Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.746123
Title: Data as infrastructure for smart cities
Author: Dos Santos Romualdo Suzuki, L. C.
ISNI:       0000 0004 7229 9881
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Abstract:
The systems that operate the infrastructure of cities have evolved in a fragmented fashion across several generations of technology, causing city utilities and services to operate sub-optimally and limiting the creation of new value-added services. The integration of cross-domain city data offers a new wave of opportunities to mitigate some of these impacts and enables city systems to draw effectively on interoperable data that will be used to deliver smarter cities. Despite the considerable potential of city data, current smart cities initiatives have mainly addressed the problem of data management from a technology perspective, have treated it as a single and disjoint ICT development project, and have disregarded stakeholders and data needs. As a consequence, such initiatives are susceptible to failure from inadequate stakeholder input, requirements neglecting, and information fragmentation and overload. This thesis proposes a systematic business-model-driven framework, named SMARTify, to guide the design of large and highly interconnected data infrastructures which are provided and supported by multiple stakeholders. The framework is used to model, elicit and reason about the requirements of the service, technology, organization, value, and governance aspects of smart cities. The requirements serve as an input to a closed-loop supply chain model, which is designed and managed to explicitly consider the activities and processes that enables the stakeholders of smart cities to efficiently leverage their collective knowledge. We demonstrate how our approach can be used to design data infrastructures by examining the degree to which the results of the SMARTify approach handles the holistic design of a data infrastructure and informs the decision making process. To establish the effectiveness of SMARTify to improve the quality of data infrastructures design, we have validated the framework against real-world case studies in different domains using a combination of both real systems and software simulation.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.746123  DOI: Not available
Share: