Enhancing urban resilience via a real-time decision support system for smart cities

Ottenburger, Sadeeb Simon; Airaksinen, Miimu; Pinto-Seppä, Isabel; Raskob, W.

doi:10.1109/ice.2017.8279970

Cited by 4 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many of those arguing that the interrelations between resilience and smartness lead to 2019)), or propose specific data-driven solutions and digital tools to improve the resilience of the city or specific urban systems (Alazawi et al 2014;Bashir 2020;Baumgärtner et al 2019;Bellini et al 2016;Ottenburger et al 2018;Sitinjak et al 2018;Tsinganos et al 2017;Zhu et al 2019). However, the arguments put forward by these articles are typically justified through simulations rather than real-world implementation and impact measurement (for exceptions see Sitinjak et al (2018), Zhu et al (2019)).…”

Section: 2mentioning

confidence: 99%

On the relation between ‘resilience’ and ‘smartness’: A critical review

Cañavera-Herrera

Tang

Nochta

et al. 2022

International Journal of Disaster Risk Reduction

View full text Add to dashboard Cite

Section: 2mentioning

confidence: 99%

On the relation between ‘resilience’ and ‘smartness’: A critical review

Cañavera-Herrera

Tang

Nochta

et al. 2022

International Journal of Disaster Risk Reduction

View full text Add to dashboard Cite

“…In this context, several conventional cities that strive to transform into smart and resilient ones have recognized the important role of urban data and developed infrastructure for their collection and utilization [44]. However, the efficient use of urban data raises new issues related to: (i) urban data sources, (ii) data ownership and (iii) data storage and processing [44][45][46].…”

Section: Cities As Data-driven Ecosystems: Urban Data Exploitation and Crowdsourcingmentioning

confidence: 99%

“…Regarding the methods of urban data exploitation, it is common to store it in databases and then retrieve and process it and visualize the results of its analysis. This timeconsuming sequence is a brake on instant data visualization and real-time decisionmaking [4,45,46]. Data interoperability and integration constitutes one of the most difficult problems facing cities, as pointed out by [65].…”

Section: Cities As Data-driven Ecosystems: Urban Data Exploitation and Crowdsourcingmentioning

confidence: 99%

“…In addition, the authors of [65] proposed a conceptual framework that aims to integrate data across the various systems of the city, urban data analytics and creation of value-added services using edge computing, cloud computing, data analytics and semantic integration. Of particular interest is the work of [46], which introduced a framework for a real-time decision support system for response during a crisis or disruption of critical infrastructure based on in-memory database technologies and urban data sources. Specifically, data that include decisions and strategies concerning urban resilience are better to be collected from the database according to current urban status and the type of disruption.…”

Section: Cities As Data-driven Ecosystems: Urban Data Exploitation and Crowdsourcingmentioning

confidence: 99%

See 1 more Smart Citation

Urban Data Dynamics: A Systematic Benchmarking Framework to Integrate Crowdsourcing and Smart Cities’ Standardization

et al. 2021

View full text Add to dashboard Cite

Urbanization and knowledge economy have highly marked the new millennium. Urbanization brings new challenges which can be addressed by the knowledge economy, which opens up scientific and technical innovation opportunities. The enhancement of cities’ intelligence has heavily impacted city transformation and sustainable decision-making based on urban data knowledge extraction. This work is motivated by the strong demand for robust standardization efforts to steer and measure city performance and dynamics, given the growing tendency of conventional cities’ transformation into smart and resilient ones. This paper revises the earlier so-called “cityDNA” framework, which was designed to detect the interrelations between the six smart city dimensions, such that a city’s profile and capacities are recognized in a systematic manner. The updated framework implements the widely accepted smart city (ISO 37120:2018) standard, along with an adaptive Web service, which processes urban data and visualizes the city’s profile to facilitate decision-making. The proposed framework offers a solid benchmarking service, at which the value of crowdsourced data is exploited for the production of urban knowledge and city transformation empowerment. The proposed benchmarking approach is tested and validated through relevant case studies and a proof-of-concept scenario, in which open data and crowdsourced data are exploited. The outcomes revealed that cities should intensify their KPI-driven data production and exploitation along with a set of solid standards for cities to enable cities with customizable scenarios enriched with indicators that reflect each city’s vibrancy.

show abstract

“…Many public water utilities undertake the supervision, control and data management of their network through a SCADA (Supervisory Control And Data Acquisition) system [34,35]. SCADA systems typically use the collection of historical sensor readings to centrally control spatially distributed assets [36].…”

Section: Cloud Computing and Scadamentioning

confidence: 99%

Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

et al. 2020

View full text Add to dashboard Cite

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.

show abstract

Enhancing urban resilience via a real-time decision support system for smart cities

Cited by 4 publications

References 14 publications

On the relation between ‘resilience’ and ‘smartness’: A critical review

On the relation between ‘resilience’ and ‘smartness’: A critical review

Urban Data Dynamics: A Systematic Benchmarking Framework to Integrate Crowdsourcing and Smart Cities’ Standardization

Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

Contact Info

Product

Resources

About