Zaheer Abbas Khan

Cloud Based Big Data Analytics for Smart Future Cities

ICT is becoming increasingly pervasive to urban environments and providing the necessary basis for sustainability and resilience of the smart future cities. Often ICT tools for a smart city deal with different application domains e.g. land use, transport, energy, and rarely provide an integrated information perspective to deal with sustainability and socioeconomic growth of the city. Smart cities can benefit from such information using Big, and often real-time cross-thematic, data collection, processing, integration and sharing through inter-operable services deployed in a Cloud environment. However, such information utilisation requires appropriate software tools, services and technologies to collect, store, analyse and visualise large amounts of data from the city environment, citizens and various departments and agencies at city scale. This paper presents a theoretical perspective on the smart cities focused Big data processing and analysis by proposing a Cloud-based analysis service that can be further developed to generate information intelligence and support decision-making in smart future cities context.

Towards cloud based big data analytics for smart future cities

A large amount of land-use, environment, socio-economic, energy and transport data is generated in cities. An integrated perspective of managing and analysing such big data can answer a number of science, policy, planning, governance and business questions and support decision making in enabling a smarter environment. This paper presents a theoretical and experimental perspective on the smart cities focused big data management and analysis by proposing a cloud-based analytics service. A prototype has been designed and developed to demonstrate the effectiveness of the analytics service for big data analysis. The prototype has been implemented using Hadoop and Spark and the results are compared. The service analyses the Bristol Open data by identifying correlations between selected urban environment indicators. Experiments are performed using Hadoop and Spark and results are presented in this paper. The data pertaining to quality of life mainly crime and safety & economy and employment was analysed from the data catalogue to measure the indicators spread over years to assess positive and negative trends.

An Architecture for Integrated Intelligence in Urban Management Using Cloud Computing

With the emergence of new methodologies and technologies it has now become possible to manage large amounts of environmental sensing data and apply new integrated computing models to acquire information intelligence. This paper advocates the application of cloud capacity to support the information, communication and decision making needs of a wide variety of stakeholders in the complex business of the management of urban and regional development. The complexity lies in the interactions and impacts embodied in the concept of the urban-ecosystem at various governance levels. This highlights the need for more effective integrated environmental management systems. This paper offers a user-orientated approach based on requirements for an effective management of the urban-ecosystem and the potential contributions that can be supported by the cloud computing community. Furthermore, the commonality of the influence of the drivers of change at the urban level offers the opportunity for the cloud computing community to develop generic solutions that can serve the needs of hundreds of cities from Europe and indeed globally.

ICT enabled participatory urban planning and policy development: The UrbanAPI project

Purpose – The aim of this paper is to present the effectiveness of participatory information and communication technology (ICT) tools for urban planning, in particular, supporting bottom-up decision-making in urban management and governance. Design/methodology/approach – This work begins with a presentation on the state of the art literature on the existing participatory approaches and their contribution to urban planning and the policymaking process. Furthermore, a case study, namely, the UrbanAPI project, is selected to identify new visualisation and simulation tools applied at different urban scales. These tools are applied in four different European cities – Vienna, Bologna, Vitoria-Gasteiz and Ruse – with the objective to identify the data needs for application development, commonalities in requirements of such participatory tools and their expected impact in policy and decision-making processes. Findings – The case study presents three planning applications: three-dimensional Virtual Reality at neig...

A framework for cloud-based context-aware information services for citizens in smart cities

BackgroundIn the context of smart cities, public participation and citizen science are key ingredients for informed and intelligent planning decisions and policy-making. However, citizens face a practical challenge in formulating coherent information sets from the large volumes of data available to them. These large data volumes materialise due to the increased utilisation of information and communication technologies in urban settings and local authorities’ reliance on such technologies to govern urban settlements efficiently. To encourage effective public participation in urban governance of smart cities, the public needs to be facilitated with the right contextual information about the characteristics and processes of their urban surroundings in order to contribute to the aspects of urban governance that affect them such as socio-economic activities, quality of life, citizens well-being etc. The cities on the other hand face challenges in terms of crowd sourcing with quality data collection and standardisation, services inter-operability, provisioning of computational and data storage infrastructure.FocusIn this paper, we highlight the issues that give rise to these multi-faceted challenges for citizens and public administrations of smart cities, identify the artefacts and stakeholders involved at both ends of the spectrum (data/service producers and consumers) and propose a conceptual framework to address these challenges. Based upon this conceptual framework, we present a Cloud-based architecture for context-aware citizen services for smart cities and discuss the components of the architecture through a common smart city scenario. A proof of concept implementation of the proposed architecture is also presented and evaluated. The results show the effectiveness of the cloud-based infrastructure for the development of a contextual service for citizens.

Towards a secure service provisioning framework in a Smart city environment

Abstract Over the past few years the concept of Smart cities has emerged to transform urban areas into connected and well informed spaces. Services that make smart cities “smart” are curated by using data streams of smart cities i.e., inhabitants’ location information, digital engagement, transportation, environment and local government data. Accumulating and processing of these data streams raise security and privacy concerns at individual and community levels. Sizeable attempts have been made to ensure the security and privacy of inhabitants’ data. However, the security and privacy issues of smart cities are not only confined to inhabitants; service providers and local governments have their own reservations — service provider trust, reliability of the sensed data, and data ownership, to name a few. In this research we identified a comprehensive list of stakeholders and modelled their involvement in smart cities by using the Onion Model approach. Based on the model we present a security and privacy-aware framework for service provisioning in smart cities, namely the ‘Smart Secure Service Provisioning’ (SSServProv) Framework. Unlike previous attempts, our framework provides end-to-end security and privacy features for trustable data acquisition, transmission, processing and legitimate service provisioning. The proposed framework ensures inhabitants’ privacy, and also guarantees integrity of services. It also ensures that public data is never misused by malicious service providers. To demonstrate the efficacy of SSServProv we developed and tested core functionalities of authentication, authorisation and lightweight secure communication protocol for data acquisition and service provisioning. For various smart cities service provisioning scenarios we verified these protocols by an automated security verification tool called Scyther.

Domain-specific languages for agile urban policy modelling

In this paper we present a new approach of performing urban policy modelling and making with the help of ICT enabled tools. We present a complete policy cycle that includes creating policy plans, securing stakeholders and public engagement, implementation, monitoring, and evaluating a particular policy model. ICT enabled tools can be deployed at various stages in this cycle, but they require an intuitive interface which can be supported by domainspecific languages (DSLs) as the means to express policy modelling aspects such as computational processes and computer-readable policy rules in the words of the domain expert. In order to evaluate the use of such languages, we present a real-world scenario from the urbanAPI project. We describe how DSLs for this scenario would look like. Finally, we discuss strengths and limitations of our approach as well as lessons learnt.

Bridging the gap between business process models and service-oriented architectures with reference to the grid environment

In recent years, organisations have been seeking technological solutions for enacting their business process models using ad-hoc and heuristic approaches. However, limited results have been obtained due to the expansion of business processes across geographical boundaries and the absence of structured methods, frameworks and/or Information Technology (IT) infrastructures to enact these processes. In an attempt to enact business process models using distributed technologies, we introduce a novel architectural framework to bridge the gap between business process models and Grid-aware Service-Oriented Architectures (GSOA). BPMSOA framework is aligned with the Model-Driven Engineering (MDE) approach and is instantiated for role-based business process models [in particular Role Activity Diagramming (RAD)], using mobile process languages such as pi-ADL. The evaluation of the BPMSOA framework using the Submission process from the digital libraries domain has revealed that role-based business process models can be successfully enacted in GSOA environments with certain limitations.

Digital Libraries: From Process Modelling to Grid-based Service Oriented Architecture

Graphical Business Process Modelling Languages (BPML) like Role Activity Diagrams (RAD) provide ease and flexibility for modelling business behaviour. However, these languages show limited applicability in terms of enactment over distributed systems paradigms like service oriented architecture (SOA) based grid computing. This paper investigates RAD modelling of a scientific publishing process (SPP) for digital libraries (DL) and tries to determine the suitability of Pi-calculus based formal approaches to enact SOA based grid computing. In order to achieve this purpose, the Pi-calculus based formal transformation from a RAD model of SPP for DL draws attention towards a number of challenging issues including issues that require particular design considerations for appropriate enactment in a SOA based grid system

Evaluating a collaborative IT based research and development project

In common with all projects, evaluating an Information Technology (IT) based research and development project is necessary in order to discover whether or not the outcomes of the project are successful. However, evaluating large-scale collaborative projects is especially difficult as: (i) stakeholders from different countries are involved who, almost inevitably, have diverse technological and/or application domain backgrounds and objectives; (ii) multiple and sometimes conflicting application specific and user-defined requirements exist; and (iii) multiple and often conflicting technological research and development objectives are apparent. In this paper, we share our experiences based on the large-scale integrated research project - The HUMBOLDT project - with project duration of 54 months, involving contributions from 27 partner organisations, plus 4 sub-contractors from 14 different European countries. In the HUMBOLDT project, a specific evaluation methodology was defined and utilised for the user evaluation of the project outcomes. The user evaluation performed on the HUMBOLDT Framework and its associated nine application scenarios from various application domains, resulted in not only an evaluation of the integrated project, but also revealed the benefits and disadvantages of the evaluation methodology. This paper presents the evaluation methodology, discusses in detail the process of applying it to the HUMBOLDT project and provides an in-depth analysis of the results, which can be usefully applied to other collaborative research projects in a variety of domains.