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Open research questions in Smart Cities and Technologies

89 unresolved questions extracted from the limitations and future-work sections of 1,248 Smart Cities and Technologies papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • First, the study could be replicated with larger and more demographically balanced expert panels, including public-sector and civil- society representatives, to test the robustness of the influence structure. Internet of Things in smart cities: Comprehensive review, open issues and challenges.

    SOCIO-TECHNOLOGICAL PATHWAYS TO SUSTAINABLE SMART CITIES: A DEMATEL ANALYSIS OF IoT CHALLENGES AND STRATEGIC RESPONSES · 2026 · DOI

  • Digital trade, defined as cross-border commerce conducted via digital platforms, has wide-reaching implications for regional development. At the macro level, it promotes manufacturing upgrading (Tang & Lan, 2024), boosts competitiveness through foreign direct investment and innovation (Ma & Kang, 2025), and enhances green total factor productivity across cities (Dai et al., 2025). Ji et al. (2023) found that digital trade also contributes to carbon emission reduction via industrial transformation and technological upgrading. At the micro level, digital trade reduces market entry barriers, stimulates entrepreneurial activity, and increases employment, especially in digitally mature cities (Zhao et al., 2025). These economic benefits may indirectly affect housing markets by shifting income distribution, changing population flows, and modifying the spatial distribution of demand for housing. 3. Digital trade and the housing market: An emerging linkage Although still nascent, recent research has begun to explore the interaction between digital transformation and urban real estate dynamics. Zhang et al. (2024) found that a 0.1 unit increase in a city’s digital economy index corresponds to a nearly 10% increase in housing costs, particularly in cities with resource mismatches. Their findings suggest that digital infrastructure and digital policy initiatives, such as the “Broadband China” strategy, may inadvertently raise house prices by concentrating on economic opportunities. Wang et al. (2024b) explored how digital industrial platforms reshaped housing construction through enhanced efficiency and customisation. Meanwhile, crossborder trade flows and the internationalisation of digital services have been found to alter income patterns and employment geographies (Jiang et al., 2022; Zhao & Gao, 2024), adding further complexity to housing market outcomes. Despite these insights, the literature still lacks an integrated framework for understanding how digital trade directly and indirectly influences urban housing systems. 4. AI-based approaches to real estate research: Enhancing modelling and insight AI has revolutionised real estate valuation and prediction by improving accuracy and capturing non-linear patterns in housing data. Studies by Abidoye et al. (2019), Njo et al. (2025), and Alzain et al. (2022) showed that artificial neural networks (ANNs) outperform traditional econometric models in forecasting house prices across varied geographic contexts.

    Is digital trade affecting city house prices? An artificial intelligence perspective · 2026 · DOI

  • The findings reveal that while both countries have transposed relevant EU directives, implementation remains fragmented due to decentralised competences, variable municipal capacities and limited data governance.

    Governing the circular–digital transition: Comparative legal‐institutional analysis of smart waste strategies in Spain and Portugal · 2026 · DOI

  • Since not much is known on the factors predicting the interest of individuals holding key positions, the present study tested how representations of Smart cities and variables from the Theory of Planned Behaviour were related to their intention to implement a Smart City programme in their municipality.

    Perceptions of and interest for Smart Cities across Swiss French municipalities · 2026 · DOI

  • The study In this article, we addressed the problem of user–group matching in annotation-based recommender systems within smart city environments, leveraging the MADCOW framework. is motivated by improve recommendation quality in collaborative annotation systems, where traditional semantic matching approaches fail to capture the dynamic nature of user participation and group evolution. This highlights the importance of considering both content-based and behavioral factors in recommendation design. the need to indicators, Indeed, our experimental results showed that traditional ontology-based approaches relying on semantic similarity measures such as CMM and DC are insufficient to capture the full complexity of user and group behavior.

    Ontology-based annotation and fuzzy recommendation for community formation in smart city knowledge platforms · 2026 · DOI

  • The following suggestions are put forth in light of the research's findings: • Create national plans for incorporating AI into urban planning. • Make investments in digital infrastructure, such as IoT systems and data platforms. • Encourage open data projects to aid in the development of AI and transparency. • Increase local AI capabilities through training and education initiatives. • Promote cooperation between the public, business, and academic sectors.

    Artificial Intelligence-Driven Smart Cities: A Framework for Addressing Contemporary Urban Challenges (Case Study: Baghdad) · 2026 · DOI

  • the supplementary features of the user. The author presents a detailed note on security and privacy threats in smart education platforms. Eskhita et al. [33] compare Dubai and Barcelona city according to the security and privacy of the user data collected by various sensors in smart city services. The results show that in Barcelona smart city services, the privacy of the user data is preserved, and it is not shared with any service providers. The author recommends the same best practices to be followed in Dubai smart city projects. Kashif et al. [31] provided an overview of the definition of a smart grid and discussed various threats associated with smart grid services like on-off, bad-mouthing, and DoS. The author experimented using ma-chine learning algorithms to evaluate the trustworthiness to secure the data in the smart grid service. Harper et al. [34] discussed the data collected by various sensors in the smart home might lead to privacy concerns. The author also urged that authorities adopt necessary regulations, standards, and policies to overcome the privacy concern in a smart home. Muhammad et al. [41] explained the layer-wise security attacks and their preventive techniques in smart healthcare services and also presented the privacy issues of patient data. The author ex-plores the attacks in the following layers: the network layer (DoS, DDoS, layer Wormhole attack) and (repudiation and non-repudiation attack, malicious code injection). However, the author does not discuss the applica-tion International Research Journal on Advanced Engineering Hub (IRJAEH) 2080 International Research Journal on Advanced Engineering Hub (IRJAEH) e ISSN: 2584-2137 Vol. 04 Issue: 04 April 2026 Page No: 2079-2098 https://irjaeh.com https://doi.org/10.47392/IRJAEH.2026.0278 the standardization in health care smart city services. The authors of [24], [23], [35], and [36] describe various international standards like ITU-T and IEEE that covers traditional standards and security. The major drawback of these studies is very few standards were discussed. Chun et al. [12] aim to clarify the need for IEEE international standards in smart city services. The author points out that implementing the standards in smart cities will lead to sustainable development. Dapeng et al. [21] conceptualized standardization in China's smart city projects, industry best practices, and the indi-cators for the smart city were discussed. The authors of [13], [14], [16], [19], and [20] analyzed various secu-rity threats in smart services like smart grids, smart hospitals, smart homes, and a few international standards such as IEEE 21451.001 (way of transmitting the data to the server in a secure manner), IEC 62351 (security in smart grid service), ISO/IEEE 11073 (international standard for healthcare patient data) and ISO/IEEE 802.15.4 (standard for the transmission of data in a trusted manner). This paper investigates the security, pri-vacy, and trust standards in various international standards issued by ISO, IETF, and ITU-T IEEE.

    Exploration of International IoT Standards for Smart Cities Security, Privacy, and Trust Management · 2026 · DOI

  • The paper notes that small cities in emerging countries must adopt smart city policies but does not identify specific adaptations needed for IoT and digital infrastructure deployment in resource-constrained urban environments or provide scalability pathways from large smart city implementations to smaller municipalities.

    Assessment of Smart Cities Challenges and Future Consequences · 2026 · DOI

  • The paper discusses smart city safety solutions including sensors, video analytics, and cross-department coordination but does not establish validated protocols for incident response coordination across multiple municipal departments or specify data privacy and security requirements for real-time safety sensor networks in smart cities.

    Assessment of Smart Cities Challenges and Future Consequences · 2026 · DOI

  • The paper mentions that identifying the responsible community and understanding community characteristics is essential for smart city development, but provides no empirical framework, assessment metrics, or validated community profiling methodologies to determine stakeholder involvement requirements across different smart city contexts.

    Assessment of Smart Cities Challenges and Future Consequences · 2026 · DOI

  • Future research should examine co-creation strategies, digital democracy platforms, and participatory governance models that let people actively participate in urban innovation and decision-making. However, further investigation is needed to comprehend the moral ramifications of AI-based governance systems, including concerns about algorithmic transparency, data security, and public accountability.

    Artificial Intelligence-Powered Smart City Transformation: A Framework and Comparative Case Study Analysis · 2026 · DOI

  • Cross-city comparative studies of DT implementation outcomes across Indonesia's 100 Smart Cities have not been conducted; longitudinal tracking research is needed to compare deployment timelines, technology stack choices, adoption barriers, and performance metrics across cities with varying economic resources and governance maturity.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • Data governance and ethical frameworks for digital twin systems operating under public-private partnership (PPP) models remain undefined in Indonesia; research must establish concrete data ownership protocols, privacy regulations, and cybersecurity standards for occupancy patterns, infrastructure usage, and personal movement data collection.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • Indonesia faces a critical shortage of professionals with expertise in BIM, AI, IoT, and urban informatics, but no baseline skills assessment or competency framework exists; workforce development research must map current capability gaps, identify optimal training pathways, and evaluate domestic versus international expert dependencies.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • The return-on-investment (ROI) calculations for digital twin systems in Indonesian contexts remain unquantified; longitudinal case studies tracking actual energy savings, maintenance cost reductions, and operational efficiency gains across completed DT implementations are required to establish credible ROI models.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • Indonesia lacks national standards and regulatory frameworks for digital twin adoption across municipalities; future research must develop and pilot interoperability standards, benchmarking metrics, and conformance testing protocols specific to Indonesian smart city governance structures and building typologies.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • The paper identifies inadequate IoT infrastructure as a foundational barrier but does not specify which Indonesian urban regions currently lack real-time data acquisition systems, sensor coverage density thresholds, or network latency requirements; empirical IoT infrastructure audits across the 100 Smart Cities are needed.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • Data analytics and visualization dashboards for digital twin systems lack empirical validation regarding usability and stakeholder-specific design; no comparative studies have assessed which visualization approaches (e.g., 2D vs. 3D interfaces, real-time vs. aggregated metrics) optimize decision-making for diverse Indonesian urban stakeholder groups.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • BIM implementation in Indonesia's smart cities faces unresolved integration challenges between Building Information Modelling platforms and real-time IoT data streams; the specific protocols, data synchronization methods, and architectural approaches for seamless BIM-IoT coupling in Indonesian urban contexts remain unexplored.

    Indonesia’s Transition Toward Digital Twin in Smart Cities Development: An Integrative Review · 2026 · DOI

  • The Generative Adversarial Network (GAN) approach is proposed as conceptually similar to the integrated dual-model framework (pitting supply against demand models), but no concrete application of GANs to housing demand-supply equilibration in city planning has been developed or validated in the paper.

    The evolution of AI in city planning · 2026 · DOI

  • Large language models (LLMs) and generative AI systems applied to urban planning queries lack established testing frameworks for validating the efficacy and accuracy of generated answers; the paper notes there are no agreed methods to test LLM outputs in planning contexts, unlike traditional mathematical models where validity can be demonstrated.

    The evolution of AI in city planning · 2026 · DOI

  • The paper identifies that minimum dataset size for deep learning applications in planning is poorly understood beyond rough estimates (approximately one billion parameter values), with guidance currently dependent on problem-specific and domain knowledge; empirical validation of optimal dataset sizes and composition for city planning AI models remains absent.

    The evolution of AI in city planning · 2026 · DOI

  • The integration of multiple model types (traditional spatial interaction models and AI/machine learning perceptron models) for city planning requires establishing standardized protocols for linking these disparate systems; currently there is no agreed methodology for interfacing demand models based on employment-population trips with supply models based on land suitability scores across different data resolutions and temporal scales.

    The evolution of AI in city planning · 2026 · DOI

  • The paper demonstrates the integrated LUTI and Perceptron Machine Learning housing model for Oxfordshire but does not show the complete iterative process to equilibrium convergence; the specific convergence criteria, number of iterations required, and sensitivity of demand-supply matching to initial parameter values need explicit documentation and validation.

    The evolution of AI in city planning · 2026 · DOI

  • The QUANT model linking housing supply through land suitability models with economic-demographic demand predictions has only been demonstrated for Britain; the transferability and validation of this integrated LUTI-PML framework to other geographic regions with different spatial interaction patterns, travel modes, and employment-population distributions remains unexplored.

    The evolution of AI in city planning · 2026 · DOI

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89 open questions have been extracted from the limitations and future-work passages of 1,248 Smart Cities and Technologies papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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