Abstract

ICT is becoming an enabler for smart city applications by making effective use of various data resources generated daily in an urban environment. Mostly this data is utilised by city authorities for city planning purposes and often citizens become indirect beneficiaries of such applications. In this paper we present an algorithm for real-time processing of streaming data from multiple sources. We also present the design and proof of concept of an application that performs mining and analysis of open data available through city portals and social networks and generates an information service in real time for use by city administrations. The prototype utilises streaming data from Twitter and open data from Bristol to demonstrate a hypothetical scenario using Apache Storm. The output is presented in the form of visual maps using OpenStreetMaps as a backend and the prototype highlights various challenges which are discussed in detail.

Highlights

  • ICT is becoming one of the enablers of smart cities, known as ubiquitous cities [6]

  • The ubiquitous nature of Internet of Things (IoT) and crowd sourcing provide a greater opportunity to cities to monitor the state of the urban environment in near real time and take decisions

  • Though city administrations are becoming more equipped with new technologies, processes and tools to effectively utilise city data, near real-time processing and decision making has still largely been neglected

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Summary

Introduction

ICT is becoming one of the enablers of smart cities, known as ubiquitous cities [6]. The increasing urban population [2] [15] and myriad city sustainability and planning challenges [11] [1] need timely information intelligence for decision making In this respect, the ubiquitous nature of Internet of Things (IoT) and crowd sourcing provide a greater opportunity to cities to monitor the state of the urban environment in near real time and take decisions. The ubiquitous nature of Internet of Things (IoT) and crowd sourcing provide a greater opportunity to cities to monitor the state of the urban environment in near real time and take decisions These IoTs and crowd sourcing activities by citizens generate huge amounts of socio-economic and urban footprint data [5] which requires fast processing and storage capabilities. On the other hand new information services can be designed and developed to meet the requirements of different stakeholders resulting in wider adoption of smart city solutions

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