Algorithms and frameworks towards sensing data in smart cities

Abstract

The 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.