Cities are contemporary metropolises that concentrate human and social activity;

engineered to support and develop the physical environment and the people within it, Smart

cities, we are led to believe, are the immediate future, where smartness is perceived as a

characterisation of advancements or digitalisation, in government, mobility and sustainability.

Therefore it is not surprising that many organisations are marketing their smart solutions and

products, often to a ubiquitous extent and so called smart cities are striving to outperform each

other. But how are smart cities actually being defined and how is performance being measured

in an era where there is increasing access to unprecedented amounts of foreseen data? This

paper identifies the plethora of the smart city definitions and categories evidenced from the

literature and shows that 'Smart cities' lacks a robust coherent definition, with many

contradicting facts within what constitutes a smart vision. Notably, almost every attempt from

organisations, the European Union or cities themselves has failed to define 'smart' in objective

terms that can be accepted globally. Certainly, they all are negotiating with a range of

descriptors and smart ways to improve the city. Even the UK's attempts to develop a clear

definition and set of standards for smart cities (i.e. PAS 180 and PAS 182) appears to suffer

from fundamental differences in how the semantic content of a 'smart' city is defined. This paper

demonstrates the necessity for a single 'Smart Cities' definition that deals with both the physical

and digital using shared parameter value(s) that can be adopted and scaled amongst different

localities and within a range of urban contexts adjusting according to existing city condition(s)

and vision(s) setting the paradigm for further innovative research in this area

The unique artificial intelligence experiment by the City of Espoo and the software and service company Tieto achieved the hoped-for result: artificial intelligence can pick up service paths out of an enormous mass of service data by grouping together risk factors that trigger the need for heavy and expensive services if found in the same person. The experiment was unique, because public administration client relationship data has never been combined and analysed as extensively using artificial intelligence before.

This roundtable aimed at discussing and sparking new train of thoughts on how to strengthen the role of urban innovation among the city leaders, institutions and urban stakeholders, including private sector organisations. It further explored the strategic pathways for Urban Innovation Community (UIC) to provide new tools, expertise and knowledge on implementing and achieving the SDGs at the local level. 

Kent County Council (KCC) UK is responsible for providing public services in education, transport, strategic planning, emergency services, social services, public safety and waste disposal to 1.4M residents across 12 district councils and 300 town and parish councils. KCC wanted to rethink Citizen Services for a digital world that would improve health and social care, regenerate towns and cities, and grow its gross domestic product (GDP) by using technology as an enabler to help make people’s lives better.