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Towards the preparation of the Guadalajara’s SmartCity Metrics Structure

Vázquez-Castañeda, C, Estrada-Guzman, E,

IEEE Guadalajara Metrics for Smart Cities Working Group

Abstract— Since 2013, Ciudad Creativa Digital (CCD) project is developing a plan to prepare the Guadalajara, Jalisco to become the first smart city in Mexico. One of the important parts of the process is the development and implementation of a metrics structure. Based on the study of the metrics used in other smart cities around the world, the Guadalajara’s metrics framework will be used for monitoring the activity of the city. The objective of this document is to present the main plan of the metrics structure preparation and some of its characteristics.

Index Terms— Ciudad Creativa Digital, Guadalajara, Key Performance Index, Metrics, Smart Cities.

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1 INTRODUCTIONHE number of people living in cities is increasing every year; by 2030 it is estimated that 60% of the

human population will be living in cities and 70% by 2050 [1]. It implies that the role of the cities in the life of the people will be an important issue for the next years. Lo-cal governments are deciding to embrace the idea of be-ing a smart city to offer better services, generate a better economic environment and improve their infrastructure. In Mexico, some cities have embraced the principal con-cepts of the smart city model to their public functions, but still in a minor grade. However, in November 2013 the federal government released the Estrategia Digital Nacional (National Digital Strategy), which consists in a 5-year national action plan for the adoption and development of the information and communication technologies as part of the Gobierno Cercano y Moderno (Closer and Modern Government) program. The initiative will prepare the environment for an easier smart city transition around Mexico [18]. In Guadalajara, our city is experiencing the process of the Ciudad Creativa Digital (Digital Creative City); a new clus-ter focused to impulse the digital industry in Mexico and to promote it as the first digital hub for Latinamerica. The GDL CCD master plan, developed by a multidisciplinary group from the Massachusetts Institute of Technology (MIT), contains the project strategies which at the end will result in an important cluster to impulse an intelligent urban development with a high-tech profile. GDL CCD will be an important base to prepare and implement the smart city model for Mexico and Latin America. The aim of this document is to present the main strategy

of the Guadalajara’s Smart City Metrics Structure and offer a brief description of the Guadalajara’s Smart City Framework to process the gathered urban information.

2 CONTEXT 2.1 Mexican Digital Strategy The Mexican Digital Strategy is a document where gov-ernment introduces the actions that will be implemented during the next years to prepare the adoption and devel-opment of the Information and Communication Technol-ogies. The principal purpose is to impulse the digitaliza-tion in Mexico to maximize the economic, social and poli-tic impacts. The principal objectives of the Mexican Digital Strategy are to promote a governmental transformation, to im-pulse a digital economy, to offer a high-quality education, to implement a universal healthcare and to ensure the safety of their citizens. To achieve the goals, the Mexican Digital Strategy proposes enablers as digital connectivity, digital skills, a strong interoperability, a strong legal framework and an open-data policy [18].

2.2 GDL CCD Strategy The Guadalajara Ciudad Creativa Digital (GDL CCD) will advance Mexico's natural position as a global leader in content production while providing a world-class envi-ronment for Mexican and overseas talent. GDL CCD will also push the boundaries of sustainable integrated urban development, providing a new model of economic cluster development that can be replicated across the country and Latin America. This initiative has support across the political spectrum and showcases, where local and federal authorities are

xxxx-xxxx/0x/$xx.00 © 200x IEEE Published by the IEEE-CCD Smart Cities

———————————————— • C. Vazquez is with the ITPhD CUCEA - Universidad de Guadalajara, CO 45100. E-mail: vazquez.carlos@cucea.udg.mx

• E. Estrada is with the ITPhD CUCEA - Universidad de Guadalajara, CO 45100. E-mail: estrada.elsa@cucea.udg.mx

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sharing the objective of enabling the digital creative in-dustry. This project is one of the cornerstones of Mexico's economic growth agenda [20].

2.3 Stakeholders One of the most important aspects in a smart city metrics is the definition of the stakeholders. The stakeholders are the principal actors of a smart city implementation, and at the same time are the first beneficiaries and the first af-fected. It is crucial for a correct smart city process to de-termine the responsibilities and tasks of each participant; the smart city metrics will depend on the performance of each stakeholder [6]. Government dependencies, contracting authorities, pro-ject managers; operators and citizens are some of the principal city stakeholders. Success of the smart city will depend on the availability and the immediate analytics of the information produced by the stakeholders.

3 WORKING GROUP MISSION & VISION The mission of the Guadalajara’s Smart City Metrics group is to prepare an open-data structure of metrics for the city to verify the status of the indicators, to analyze the correlation between indicators and KPI’s, to improve the city performance and to share the metrics structure with other cities to develop standardization.

The vision of the Guadalajara´s Smart City Metrics group is to have a complete structure of metrics for the metro-politan area by the end of December 2014 and start a real-time analysis of the KPI’s with inputs from the Open Data Framework by the second half of 2015.

4 SOURCES OF DATA FOR GUADALAJARA’S SMART CITY STRUCTURE

Fig.1. Guadalajara’s Smart City data sources.

The principal sources for the KPI’s will be the Guadalaja-ra’s government dependencies and some other private and public institutions certifying the validity and veracity of the information. Furthermore, data extracted from the Internet must complement the indicators. The Smart City model requires an open data environment for its implementation; this is an important area oppor-tunity, since the government is still developping such procedures. According to the five Star Open Data model, our first steps will be related to one-star level model, where data is visible, licensed for reuse but requires con-siderable effort to extract value [21]. Semantic analysis will be required to detect metrics inside documents and define the different layers of indicators.

5 STATE OF THE ART IN METRICS Measuring is a fundamental issue since it improves quali-ty of life by understanding the city performance in four key areas: talent, innovation, connections and distinc-tiveness [4]. City metrics require standard specifications; methods and strategies to enable compare cities under the same framework [7]. One of the first tasks in the preparation for a smart city is to detect the target objects of evaluation called functions or categories or areas, encompassing indicators to gauge since environment until the level of services requirements to handle a growing urban zone. There are different approaches and benchmarks to measure and describe in smart cities. Nevertheless, the main objective is to find measures to understand the city performance, discover underlying trends, compare characteristics and identify strengths and weaknesses of the city in a comparative way, in order to measure the development of Intelligent Communities. The smart city area configurations could present some varia-tions depending of different factors. China generated a city plan in 2011 where they visualize a smart city as a model with four areas: citizen, enterprise, government and infra-structure. Meanwhile Shanghai published its first release smart city benchmarks considering four factors: Informatiza-tion, Integrated Competitive Capability, Green and Low Carbon, Culture and Technology, in grouping by five di-mensions, 19 second layers indicators and 64 third layer indicators [17]. Other study published in 2011 presented a collection of di-versity indexes listed each according to the area of urban performance as: Finance, Economy, Quality of life, Technol-ogy, Environment [11]. This urgency of measuring and monitoring city performance and quality of life, have been detected by the Global City Indicators Facility. Such indica-tors enable cities to measure, report and improve areas of city services and quality of life with a success case devel-opped at the University of Toronto, Canada. The indica-tors are structured around 20 topics, e.g. Education, Ener-gy, Civic Engagement, Culture, Health, Governance, Transportation, Solid Waste, among others [14].

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The survey Global Power City Index is a matrix com-posed of city actors and functions indicators, which eval-uates and ranks the comprehensive power about forty major cities. The evaluation is based on six functions: Economy, Research & Development, Cultural Interaction, Livability, Environment and Accessibility, and four global actors who are leading global activities in their cities: Managers, Researchers, Artist, Visitors and Residents [8, 16]. The Province of Ontario, Canada inside The Intelli-gent Community Forum defines five critical success fac-tors for the creation of Intelligent Communities: Broad-band connectivity, Knowledge workforce, Digital Inclu-sion Innovation, Marketing and Advocacy. In addition to its Intelligent Community Indicators, ICF has identified factors that distinguish the most successful Intelligent Communities as Collaboration, Leadership and Sustaina-bility [19], while other groups presents a model where city has alternative capabilities like connected, entrepre-neurial, livable and pioneer city [2].

Fig.2. Guadalajara’s Smart City Metrics Structure diagram.

The implementation of the areas for the Guadalajara´s structure is based on the study of several city develop-ments, looking for the more standardized and shareable configuration.

6 METRICS FOR SMART CITIES FRAMEWORK The Guadalajara’s Smart City Data Framework is the mod-ule that will collect the stakeholder’s information defined in the implementation of the metrics structure; this module will be responsible of the indicators surveillance. Moreover, framework will lead the data intelligence procedures to optimize the city operations according to the indicator’s behavior; this is the reason why it is vital to implement a robust metrics structure [5].

The first step to establish the Guadalajara Smart City Metrics Structure was to declare the areas or sections of study. After a revision of other city structures, we decided to use a simi-lar structure based in the Cohen´s Smart Cities Wheel [9]. The areas of study for Guadalajara will be smart people, smart economy, smart environment, smart government, smart living and smart mobility. The next level of definition is related to the sources specifica-tion for each area; the meticulousness of this step is im-portant because the principal actors of the city and the own-ers of the information for the smart city structure will be declared at this point. Once every possible metric has been related with the structure, the next step is to find the metrics that could be used as a Key Performance Indicator (KPI).

7 KPI’S: INDEX DEFINITIONS AND CORRELATIONS The Key Performance Indicator (KPI) is a performance measurement, which evaluates the effectiveness of a specific metric, allowing the quantification of the goals progress. For a smart city implementation, the KPI definition is related to the important metrics for the city management. The use of KPI’s allows the identification of issues and improvements in the performance of the city. However, the correct use of the KPI’s depends on the data quality and how fast can be acquired and processed. The use and analysis of the data framework will allow us to detect correlations between the city indicators; nevertheless, the analysis implies to prepare the complete structure to deduce the implications between KPI’s. The data intelli-gence algorithms will deduce the factors related to each index of our metrics. Despite the local data sources, most of the KPI’s detected in other cities can be implemented in Guadalajara, where the correlation of metrics could present a variation from city to city.

8 OPEN DATA FRAMEWORK PREPARATION The goals of the Open Data Framework are to provide an open data plataform, enable people to build on open data from Guadalajara living labs. Such data sources must have a national legislation for freedom of information, with standard reporting protocols. The creation of incen-tives for the open data framework is needed in order to promote the data sharing for goods between business and citizens as well as promoting collaboration among uni-versities, government, and industry. The framework of the Guadalajara’s Smart City Metrics resides over components that proceed from different layers, based on standars, tools, metodologies and stake-holders. These will be integrated into the context of local collaboration in working groups. As a reference, see the roadmap presented in fig. 3. Standars are defined toward tree layers: 1) File structures which include JSON, XML and CSV formats. 2) Protocols

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over TCP/IP as CAP (Common Alert Protocol) simple version, RESTFUL (Representational state transfer), MQTT machine-to-machine (M2M)/"Internet of Things" connectivity protocol. 3) Kind of storage criteria as the flow of continuos data and periodic subset of data. Tools and methodology aim to enable the physical infra-structure for repositories storage (BigData or compatible), enought network bandwidth for the access, scalable archi-tecture, and mirrors or backups of information. A Web portal to provide access to the repository is considered, in order to manage and support to users, security, privacy, and implementation of policies. The methodology must include the management and the scale of data reposito-ries. Stakeholders are integrated by: IEEE Physical Infrastruc-ture Working Group, IEEE Inernet of Things Working Group, Data Visualization and Analytics Working Group, Government, Industry (Analytics and Enterpreuners), Researchers, and Citizens.

The next step is to prepare a deep revision of each metric to define its properties; status of implementation, fre-quency of change, intervals of performance, units of measure, etc [3]. By this time the Data Framework will be ready to start working at some percent of capacity, ac-cording to the information provided by the stakeholders, with the understanding that missing data should be available at a specific date.

9 BEST PRACTICES The interest of the cities to become a smart city has grown in the last years. The city governments have experienced the benefits of the technology applied to the city opera-tions; moreover, citizens perceive the improvement on the services, operations, economy and quality life [12]. Every year the number of smart cities is increasing and each city is in a different level of implementation. To verify the

advance in the process, cities are analyzed according to core areas of interest [10]. The Department for Business, Innovation and Skills in the United Kingdom propose the analysis of areas as govern-ance, geographic and cultural spread, access to infor-mation, open data polycies, investment priorities, etc. They selected cities as Chicago, Rio de Janeiro, Stock-holm, Boston, Barcelona and Hong Kong as the cities with the best score [13]. Besides, the Institute for Urban Strate-gies at The Mori Memorial Foundation presents a ranking based on areas as economy, research and development, cultural interaction, livability, environment and accessi-bility. Their Global Power City Index 2013 presents Lon-don, New York, Paris, Tokyo, Singapore, Seoul, Amster-dam, Berlin, Vienna and Frankfurt as the first 10 cities with the best general ranking [16]. It is important to no-tice that each list introduces different cities, and also it changes its nominees year by year [8].

10 GUADALAJARA SMART CITY PROCESS The next table is a roadmap of the Guadalajara’s metrics definition. Process is programmed for the next 12 months starting from January 2014.

TABLE 1 ROADMAP OF THE GUADALAJARA’S METRICS DEFINITION.

 

Janu

ary  

Februa

ry  

March  

April  

May  

June

 

July  

August  

Septem

ber  

Octob

er  

Novem

ber  

Decembe

r  

Best  practices  analysis                                                  Metrics  benchmarking  of  the  selected  cities                                                  Guadalajara´s  stake-­‐holders  definition                                                  Smart  people  indica-­‐tors                                                  Smart  Economy  indi-­‐cators                                                  Smart  Environment  indicators                                                  Smart  Government  indicators                                                  Smart  Living  indica-­‐tors                                                  Smart  Mobility  indica-­‐tors                                                  Guadalajara's  metrics  structure  (first  draft)                                                  Data  availability                                                  Guadalajara's  metrics  structure  (second  draft)                                                  Guadalajara  KPI's                                                   This is the brief description of the roadmap. The activities to achieve the goals are contained in the complete ver-sion.

Fig. 3 Roadmap for the open data framework in 2014

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11 CLUES FOR THE SUCCESS The Guadalajara’s Smart City Metrics Structure will con-tain some of the metrics and KPI’s of the cities ranked in the previous lists; it is important to contemplate some other cases as China’s cities, where the smart city imple-mentation process is generating a lot of important infor-mation. Data surveillance of other cities will be part of the daily routine, verifying new developments around the world [15]. One of the most important challenges in the preparation of Guadalajara as a smart city is to persuade government about the importance of an open-data culture. CCD has established a direct dialog with the Guadalajara city council to prepare the transition on dependencies. This process will allow complementing the metrics structure, determining which metrics are already available and which metrics should be extracted from other places. At the same time, private institutions will be contacted to ask for specific information for complementing the metrics.

12 PERSPECTIVES The next step is to send an invitation for the local univer-sities to generate work groups that could help in the defi-nition of the metrics structure. It is necessary to build 6 multidisciplinary groups, one for each area. Other important step is to prepare the design of the visual interfaces for the Data Framework. Even when data analysis offer the information that we need, the interfaces allow citizens to follow the city performance and how every action can impact, stimulating the participation of the people in the data providing.

ACKNOWLEDGMENT The authors wish to thank the Guadalajara Ciudad Crea-tiva Digital A.C. (GDL CCD) organization for their sup-port sharing its vision and take care of the working groups initative, especially Octavio Parga as President and Victor M. Larios as Science and Technology Director. Also, we thank the IEEE Guadalajara Section volunteers, CANIETI Occcidente and their associated Industry in Mexico, PROMEXICO and CONACYT for their support. A special thank for the Universidad de Gualdajara and its PhD in Information Technologies program providing PhD Students, the advice of professors, facilities and acces to information databases.

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