Artificial Intelligence (AI) Integration in Urban Decision-Making Processes: Convergence and Divergence with the Multi-Criteria Analysis (MCA)

The dynamics underpinning the urban landscape change are primarily driven by social, economic, and environmental issues. Owing to the population’s fluctuating needs, a new and dual perspective of urban space emerges. The Artificial Intelligence (AI) of a territory, or the system of technical diligence associated with the anthropocentric world, makes sense in the context of this temporal mismatch between territorial processes and utilitarian apparatus. This creates cerebral connections between several concurrent decision-making systems, leading to numerous perspectives of the same urban environment, often filtered by the people whose interests direct the information flow till the transformability. In contrast to the conventional methodologies of decision analysis, which are employed to facilitate convenient judgments between alternative options, innovative Artificial Intelligence tools are gaining traction as a means of more effectively evaluating and selecting fast-track solutions. The study’s goal is to investigate the cross-functional relationships between Artificial Intelligence (AI) and current decision-making support systems, which are increasingly being used to interpret urban growth and development from a multi-dimensional perspective, such as a multi-criteria one. Individuals in charge of administering and governing a territory will gain from artificial intelligence techniques because they will be able to test resilience and responsibility in decision-making circumstances while also responding fast and spontaneously to community requirements. The study evaluates current grading techniques and recommends areas for future upgrades via the lens of the potentials afforded by AI technology to the establishment of digitization pathways for technological advancements in the urban valuation.

Authors

Institutions

Publication Details

Journal
Information
Published
2024-10-31
DOI
https://doi.org/10.3390/info15110678
Citations
9
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
2.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence (AI) Integration in Urban Decision-Making Processes: Convergence and Divergence with the Multi-Criteria Analysis (MCA)

Alejandro Segura de la Cal, Francesco Sica, Maria Rosaria Guarini
9 citations
Information
Traffic Prediction and Management Techniques
2.39
article

Artificial Intelligence (AI) Integration in Urban Decision-Making Processes: Convergence and Divergence with the Multi-Criteria Analysis (MCA)

Alejandro Segura de la Cal, Francesco Sica, Maria Rosaria Guarini
article en
9 citations

Abstract

The dynamics underpinning the urban landscape change are primarily driven by social, economic, and environmental issues. Owing to the population’s fluctuating needs, a new and dual perspective of urban space emerges. The Artificial Intelligence (AI) of a territory, or the system of technical diligence associated with the anthropocentric world, makes sense in the context of this temporal mismatch between territorial processes and utilitarian apparatus. This creates cerebral connections between several concurrent decision-making systems, leading to numerous perspectives of the same urban environment, often filtered by the people whose interests direct the information flow till the transformability. In contrast to the conventional methodologies of decision analysis, which are employed to facilitate convenient judgments between alternative options, innovative Artificial Intelligence tools are gaining traction as a means of more effectively evaluating and selecting fast-track solutions. The study’s goal is to investigate the cross-functional relationships between Artificial Intelligence (AI) and current decision-making support systems, which are increasingly being used to interpret urban growth and development from a multi-dimensional perspective, such as a multi-criteria one. Individuals in charge of administering and governing a territory will gain from artificial intelligence techniques because they will be able to test resilience and responsibility in decision-making circumstances while also responding fast and spontaneously to community requirements. The study evaluates current grading techniques and recommends areas for future upgrades via the lens of the potentials afforded by AI technology to the establishment of digitization pathways for technological advancements in the urban valuation.

InformationVol. 15(11)
Sapienza University of Rome (IT), Universidad Politécnica de Madrid (ES)
Sustainable cities and communities
Openalex Percentile: Top 12%
Traffic Prediction and Management Techniques
2.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.