A persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes is identified and a persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes is identified.
Abstract
Urban services increasingly depend on interconnected sensing, communication, computing, decision-support, and response functions, yet technical performance alone does not establish service effectiveness. This structured integrative review examines WSNs, WBANs, V2X systems, 5G-enabled edge–cloud infrastructures, and prospective 6G capabilities across health, mobility, environmental monitoring, energy, water, infrastructure safety, and climate resilience. A five-database search covering January 2018–March 2025 was supplemented by citation tracing and a documented gap-directed update with a final cutoff of 1 July 2026. The analytical corpus comprised 40 peer-reviewed studies, five deployment cases, and one scope-boundary case. An outcome-mediated perception–network–edge/cloud–decision–response framework enabled categorical comparison of heterogeneous evidence without pooling non-comparable measures. Attribution was classified as T1 (comparatively evaluated downstream outcome), T2 (technical or bounded operational outcome), or T3 (conceptual linkage): three studies were T1, 34 T2, and three T3. Ten studies supported target-level SDG alignment, whereas none reached indicator-level correspondence. Evidence remained concentrated at communication, processing, decision-support, and bounded operational endpoints, with limited assessment of response availability and disruption–recovery conditions. Among the deployment cases, only SFpark supported T1 interpretation. These findings characterize the selected corpus and identify a persistent gap between technical performance and comparative, longitudinal, and distributionally assessed urban-service outcomes.
The proposed framework suggests that the adoption of IT-based DSS solutions can generate several benefits for a wide range of stakeholders involved in the management and utilization of highway infrastructures, including local communities and urban authorities.
Roberto Viviani, F. Parola, Antonella Ferri et al.· The TQM Journal· 0 citations
A structured, literature-based mapping review of ITS applications from a standards-oriented perspective and proposes a five-dimension standards-facing reporting checklist addressing interoperability, data lifecycle and governance, security and privacy, operational readiness, and standards-facing evidence is presented.
Francisco Cachumba, P. B. Bautista, N. O. Orozco Garzón et al.· Smart Cities· 0 citations
This paper presents a multi-dimensional robustness evaluation framework for ultra-dense Internet of Things (UD-IoT) networks in smart city environments. The framework addresses the need to assess robustness beyond isolated indicators such as latency, throughput, packet loss, or availability by integrating operational c...
Viktor Stoynov, D. Mihaylova· Telecom· 0 citations
The convergence of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) has strengthened smart greenhouse management by enabling continuous environmental monitoring, automated control, and more informed use of agricultural resources. This review examines and synthesises research on IoT- and WSN-enabled gree...
J. Popoola, B. Iyaomolere, K. Akingbade et al.· Saudi Journal of Engineering...· 0 citations
Urban centers in tropical developing nations face severe air pollution crises, yet a critical policy inertia gap persists between real-time sensor data acquisition and dynamic municipal enforcement. This study aims to develop and evalu- ate the Smart Air Quality Governance (SAQG) framework, an automated, artificial int...
Luiz Rubio, Muhammad Bukhori Dalimunthe, Fazli Rachman et al.· Advanced Robotics· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.