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​​​Figure 1. Illustration of a typical frame work of smart city.​

Smart cities, can the performance be measured?

Miimu Airaksinen | 14.6.2016

​Today 78 per cent of European citizens live in cities, and 85 per cent of the EU’s GDP is generated in cities. In addition, over 90 per cent of the innovations are generated in cities. At the same time over 70 per cent of all CO2 emissions are originated from cities. In order to avoid negative effects cities need to transform themselves into ‘smart cities’.

Performance analysis has become an important tool in planning and in project assessment, but also in assessing cities. The comparison of cities can support investors in their choice of location and also it can be an important guide for the cities to judge their strengths and weaknesses and to define their goals and strategies for future development and better positioning in the urban system.

The comparison and analyse of current smart city indicator frameworks showed clearly that the three sustainability pillars; people, planet and profit are widely used and adopted. However, this is not enough to determine the success of a smart city project. Success is also determined by how projects have been – or will be – realised in various contexts. The Governance of developing and implementing urban smart city projects is a determining factor for high scores in people, planet and prosperity indicators. Therefore CITYkeys framework has included a number of indicators to evaluate the importance of the city context and quality of the development and implementation process.

 
In addition the ability of individual smart city success stories to be replicated in other cities and contexts is important. Under the CITYkeys Propagation category, smart city projects are evaluated to determine their potential for up-scaling and the possibilities for application in other contexts.

 
Monitoring key performance indicators also enables optimized operation of different subsystems within a city (e.g. energy or mobility) by enlarging the efficiency of urban flows as energy resources and mobility, while minimising the environmental impact at the same time. A city monitoring system provides access to and exchange between data of different applications in an urban environment. In order to maximise the input from various subsystems in cities the systems should be based on standards and interoperable interfaces. Further, the monitoring systems can support also the optimal operation of cities with holistic city operating systems by enabling the collection and distribution of sensor data, analysis and visualisation.

 

Background and introduction

Whereas more than half of the world’s population lives in cities, this rises to over two thirds in EU28 and the proportion is growing. Moreover, by 2050 nearly 70 per cent of the world population will live in urban areas. High density city populations increase strains on energy, transportation, water, buildings and public spaces.1 Urban areas account for 70 per cent of current global CO2 emissions and hence heavily contribute to the threats of global climate change, while simultaneously being highly vulnerable to the impacts of it. This causes extensive challenges, for example regarding air pollution, congestion, waste management and human health.2

 
According to SBA3,4, sustainability is based on a principle where everything that we need for our survival and well-being depends, either directly or indirectly, on our natural environment. Sustainability creates and maintains the conditions under which humans and nature can exist in productive harmony, that permit fulfilling the social, economic and other requirements of present and future generations. Sustainability is important to making sure that we have and will continue to have, the water, materials, and resources to protect human health and our environment.

 
The term ‘smart city’ often implies a usage of ICT solutions in the city.5 Some definitions use intelligent cities and smart cities as synonymous terms6 while others make a distinction.5 According to Malek7, the intelligent city refers to a city that has an information technology infrastructure. Often the ultimate objective of smart city is to be sustainable.8

 
Cities are also areas of creativity and of economic growth: the potential for exchanges, optimization and new solutions is unique and enormous. However, this transition process is progressing slow.9,10 As the EU has set its climate and energy targets for 2030 (EC 2014) there is an urgent need to develop smart solutions to overcome barriers and to address these challenges,11 and accelerate transition. Innovative approaches are needed to tackle problems related to overcrowding and jamming of infrastructures, energy consumption, resource management and environmental protection. The development of Smart Cities solutions is highly relevant in order to contribute to the climate targets established in the European 2030 Strategy and, beyond that to the European 2050 objectives.

 
There is a strong need for new, efficient, and user-friendly technologies and services, in particular in areas of energy, transport, and ICT with interoperable and integrated approaches: ‘smart’ solutions, i.e. both highly efficient and sustainable on the one hand, as well as generating economic prosperity and social wellbeing on the other. This is best achieved by mobilising all of a city’s resources and coordinating its actors using new technologies and forward looking joined-up policies.

 
Performance analysis has become an important tool in planning phase or in project assessment, but also in assessing cities. City rankings are popular today and they increasingly attract public attention. The comparison of cities can attract new resident citizens and support investors in their choice of location. In addition it can be an important guide for the cities to judge their strengths and weaknesses and to define their goals and strategies for future development and better positioning in the urban system. For proper comparison of cities appropriate evaluation mechanisms and indicators are needed. An indicator can be defined as “Anything used to measure the condition of something of interest. Indicators are often used as variables in the modelling of changes in complex environmental systems.”12

 
City administrations tend to use a diverse set of key performance indicators (KPIs) to evaluate the success of specific projects. These KPIs may reflect the city’s environmental and social goals, as well as its economic objectives.13 Appropriate metrics need to articulate progress towards determined strategic goals aligned with the sustainability principles, which can then lead cities to develop indicators to measure success against the goals in each smart city characteristic. It has also been suggested that it is vital that metrics measuring success are connected to the vision and goals.14

 
Currently there are many initiatives by cities, companies, research groups, and authorities to create methodologies or frameworks for assessment of the sustainability or the environmental impact of a city. Recently, several standards have been developed using life cycle thinking to determine the environmental impact of ICT products, networks and services. There are also a number of initiatives where cities are to report their greenhouse gas emissions and energy usage.15

 
Most often in smart city assessment frameworks the classical people (society), planet (environment), profit (economy) classification is used (see Figure 1), or in some that classification is behind the framework. Typically the assessment frameworks have indicators in the categories of economy, people and living, and governance and services. In addition almost all frameworks also have indicators related to environment, and these indicators consider mainly energy consumption, sustainability of buildings, carbon footprint, waste generation etc. Also smart mobility, transport and infrastructure are addressed in the systems but there the focus is somewhat different depending on the framework. The role of ICT as enabling technology is embedded in all main categories.

 

Key performance indicators

There is a multitude of indicator sets in place, but only a few that are generally accepted. The result is that cities tend to use those that suit their purposes; and have significant difficulty in making a fair comparison between cities – and at times within their own city.

 
European Innovation Partnership on Smart Cities8 seeks to support cities in becoming more energy efficient, using more renewable energy and saving greenhouse gas emissions by stimulating technological innovation, engaging citizens and providing innovative concepts, processes, methods and tools. To create transparency and build confidence, all such actions need to be quantifiable against clear baselines such that gains can be clearly evidenced – to city leadership and society. Measuring a city’s progress can raise societal awareness for a low-carbon lifestyle, support industry in identifying new business opportunities, and help city administration in coordinating and monitoring the transformation process. For this, a comprehensive indicator system, based as far as possible on real data, is needed.

 
Although there are many good indicator systems in place for cities, such as the Reference Framework for Sustainable Cities, Global City Indicators Facility, the European Energy Award and the like; there is no broadly-accepted indicator system that reflects the ‘smart city’ approach. Developing one would enable cities to self-evaluate and compare their progress. This will require unambiguous operational definition of the term ‘smart city’ from which city indicators can be derived, and improved consistency and comparability of urban data among European cities. Greater acceptance is also required at city leadership levels to more openly report on progress against common agreed indicators.

 
In CITYkeys review of existing frameworks, it can be seen that the current smart city frameworks and KPIs have very wide range from very specific sectoral project based indicators to holistic and integrated citywide indicator frames. It can be seen that the good majority of mapped frameworks targets the scale of the entire city by using an integrated-holistic methodology and relevant indicators.

 
According to review16 of smart city indicator frameworks it can be concluded that the following categories are the most often used: Economy, People & Living, Governance & Services, Mobility & Transport & Infrastructure and Environment. ICT is embedded in each category. Typically in each assessment scheme the indicators are differently categorised in and therefore doing a clear division into the categories is rather difficult. The different categories are also often overlapping with each other; for example indicators in the Infrastructure category are often also related to environment and therefore overlapping with the Environment category. This highlights the importance of integrated approach.

 
Evidently environment and energy related indicators are among of the most important in respect of reducing CO2 emissions.17,18,19 Typically energy is assessed in respect of the efficiency of energy consumption, use of renewable energy or availability clean energy transport. Energy use is typically measured by energy consumption per GDP or per capita but also other types of indicators exist e.g. the deployment of smart metering by a percentage of households.

 
In most of the assessment schemes the indicators related to energy and migitation were well presented highlighting the importance of environmental issues, these are the typical “planet” indicators referred in Figure 1. In addition the other two traditional sustainability pillars “people” and “property” were well covered. However, indicators describing multilevel governance or scalability or replicability of projects were non-existing. This is striking since multilevel governance is the crucial enabler for integrated solutions in cities. In addition scalability and replicability are important when considering the implementation and spreading viable solutions.

 
The CITYkeys assessment method and the indicators are to be used to evaluate the success of smart city projects and the possibility to replicate the (successful) projects in other contexts. The success is determined by the transition across the entire ecological footprint of urban areas, simultaneously promoting economic prosperity, social aims and resilience to climate change and other external disturbances. Over the past decennia, the concept of sustainability – split up in the triple bottom line of social sustainability (people), environmental sustainability (planet) and economic sustainability (prosperity) – has become generally accepted in the development of indicator systems for national and regional urban development.20 The 3 Ps (people, planet, prosperity) have also gained considerable ground in company reporting.21

 
The extent to which smart city projects are able to have an effect on social, environmental and economic indicators forms the core of the evaluation. However, this is not enough to determine the success of a smart city project. Success is also determined by how projects have been – or will be – realised in various contexts. The Governance of developing and implementing urban smart city projects is a determining factor for high scores in people, planet and prosperity indicators.22 Hiremath et al. also notes that Governance has been established as one of the four pillars of sustainable development.17 Therefore we need to include a number of indicators to evaluate the importance of the city context (external factors) and quality of the development and implementation process (internal factors). 

 
Finally, the ability of individual smart city projects to be replicated in other cities and contexts determines its ultimate effect in achieving European goals with regard to energy and CO2 emissions. Under the Propagation category, smart city projects are evaluated to determine their potential for up-scaling and the possibilities for application in other contexts.

 

Measuring key performance indicators

To understand a city’s functions and to evaluate its performance it is important that the smart city indicators would be obtained from data in as real time as possible for the critical infrastructure and in areas like building and traffic control.

 
The real time data can be categorised into two main categories; 1) physical urban data and 2) information from measured data. The physical illustrative data here refers to urban area monitoring e.g. urban pattern recognition for the physical monitoring of cities. The information from measured data refers here on the provisioning and consumption of urban services; measures like energy and water supply or waste collection. The urban data is information on supply and demand. Basically this kind of data is easy to monitor but in practise this data is much more challenging to monitor than the physical urban data.

 

Interpretation of Monitored Key Performance Indicators

Performance efficiency can be defined as a ratio between an output of performance, service, goods, or energy, and an input of energy.23 E.g. energy intensities have probably become the most common indicators of energy efficiency. It measures the rate of energy consumption per outcomes, and answers the basic question: how much must one consume energy to achieve the desired result? This might seem uncomplicated, but in reality, both input and output can be measured in numerous ways and choosing one approach over another always leads to compromises.24

 
IMP_1_16_tiede2_1_EN.jpg
 
Figure 2. CITYkeys framework for smart city indicators (www.citykeys-project.eu).

Monitoring Key Performance Indicators

Monitoring key performance indicators also enables optimized operation of different subsystems within a city (e.g. energy or mobility) by enlarging the efficiency of urban flows as energy resources and mobility, while minimising the environmental impact at the same time.

 
At the same time, access to user data continues to be of importance to utilities for operational purposes and to achieve the efficient use of resources. In addition, access to such data by consumers and authorized third parties has significant potential to enable consumers to understand their energy use, and thus become more proactive in managing that use, ultimately saving money on their energy bills and becoming more efficient consumers of energy.

 
The success for accurate data optimisation needs both the development of legal and regulatory regimes that respect consumer privacy, promote consumer access to and choice regarding third –party use of their energy data, and secure potentially sensitive data to increase consumer acceptance of open data.25 In addition, the success of such efforts also depends upon the development of appropriate technical standards and protocols for promoting privacy, choice, and the secure, interoperable transfer and maintenance of sensitive data.

 

Discussion and conclusion

Performance analysis has become an important tool in planning and in project assessment, but also in assessing cities. City rankings are highly popular today and they increasingly attract public attention. The comparison of cities can support investors and citizens in their choice of location and also it can be an important guide for the cities to judge their strengths and weaknesses and to define their goals and strategies for future development and better positioning in the urban system.

 
City administrations tend to use a diverse set of key performance indicators to evaluate the success of specific projects. These KPIs may reflect the city’s environmental and social goals, as well as its economic objectives. Appropriate metrics need to articulate progress towards determined strategic goals aligned with the sustainability principles, which can then lead cities to develop indicators to measure success against the goals in each smart city characteristic. It has also been suggested that it is vital that metrics measuring success are connected to the vision and goals.

 
The comparison and analyse of current smart city indicator frameworks showed clearly that the three sustainability pillars; people, planet and profit are widely used and adopted.

 
However, this is not enough to determine the success of a smart city project. Success is also determined by how projects have been – or will be – realised in various contexts. The Governance of developing and implementing urban smart city projects is a determining factor for high scores in People, Planet and Prosperity indicators. Therefore CITYkeys framework has included a number of indicators to evaluate the importance of the city context (external factors) and quality of the development and implementation process (internal factors). 

 
Finally, the ability of individual smart city projects to be replicated in other cities and contexts determines its ultimate effect in achieving the goals with regard to energy and CO2 emissions. Under the CITYkeys Propagation category, smart city projects are evaluated to determine their potential for up-scaling and the possibilities for application in other contexts.

 
To understand a city’s functions and to evaluate its performance it is important that the smart city indicators would be obtained from data in as real time as possible. The monitored indicators should give a holistic view of city’s sustainability development. In city level the energy use of buildings is most commonly measured in kWh or in kWh/m2. This metric is very useful when considering building stock design but it does not provide an understanding as to how effectively building stock is utilised during the operations phase. This indicator might even lead to a wrong conclusion if the usage and history of building stock is not known. In the operation phase it is important to know how efficiently the buildings are used. Thus, the number of hours per day when the buildings are occupied is important but also how densely the space is populated.

 
Monitoring key performance indicators also enables optimized operation of different subsystems within a city (e.g. energy or mobility) by enlarging the efficiency of urban flows as energy resources and mobility, while minimising the environmental impact at the same time. 
A city monitoring system provides access to and exchange between data of different applications in an urban environment.

 
In order to maximise the input from various subsystems in cities the systems should be based on standards and interoperable interfaces. Further, the monitoring systems can support also the optimal operation of cities with holistic city operating systems by enabling the collection and distribution of sensor data, analysis and visualisation.

 
Accurate data optimisation needs both the development of legal and regulatory regimes that respect consumer privacy, promote consumer access to and choice regarding third-party use of their energy data, and secure potentially sensitive data to increase consumer acceptance of open data. In addition the success of such efforts also depends upon the development of appropriate technical standards and protocols for promoting privacy, choice, and the secure, interoperable transfer and maintenance of sensitive data.​

 
IMP_1_16_tiede2_tutkija.jpg
 

MIIMU AIRAKSINEN

Research Professor and Doctor of Engineering (Structural Engineering) Miimu Airaksinen is familiar with the challenges and strengths facing the Finnish and European construction sector.

Her research at VTT is focused on the eco-efficiency of the built environment and the future priorities of the construction sector. She is also a member of Finland’s climate panel and a UN Habitat advisor. She has been highly active in developing the Smart Building and Smart City concepts and user studies.​

 

References

[1] European Commission, 2013, Report for the European Parliament: Mapping Smart Cities in the EU. IP/A/ITRE/ST/2013-02.
[2] OECD, 2012, OECD Environmental Outlook to 2050, OECD Publishing.
[3] SBA Sustainable Building Alliance, 2009, Common Carbon Metric. For Measuring Energy Use & Reporting Greenhouse Gas Emissions from Building Operations. UNEP SBCI. http://www.sballiance.org/dldocuments/common-carbon-metric2009.pdf.
[4] EPA, United States Environmental Protection Agency, 2014, What is sustainability?, http://www.epa.gov/sustainability/basicinfo.htm
[5] Hollands, RG. 2008, Will the real smart city please stand up? City 12, 3, (December 2008), 303-320. DOI=http://10.1080/13604810802479126.
[6] Allwinkle, S. and Cruickshank, P. 2011, “Creating smarter cities: an overview,” Journal of urban technology, 18, 2, (April 2011), 1-16. DOI=http://10.1080/10630732.2011.601103.
[7] Malek, JA. 2009, Informative global community development index of informative smart city, Proceedings of the 8th WSEAS (World Scientific and Engineering Academy and Society) international conference on education and educational technology. 17–19 October 2009, Genova, Italy. ISSN: 1790-5109.
[8] European Commission, 2013, EIP SCC, European Innovation Partnership on Smart Cities and Communities, Strategic Implementation Plan, 14.10.2013, http://ec.europa.eu/eip/smartcities/
[9] Giffinger, R., Fertner, C., Kramar, H., Meijers, E., Pichler-Milanovic, N., 2007, Ranking of European medium-sized cities, Final Report, Vienna, 2007.
[10] Gonzales, J.A. and Rossi, A., 2011, New trends for smart cities, open innovation mechanism in smart cities, European commission with the ICT policy support programme.
[11] Nam, T. & Pardo, T.A., 2011, Conceptualizing Smart City with dimensions of technology, people and institutions. In 12th Annual international conference on digital government research, 12-15 June, College Park, MD.
[12] Canadian Environmental Assessment Agency. 2013, “Cumulative Effects Assessment 
Practitioners’ Guide,” http://www.ceaa-acee.gc.ca/default.asp?lang=En&n=43952694-
[13] GSMA 2013, Guide to Smart Cities. The Opportunity for Mobile Operators. http://smartcitiesindex.gsma.com/indicators/
[14] Colldahl, C., Frey, S., Kelemen, J. E., 2013, “Smart Cities: Strategic Sustainable Development for an Urban World,” School of Engineering. Blekinge Institute of Technology. Karlskrona, Sweden.
[15] Lövehagen, L., Bondesson, A., 2013, Evaluating sustainability of using ICT solutions in smart cities – methodology requirements. ICT4S 2013, International Conference on Information and Communication Technologies for Sustainability. pp. 175-182.
[16] Airaksinen M., Ahvenniemi H., Virtanen M., 2012, “Smart City Key Performance Indicators,” European Energy Research Alliance, EERA, Join Program Energy in Cities status Report.
[17] Hiremath, R.B., Balachandra, P., Kumar, B., Bansode, S.S. and Murali, J., 2013, Indicator-based urban sustainability – A review. Energy for Sustainable Development 17 (2013), 555-563.
[18] McManus, P., 2012, Measuring Urban Sustainability: the potential and pitfalls of city rankings, Australian Geographer, Vol. 43, No. 4, pp. 411-424.
[19] Nielsen, Per Sieverts; Ben Amer, Sara and Halsnæs, Kirsten. 2013, TRANSFORM-project. Definition of Smart Energy City. Deliverables 1.1. and 1.2. Technical University of Denmark, DTU.
[20] SCOPE, 2007, Sustainability Indicators: A Scientific Assessment. Edited by T. Hák, B. Moldan and A.L. Dahl. Washington: Island Press. 2.
[21] Kolk, A., 2004, “A Decade of Sustainability Reporting: Developments and Significance.” International Journal of Environment and Sustainable Development 3, no. 1 (2004): 51-64.
[22] Fortune, Joyce and Diana White, 2006, Framing of project critical success factors by a systems model. International Journal of Project Management 24 (2006) 53–65.
[23] European Commission, 2006, “Directive 2006/32/EC of the European Parliament and of the Council of 5 April 2006 on energy end-use efficiency and energy services and repealing Council Directive 93/76/EEC,” Official Journal of the European Union.
[24] Forsström, Juha; Lahti, Pekka; Pursiheimo, Esa; Rämä, Miika; Shemeikka, Jari; Sipilä, Kari; Tuominen, Pekka; Wahlgren, Irmeli, 2011, Measuring energy efficiency. Indicators and potentials in buildings​, communities and energy systems. VTT.
[25] DOE, 2010, Department of Energy, United States of America, “Data access of privacy issues related to smart grid technologies,” October 5, 2010, http://www.energy.gov/sites/prod/files/gcprod/documents/Broadband_Report_Data_Privacy_10_5.pdf​

 


 

 

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