Zaheer Allam

Curtin University Sustainability Policy Institute, Curtin University, Australia

Redefining the smart city: culture, governance and metabolism
Case study of Port Louis, Mauritius

BACKGROUND
The world is witnessing a mass movement of people from rural to urban setups. For the first time in the human history, man is more present in cities rather than in the countryside. Such boom in urban demographics has stretched and burden the foundations of cities from a structural, socio-economic and environmental perspective. This new density is further substantiated by the economic significance of urban areas. There is a drive to further expand economies is furthered in the concept of Smart Cities through tools to enhance productivity and interconnectivity by big data and real-time processing (Nam and Pardo, 2011). However, literature warns about the danger of technocratic governance and mass surveillance that big data cities will generate (Shelton et al., 2015). In a drive to adopt the Smart concept, and its related brand, new smart cities are mushrooming around the world. Although these new smart cities will lead to enhance productivity, there are dangers that are being overlooked in literature; for instance, loss of biodiversity, urban sprawl, and a resulting increasing need for vehicular transportation (Khan et al., 2015, Ning et al, 2017; Rathore et al.,2016).

As new cities require new infrastructures, property value is higher as opposed to existing cities. This creates an unhealthy environment as only upper middle-class professional can afford these cities (Shapiro, 2006). New smart cities are conspicuous for businesses which will lead to an exodus of organisations and trades from existing urban areas for new smart ones (Nam and Pardo, 2011). This provides an environment of unfair competition, where existing cities loses its attractivity, and thus suffers from business retention in the favour of new Smart Cities. To avoid such mishaps, Shelton et al. (2015) postulate the need for showcasing existing cities using a smart concept. This will create a fair competitive environment and ensure a healthy social and business mix. Moreover, in terms of sustainability, smarting an existing city is more favourable over building an entirely new one.

CASE STUDY
When Mauritius branded its ‘Smart Mauritius’ Initiative, a valid framework for new Smart Cities was released in 2015 (BoI, 2018). However, no such concept exists for smarting existing urban areas into smart ones. While new Smart Cities are being initiative, Port Louis, the Capital city of Mauritius is being met with increasing challenges for business retention; leading to a slow urban decay. The study develops a model of how to smart an existing city while socially and economically rejuvenating the social fabric of Port Louis.

METHODOLOGY
The methodology applied is based on a theoretical review of literature and a focus group approach including private and public stakeholders.

PROPOSED MODEL
The study aims at redefining the concept of smart city based on three key dimensions:
Culture
Existing cities already have a solid foundation with prominent cultural and historical dimensions associated to them. Aspects of preserving both tangible, in the form of Architectural landmarks, and intangible components of the city is studied. When coupled with Smart Infrastructures, Culture can feed new innovative manifestations, and give rise to a new market (EY, 2015).

Governance
A model of Governance is explored to support the transition from an existing urban fabric to a Smart one. The model supports economically incentivising urban regeneration through Governmental measures, with a specific focus on Smart Infrastructures, Culture and Sustainability. Smart Cities in Mauritius is privately owned by few large businesses. The proposed model also allows for decentralising wealth creation.

Metabolism
Revamping an existing city is more sustainable than building a new one. However, while smarting existing cities, there is need to understand how materials flow within a city and how it affects liveability. Urban metabolism offers an understanding on this matter (Newman et al., 2017).

RESULTS
A theoretical model linking culture, governance and metabolism specifically for the city of Port Louis is proposed. A resulting framework, a National Urban Regeneration Scheme, aimed at sustainably smarting existing cities is defined and its economic quantification of adoption is further modelled and showcased for the City of Port Louis.

REFERENCES
Baslé, M., 2016. Smarter Cities’ Attractiveness. Testing New Criteria or Facets:“Data Scientists” and “Data Platforms”. Journal of the Knowledge Economy, pp.1-11.

BoI, 2018. Smart Cities. Board of Investment [online]. Available from: http://www.investmauritius.com/investment-opportunities/smart-cities.aspx [Accessed 14th April 2018].

EY, 2015. Cultural Times. Available from: http://www.ey.com/Publication/vwLUAssets/ey-cultural-times-2015/$FILE/ey-cultural-times-2015.pdf [Accessed 14th April 2018].

Khan, Z., Anjum, A., Soomro, K. and Tahir, M.A., 2015. Towards cloud based big data analytics for smart future cities. Journal of Cloud Computing, 4(1), p.2.

Newman, P., Beatley, T. and Boyer, H., 2017. Produce a More Cyclical and Regenerative Metabolism. In Resilient Cities (pp. 155-177). Island Press, Washington, DC.

Ning, Z., Xia, F., Ullah, N., Kong, X. and Hu, X., 2017. Vehicular social networks: Enabling smart mobility. IEEE Communications Magazine, 55(5), pp.16-55.

Pereira, G.V., Bernardes, M.B., Bernardini, F., Cappelli, C. and Gomyde, A., 2017, June. Building a Reference Model and an Evaluation Method for cities of the Brazilian Network of Smart and Human Cities. In Proceedings of the 18th Annual International Conference on Digital Government Research(pp. 580-581). ACM.

Rathore, M.M., Ahmad, A., Paul, A. and Rho, S., 2016. Urban planning and building smart cities based on the internet of things using big data analytics. Computer Networks, 101, pp.63-80.

Shelton, T., Zook, M. and Wiig, A., 2015. The ‘actually existing smart city’. Cambridge Journal of Regions, Economy and Society, 8(1), pp.13-25.