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dc.contributor.advisorNamboodiri, Vinod
dc.contributor.authorDas, Uddipan
dc.date.accessioned2020-07-14T13:37:22Z
dc.date.available2020-07-14T13:37:22Z
dc.date.issued2020-05
dc.identifier.otherd20009
dc.identifier.urihttps://soar.wichita.edu/handle/10057/18806
dc.descriptionThesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Electrical Engineering & Computer Science
dc.description.abstractThe concept of smart cities (SCs) has been evolved in recent years in gaining signi cant importance for intelligent development and sustainable socio-economic growth of cities. The wide use of information and communication technologies (ICT) in di erent domains help smart cities in making citizens' life easier and better. The inclusion of intelligence in all infrastructure and citizen services ensures SC's sustainability and e ciency. This dissertation focuses on some challenges, under the umbrella of smart cities conceptual framework, in areas such as smart grids, info-mobility, people mobility, welfare and social inclusion, etc. In particular, data management in advanced metering infrastructures (AMI) of smart grids considering the requirements of quality-of-service (QoS) and the way nding of blind and visually impaired (BVI) persons in outdoor space for smart living have been considered in this dissertation work. This dissertation addresses the scenario of how to deal with huge data volume challenges in smart grids AMI. This work proposes a novel approach, and also shows its e ciency to manage AMI data tra c volume through data aggregation, that estimates the expected network delays messages would su er and dynamically determines an aggregation policy such that the electric utility gets the information in a more timely manner, albeit at a lower data granularity. Moreover, the scenario of managing the trade o between QoS and data volume reduction through a mathematical optimization framework to estimate the level of data aggregation needed in a large multi-level data collection network of smart grid AMI is also considered in this dissertation work. An intelligent approach containing an optimization framework is proposed to manage AMI data tra c volume in multi-level data collection trees that dynamically determines an aggregation policy to be applied at forwarding nodes of the tree to reduce the network delays with which the electric utility can get the necessary information. This dissertation also focuses on proposing a computer visionbased image localization framework for accurately providing path advancement information in an outdoor environment for way nding of BVI persons.
dc.format.extentxvi, 91 pages
dc.language.isoen_US
dc.publisherWichita State University
dc.rightsCopyright 2020 by Uddipan Das All Rights Reserved
dc.subject.lcshElectronic dissertation
dc.titleAlgorithms and frameworks towards sensing data in smart cities
dc.typeDissertation


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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • Dissertations
    This collection includes Ph.D. dissertations completed at the Wichita State University Graduate School (Fall 2005 --)
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science

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