating that the policies ought to be responsive while collaboration is required in promoting AI uptake. The discussion integrates ethics and the environment very carefully, as required by sustainability and equity. Lastly, the research presents an excellent argument for AI as an agent for constructing new and eco-friendly transportation infrastructure in poor countries. These countries’ recommended policies should be flexible, as they promote capacity building and ethics in AI with regard to infrastructure development as part of their developmental paths, which are simultaneously technical and social. Keywords: Artificial Intelligence, Pavement Engineering, Developing Nations, Sustainable Infrastructure, Ethical AI, Transportation

show abstract

Section: Case Studies Of Ai Integration In Pavement Engineeringmentioning

confidence: 99%