Big data driven multi-tier architecture for electric mobility as a service in smart cities

Abstract

Purpose Electric mobility as a service (eMaaS) is suggested as a possible solution to ease transportation and lessen environmental issues by providing a collaborative transport sharing infrastructure that is based on electric vehicles (EVs) such as electric cars, electric bicycles and so on. Accordingly, this study aims to propose a multi-tier architecture to support the collection, processing, analytics and usage of mobility data in providing eMaaS within smart cities. The architecture uses application programming interfaces to enable interoperability between different infrastructures required for eMaaS and allow multiple partners to exchange and share data for making decision regarding electric mobility services. Design/methodology/approach Design science methodology based on a case study by interview was used to collect data from an infrastructure company in Norway to verify the applicability of the proposed multi-tier architecture. Findings Findings suggest that the architecture offers an approach for collecting, aggregating, processing and provisioning of data originating from sources to improve electric mobility in smart cities. More importantly, findings from this study provide guidance for municipalities and policymakers in improving electric mobility services. Moreover, the author’s findings provide a practical data-driven mobility use case that can be used by transport companies in deploying eMaaS in smart cities. Research limitations/implications Data was collected from a single company in Norway, hence, it is required to further verify the architecture with data collected from other companies. Practical implications eMaaS operates on heterogeneous data, which are generated from EVs and used by citizens and stakeholders such as city administration, municipality transport providers, charging station providers and so on. Therefore, the proposed architecture enables the sharing and usage of generated data as openly available data to be used in creating value-added services to improve citizen’s quality of life and viability of businesses. Social implications This study proposes the deployment of electric mobility to address increased usage of vehicles, which contributes to pollution of the environment that has a serious effect on citizen’s quality of life. Originality/value This study proposes a multi-tier architecture that stores, processes, analyze and provides data and related services to improve electric mobility within smart cities. The multi-tier architecture aims to support and increase eMaaS operation of EVs toward improving transportation services for city transport operators and citizens for sustainable transport and mobility system.

Applying Enterprise Architecture for Digital Transformation of Electro Mobility towards Sustainable Transportation

“…Although, DT for eMobility is faces with several challenges, ranging from network, requirements, communication protocols, interfaces, data integration, etc. [8,37].…”

Managing digital transformation of smart cities through enterprise architecture – a review and research agenda

“…This is accomplished by identifying and analysing the implementation of changed towards the desired business vision and goals (Bhatt, Ghuman, and Dhir 2020). EA supports to identify business processes that are common and sharable across the city, optimise business efficiency and decrease operational cost (Jnr et al 2020b). EA supports the changing business models and needs, provide improve service to citizens and improve service productivity (Kempegowda and Chaczko 2018).…”

“…EA facilitates digital transformation as a fundamental changing process initiated for competitive advantages through the development of IT for value creation. EA in digital transformation of cities aids municipalities to achieve clear transformation strategy and vision for stakeholders (Goerzig and Bauernhansl 2018;Jnr et al 2020b). EA provides agility and flexibility in business and IT systems for digitisation of services and products in cities by proving close alignment of digital technologies and business models for smart solutions and strategies (Zimmermann et al 2016).…”

“…An application of OEAF in digital transformation for Electric Mobility as A Service (eMaaS) in smart city is shown in Figure 8. The presented example is derived from prior studies Anthony Jnr 2020a;Jnr et al 2020b) that employed EA to model eMaaS in smart cities. Figure 8 depicts results of the applicability of OEAF in digital transformation for eMaaS in smart city.…”

“…EA has been and still is a continually evolving domain which is shaped by technological advances and social progress as well as learning outcomes. EA has been employed by prior studies in smart city domain (Pourzolfaghar, Bezbradica, and Helfert 2016;Anthony Jnr 2020a;Jnr et al 2020b). One key objective of EA is to integrate the different facets of cities aligned which includes business interests and information systems.…”