Leveraging AI Models for Automated Pattern Detection in Citizen Participation Data
DOI:
https://doi.org/10.59490/dgo.2025.1068Keywords:
Citizen participation, Artificial Intelligence models, Data analysis, Pattern detection, Semantic, spatial and temporal analysisAbstract
Citizen Participation (CP) is essential for urban projects, traditionally done through face-to-face meetings. Information Technologies (IT) have introduced electronic participation (e- Participation), enhancing inclusivity and engagement. CPPs generate valuable data for decisionmaking, but processing large volumes of unstructured data is challenging. Traditional methods are inefficient. AI algorithms can improve data analysis, automate classification, detect patterns, and extract relevant information, reducing the workload for decision-makers. This research explores how AI can detect and classify patterns in CPP data, contributing to best practices in applying AI to government operations.
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Copyright (c) 2025 Amal Marzouki, Boutheyna Nouri, Sehl Mellouli
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