Subtopic Deep Dive
Smart City Decision Support Systems
Research Guide
What is Smart City Decision Support Systems?
Smart City Decision Support Systems are AI-driven platforms integrating multi-source urban data for optimized decision-making in energy management, environmental sustainability, and crisis response within smart cities.
These systems employ optimization algorithms and human-in-the-loop interfaces to process real-time data for evacuation planning and resource distribution (Choi and Song, 2022). Research emphasizes transitioning urban plans toward sustainability amid environmental threats, with 33 citations for Choi and Song's diagnostic framework. Over 10 recent papers analyze policies, monitoring, and bibliometrics in this domain.
Why It Matters
Smart City Decision Support Systems enable municipalities to manage environmental risks like heat waves and poor indoor air quality, as shown in gap analyses of adaptation policies (Kim et al., 2023). They support energy retrofitting critical success factors for residential buildings, reducing consumption (Adegoke et al., 2024). Real-time monitoring enhances indoor resilience during extreme events (Azoulay Kochavi et al., 2025), while bibliometric studies guide thermal comfort strategies (Ahsissene et al., 2024). These applications boost crisis preparedness and sustainability in urban energy systems.
Key Research Challenges
Policy Implementation Gaps
Mismatch between heat wave adaptation policies and actual effects hinders effective DSS deployment (Kim et al., 2023). Municipalities struggle to align industry types with policy levels using cluster analysis. This gap delays smart city transitions (Choi and Song, 2022).
Real-Time Data Integration
Fusing multi-source environmental parameters for monitoring remains challenging amid extreme events (Azoulay Kochavi et al., 2025). Systems must handle poor IAQ and behavioral changes in schools. Scalability limits DSS reliability in dynamic urban settings.
Energy Efficiency Measurement
Post-occupancy evaluation of space energy intensity lacks robust benchmarking in green buildings (Yaman et al., 2021). Deficiencies in tools like GBI-IT complicate retrofitting success factors (Adegoke et al., 2024). Accurate metrics are essential for sustainable DSS.
Essential Papers
Direction for a Transition toward Smart Sustainable Cities based on the Diagnosis of Smart City Plans
Hee-Sun Choi, Seulki Song · 2022 · Smart Cities · 33 citations
Achieving urban sustainability through smart cities is necessary to manage urban environmental problems that threaten human survival. Smart city policy emphasizes the environmental aspects of urban...
Climate Change Education and Curriculum Revision
Janssen Edelweiss Teixeira, Elizabeth Crawford · 2022 · World Bank, Washington, DC eBooks · 9 citations
No AccessOther papers1 Jan 2022Climate Change Education and Curriculum RevisionAuthors/Editors: Janssen Edelweiss Teixeira, Elizabeth CrawfordJanssen Edelweiss Teixeira, Elizabeth Crawfordhttps://d...
Academic Topics Related to Household Energy Consumption Using the Future Sign Detection Technique
Minkyu Kim, Chankook Park · 2021 · Energies · 7 citations
With the emergence of new technologies and policies to transition to clean energy, the household energy consumption sector is also changing. In response to policy, environmental, and technical chan...
A Study on Threat Modeling in Smart Greenhouses
So-Hyeon Cho, Dongseok Kang, Min-Song Kang et al. · 2020 · Journal of Information Security and Cybercrimes Research · 4 citations
In the era of agriculture 4.0, cutting-edge technologies including Information and communication technology (ICT) is being introduced into traditional agriculture. As farm intelligence emerges as a...
Real-Time Monitoring of Environmental Parameters in Schools to Improve Indoor Resilience Under Extreme Events
Salit Azoulay Kochavi, Oz Kira, Erez Gal · 2025 · Smart Cities · 4 citations
Climatic changes lead to many extreme weather events throughout the globe. These extreme weather events influence our behavior, exposing us to different environmental conditions, such as poor indoo...
A Bibliometric Analysis and Scoping Review of the Critical Success Factors for Residential Building Energy Retrofitting
Ayodele Samuel Adegoke, Rotimi Boluwatife Abidoye, Riza Yosia Sunindijo · 2024 · Buildings · 4 citations
Retrofitting existing residential buildings presents a feasible approach to improving energy efficiency. Therefore, recognising the critical success factors (CSFs) for residential building energy r...
Post Occupancy Evaluation of Space Energy Intensity on Green Building Index Energy Efficiency (EE) Criteria
Rostam Yaman, Jamalunlaili Abdullah, Hamimah Adnan et al. · 2021 · Engineering Journal · 4 citations
Green interior tool sustainable benchmarking system in Malaysian is relatively new.Despite of the launch of Malaysian Green Building Councils very own Green Interior Tools (GBI-IT) and implementati...
Reading Guide
Foundational Papers
No pre-2015 foundational papers available; start with highest-cited recent work by Choi and Song (2022) for core diagnostic framework on smart city plans.
Recent Advances
Prioritize Azoulay Kochavi et al. (2025) for real-time monitoring advances, Adegoke et al. (2024) for retrofitting bibliometrics, and Ahsissene et al. (2024) for thermal comfort analysis.
Core Methods
Policy diagnosis via plan evaluation (Choi and Song, 2022), cluster analysis for heat adaptation (Kim et al., 2023), bibliometrics for success factors (Adegoke et al., 2024), real-time IAQ sensing (Azoulay Kochavi et al., 2025).
How PapersFlow Helps You Research Smart City Decision Support Systems
Discover & Search
Research Agent uses searchPapers and exaSearch to find key works like 'Direction for a Transition toward Smart Sustainable Cities' by Choi and Song (2022), then citationGraph reveals policy diagnosis clusters and findSimilarPapers uncovers related heat wave analyses (Kim et al., 2023).
Analyze & Verify
Analysis Agent applies readPaperContent to extract optimization methods from Choi and Song (2022), verifies claims via verifyResponse (CoVe) against 250M+ OpenAlex papers, and runs PythonAnalysis with pandas for bibliometric trends in Adegoke et al. (2024), graded by GRADE for evidence strength.
Synthesize & Write
Synthesis Agent detects gaps in policy transitions (Choi and Song, 2022 vs. Kim et al., 2023), flags contradictions in energy retrofitting factors; Writing Agent uses latexEditText, latexSyncCitations for manuscripts, latexCompile for reports, and exportMermaid for DSS workflow diagrams.
Use Cases
"Analyze citation networks for smart city sustainability policies."
Research Agent → citationGraph on Choi and Song (2022) → Analysis Agent → runPythonAnalysis (NetworkX for centrality) → network visualization export.
"Draft LaTeX report on heat wave policy gaps."
Synthesis Agent → gap detection (Kim et al., 2023) → Writing Agent → latexEditText + latexSyncCitations + latexCompile → formatted PDF report.
"Find GitHub repos for real-time environmental monitoring code."
Code Discovery → paperExtractUrls (Azoulay Kochavi et al., 2025) → paperFindGithubRepo → githubRepoInspect → reusable monitoring scripts.
Automated Workflows
Deep Research workflow conducts systematic reviews of 50+ smart city papers, chaining searchPapers → citationGraph → structured sustainability reports. DeepScan applies 7-step analysis with CoVe checkpoints to verify policy gaps (Kim et al., 2023). Theorizer generates decision models from energy retrofitting literature (Adegoke et al., 2024).
Frequently Asked Questions
What defines Smart City Decision Support Systems?
AI-driven platforms integrating multi-source data for urban energy and environmental decisions, focusing on sustainability transitions (Choi and Song, 2022).
What methods are used in this subtopic?
Diagnostic frameworks for smart city plans (Choi and Song, 2022), bibliometric analysis for retrofitting (Adegoke et al., 2024), and real-time monitoring (Azoulay Kochavi et al., 2025).
What are key papers?
Choi and Song (2022, 33 citations) on smart sustainable transitions; Adegoke et al. (2024) on energy retrofitting CSFs; Kim et al. (2023) on heat wave policy gaps.
What open problems exist?
Bridging policy-effect gaps (Kim et al., 2023), scalable data integration for extremes (Azoulay Kochavi et al., 2025), and post-occupancy energy metrics (Yaman et al., 2021).
Research Energy and Environmental Systems with AI
PapersFlow provides specialized AI tools for Social Sciences researchers. Here are the most relevant for this topic:
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Field-specific workflows, example queries, and use cases.
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Part of the Energy and Environmental Systems Research Guide