- Email: [email protected]
Knowledge society technologies for smart cities development
CHAPTER
Knowledge society technologies for smart cities development
11
Raquel Pe´rez-delHoyo1, Higinio Mora2 Department of Building Sciences and Urbanism, University of Alicante, Alicante, Spain1; Department of Computer Science Technology and Computation, University of Alicante, Alicante, Spain2
Chapter outline 1. Knowledge society in the new era .......................................................................185 2. Knowledge society and new technologies in the governance of cities ...................186 3. Technologies for smart urban planning: a citizen-centric approach .......................188 4. Conclusions .......................................................................................................194 Acknowledgments ...................................................................................................194 References .............................................................................................................195
1. Knowledge society in the new era The world is immersed in the era of the knowledge society. Unlike the information society, the knowledge society goes further and is able to transform this information into solutions that allow effective actions to be taken to improve society. In such a way, this knowledge society is based on the generation, distribution and use of knowledge to improve the quality of life of citizens. The technologies that have played an essential role in this development correspond to the area of information and communications technologiesdICT. They are the set of technologies that allow us to interact with the digital world and analyze the data acquired from it. The set of technologies reviewed in this chapter are the new communication technologies, the geopositioning services, and cloud computing paradigm. All of these technologies working in a combined way allow enabling new forms of building the knowledge society. Currently, there are many applications of the knowledge society in the real world. Perhaps, one of them that has contributed more to the increased of wellness of the citizens is the smart city concept. A smart city can be defined, therefore, as a model of urban management able of responding to the problems and needs of 21st century cities, which arises as a result of the development of the current knowledge society and its technological environment. Smart Cities: Issues and Challenges. https://doi.org/10.1016/B978-0-12-816639-0.00011-9 Copyright © 2019 Elsevier Inc. All rights reserved.
185
186
CHAPTER 11 Knowledge society technologies for smart cities
There are many smart city applications oriented toward improving the life of citizens (Gilart-Iglesias et al., 2015; Mora et al., 2017; Chen and Tsai, 2018). In this chapter, we put the focus on the urban planning of the city as one of the key processes to handle the sustainable and integrated development of today’s cities. The concept of “smart urban planning” (Babar and Arif, 2017) mainly relies on conducting this task aided with new knowledge technologies. The remaining part of this chapter is organized as follows. Section 2 describes the connection between the knowledge society and new technologies in the governance of cities. Next, Section 3 introduces the smart urban planning concept, and finally, we conclude the chapter in Section 4.
2. Knowledge society and new technologies in the governance of cities The ICT and the knowledge society have definitely changed the way in which citizens relate to the city (Mueller et al., 2018) and the way in which its management is carried out, and this new way of developing activities in the city also implies a change and modernization of their public institutions. This means, as shown in Fig. 11.1, that the smart city model only makes sense if it is linked to innovation to define a future city project to ensure together, in a balanced manner, the social sustainabilitydcohesion and social development, the economic sustainabilityda competitive economic strategy, the environmental sustainabilitydawareness and care for the environment, and the accessibilitydsocial integration. Within this context, it is clear that the concept of city governance requires major changes to respond to the new realities. The knowledge society and the latest technologies play an essential role in the governance of the city and its objective of achieving a sustainable economic, social, and institutional development, by promoting an intelligent balance between institutions, civil society, and the economy market. For this purpose, a smart city model allows governance to progress from its traditional structures to a greater relationship between public institutions and their environment (Meijer and Rodrı´guez-Bolı´var, 2016).
FIGURE 11.1 Smart city model and sustainable urban development.
2. Knowledge society and new technologies in the governance of cities
The possibilities offered by new technologies to maintain an efficient political and administrative structure are well known by public opinion: to facilitate the management of the city among the different administrations or institutions, to optimize the management of services and resources, to speed up administrative procedures and proceedings, to provide citizens with access to basic services, and to promote a sense of citizenship and citizen participation (Hanna, 2010; Lv et al., 2018; Lytras and Visvizi, 2018). In addition, new technologies allow connections for greater political, social, economic, cultural, and ideas exchange with other cities at all levels of government. In the field of urban planning, the planning and design of cities nowadays cannot be understood without the participation of citizens. Increasingly, an informed citizenry constitutes an active citizenry capable of self-organizing, having an opinion, and making the best decisions about the matters that affect the community. Therefore, beyond the urban development projects’ conventional periods of public exhibition established by law, it is necessary to set in motion innovative citizen participation processes before any urban development project has begun its development. The benefits of ICT for this purpose are very important and varied (Alfaro et al., 2017). For example, they can provide citizens with web 2.0 platforms that allow them interact and discuss the projects that should be developed with priority in the city or with citizens’ mailboxes in each website to facilitate consultations or suggestions on any matter related with the city, in addition to offering information on any urban project in all its phases of development. Knowledge is no longer found especially in a given space, and civil society plays an essential role in its production (Cossetta and Palumbo, 2014). People are the main source of information to build knowledge about the real problems and needs of the city they inhabit. It is only necessary to offer an effective channel of communication between citizens and public institutions to obtain, directly and in real time, accurate and up-to-date information about the experience of citizens in the city, the problems they perceive, and their priority (Dameri, 2017). The latest technologies are the key for developing these communication channels, which must be accessible and simple to usedthrough intuitive applications for mobile devices, for exampledso that they can be distributed among the greatest number of citizens. In this way, it is possible to obtain up-to-date information and build knowledge on any issue that affects the public space in the city: urban accessibility, operation of urban facilities and services, operation of public transport, cycle and pedestrian paths, and needs in specific environments such as schools or parks in certain time bands. In addition, involving citizens in solving the problems of the city allows neighbors to identify with their neighborhood and feel it as their own, preventing its abandonment and long-term deterioration (Jasso and Petrı´kova´, 2016), which also means the improvement of the relationship with the nearby neighborhoods and with the rest of the city. The democratization of urban planning and the active citizen participation processes are mechanisms against exclusion and for social development (Pearce, 2010).
187
188
CHAPTER 11 Knowledge society technologies for smart cities
Therefore, the commitment to social cohesion finds an important space in the city of the knowledge society, where citizens interact by developing more participative and interactive dynamics, with each other and with the city, thanks to technology, even allowing their habits, preferences, and positioning are known. Knowing citizen traceability, i.e., the level of use that citizens make of public spacedwhat obvious and not-so-obvious places they use to develop a specific type of activity such as running, riding a bicycle, or doing other sportsdallows, for example, the inclusive spaces of a city to be identified, i.e., the spaces used by all people regardless of their abilities or profiles, as well as learning from these spaces to serve as urban design models (Pe´rez-delHoyo et al., 2017). This information allows for better planning of the city, not only respecting those habits and preferences but also discovering new singularities and opportunities. These initiatives set in motion management dynamics within the context of the smart city that contribute to social cohesion and the empowerment of citizens. On the other hand, knowing the habits and preferences of citizens helps us to plan and design the smart city (Mora et al., 2015; Lenormand and Ramasco, 2016). The role of citizens has changed definitively by participating in what researchers have started to refer to as an “urban planning of ideas.” For this purpose, the virtual space is a new social space, and specialized social networks are a very powerful source of information. But the city of the knowledge society can go a step further, by adapting itself to citizens instead of citizens having to adapt to the city. The latest technologies allow citizens to be identified when they approach an urban environment and transform some of its elementsdsuch as traffic lights, information panels, or othersdto facilitate the use of these environments by citizens according to their abilities (Pe´rez-delHoyo et al., 2016). All these initiatives are part of the smart city project, thanks to technology (Etezadzadeh, 2016). In short, in the field of cities’ government, it is a need to humanize the smart city concept and work on initiatives that relates to the citizen as a receiver of actions that improve quality of life and serve to acquire information for planning and designing smart cities. In this way, it is a challenge for the government to move toward a type of city that could be called “citizen-centric smart city”, in which a circular relationship between administrators and citizens is built to improve their quality of life, focused on their needs, habits, and preferences. Fig. 11.2 illustrates this idea.
3. Technologies for smart urban planning: a citizen-centric approach From the point of view of urban planning, the smart city is a new urban model based on knowledge in a deep research exploration and a wide application of the latest information and communication technologies (Kummitha and Crutzen, 2017).
3. Technologies for smart urban planning: a citizen-centric approach
FIGURE 11.2 Citizen-centric smart city.
An urban development model aims to solve real problems and needs and pursues specific objectives and strategies. It is the reflection of the evolution of a society and draws a vision for the future city by answering the questions: what kind of place do we want the cities to be? and how should the goal of quality of life be defined? (Saaty and De Paola, 2017). As already mentioned in previous section, the smart urban planning concept, within the context of smart city, cannot be understood without citizen participation. The knowledge society and the latest information and communication technologies have transformed the traditional meaning of citizen participation, by placing people at the center of planning, design, and management of the cities of the future (Castells, 2011). Consequently, we are witnessing a reformulation of the urban planning paradigm (Landry, 2016; Marsal-Llacuna et al., 2011). Urban planning becomes a process where the city learns from itself and from the people’s habits, needs, and desires. A process that uses the imagination and collective intelligence of citizens cocreate and shape the city of tomorrow. This citizen-centric approach is critical for the future of urban planning within the context of smart city. A wide and proper use of technology is essential for urban planning to push ahead in this direction. The new information and communication technologies, the geopositioning services, and cloud computing paradigm offer new opportunities for cities to be smarter and more sustainable. Fig. 11.3 schematically draws this idea. This recurring idea is discussed in this section. The discussion is conducted by the analysis of some current approaches and the study of some real cases on how technologies can improve urban design and planning processes. One of the core urban initiatives in which technologies have facilitated new opportunities has been to give citizens a voice to express their opinion on the projects that are carried out in the city. For this purpose, ICT provide institutions with open public debate spaces on the internet where citizens, anonymously or as registered users, can comment and contribute ideas to improve their city. Good examples of these initiatives are some projects developed by some municipalities
189
190
CHAPTER 11 Knowledge society technologies for smart cities
FIGURE 11.3 Key technologies in urban planning for smart city.
in Portugal: the e-Democracy Service supported by a Geographical Information SystemdGISddeveloped for the public discussion of Oporto’s Municipal Master Plan (Oliveira et al., 2004) and the use of an interactive discussion map for public discussion of Lisbon Master Plan (Pina, 2012). In both projects, GIS technologies have served to drive public participation processes. Geographic Information Systems in Public ParticipationdPPGISdis an area with an increasing importance in the context of Geographic Information Science. These technologies have been used on a larger scale for a large number of different and varied projects, for example, to elicit information on outdoor places important to citizens in Wiltshire, England (Ridding et al., 2018); for the environmental planning and management of Mt. Baker-Snoqualmie National Forest in western Washington, USA (McLain et al., 2017); and for analyzing how landscape values are perceived by citizens in different areas of Europe (Garcia-Martin et al., 2017), among many others participatory mapping studies. The relationship between GIS and the knowledge society has allowed participatory mapping methodologies to be implemented. Mapping exercises are capable of providing communities with useful information. Processes for informing citizens in real time about the number of urban opportunities in a particular urban area, i.e., information on shops, facilities and services available, cultural routes and itinerary,es, up-to-date traffic or public transport
3. Technologies for smart urban planning: a citizen-centric approach
information, are also possible, thanks to ICT technologies. Knowing this information allows citizens to make smarter use of the opportunities offered by a city, reduce transport times, and use the appropriate services at any particular time. This intelligent use of the services and resources of a city is more in line with the principles of sustainable urban development. Processes for informing citizens have been mainly based on the calculation of close relationships and intensities of use, and they have been primarily supported by Global Positioning Systems technologiesdGPSd for positioning and GIS technologies for displaying data and spatial analysis. There are many projects recently developed in this field, for example, a smart decision support system determining the most efficient way to plan the tourist itineraries. Operations are managed through a mobile app/website. The system was implemented in the city of Melbourne, Australia (Bagloee et al., 2017). Another recent initiative funded by the German Government is about providing citizens with personalized, context-aware intermodal travel information. The aim of the initiative is to enhance travel information systems by analyzing the available itineraries to better suit the traveler, based on his personal preferences, context information, and popular selections (Samsel et al., 2016). On the other hand, urban geospatial data allow local industry and public institutions to develop applications that improve life of citizens. Therefore, the management of geospatial data is a big challenge for smart cities. Emerging technologies such as Semantic Web technologies to build up relations and connections between concepts, or open data web applications with well-performing search engines, can help public institutions to contextualize geospatial data by transforming the general information into useful knowledge. This knowledge will enable citizens, businesses, and public institutions to codesign new public information services to participate and understand what is going on in their city. In addition, geospatial data and open data are often used within the context of big data (Wu et al., 2018). Therefore, the use of cloud technology is almost mandatory. In line with this approach, some projects have been developed, for example, the European Union funded Project Smarticipate (Smarticipate Project, 2018), which is driven by the pilot cities of London; Britain; Rome, Italy; and Hamburg, Germany, with the aim of empowering citizens and businesses and fostering their involvement in the city’s governance system. The development of iterative processes in the field of the participatory urban planning and user-centered design of applications are some of the actions that have been carried out (Vogt and Fro¨hlich, 2016). Moving on to other issues, the knowledge of the people’s habits, preferences, needs, and desires is an essential factor for the smart urban planning within the context of smart cities. The study of urban places preferred and citizens’ movement patterns supports a better understanding of modern cities and enables a more comprehensive strategy for urban planning (Mora et al., 2015). In line with this overall vision, a wide range of studies has been developed, for example, using GPS and mobiles devices to analyze the movement patterns of taxis
191
192
CHAPTER 11 Knowledge society technologies for smart cities
between different urban areas in Beijing, China (Chen et al., 2017); the sociospatial and temporal complexities of older adults’ mobility in Metro Vancouver, Canada (Franke et al., 2017); or the spatial behavior of backcountry skiers in Tatra National Park, Poland (Taczanowska et al., 2017). The large development of ICT allows us to interact with an urban environment providing a huge amount of data and information about the cities we live in (Bohn et al., 2004). In these cases, the cloud is an essential tool for conducting advanced data analytics (Babar and Arif, 2017). Internet of things (IoT) devices, smart phones location data, and smart cards data have been used in a large number of urban planning initiatives within the context of the hyperconnected society and the big data phenomenon. Big data has aided understanding of human mobility (Lu et al., 2017). For example, to explore the spatial distribution and density of recreational movement in multiple-use urban forests in Helsinki, Finland (Korpilo et al., 2017) or the bike-sharing travel patterns and purposes in New York City (Bao et al., 2017). Much research on Geo-IoT technologies has been conducted even to described future scenes (Kim, 2018). The study of the citizens’ mobility has seen significant growth due the prevalence of mobile devices. By combining these data with the city’s points of interests, both travel patterns and purposes can be known. Increasingly, the methods for addressing the aspects that affect the functioning of the city are based on evidence, i.e., in the study of the citizens’ behaviors. For this purpose, many methodologies have been developed, for example, to improve urban accessibility for people with disabilities, a computational method based on new communications technologies (Gilart-Iglesias et al., 2015; Mora et al., 2017). The means of public transportdtrains, buses, and bike sharingd are also being continuously monitored with sensors that send important information about urban routes, travel times, and traffic intensity to the cities’ governments. A good example of this trend is the information system on the public transport of London, Britain (Ferrari et al., 2014). Actually, these participatory processes based on the analysis of urban dynamics are part of a challenging field of research to improve urban planning. To this end, some recent studies identify trajectories from origin-destination data and potential development axes (Bahbouh et al., 2017) and propose new algorithms to extract knowledge, i.e., patterns, rules, and regularities, from user trajectories (Cesario et al., 2017; Qian and Lu, 2017). On another level, sensor networks allow cities to monitor their environmental conditions and, therefore, not to make the mistakes of the past and move toward more sustainable development models. Environmental pollution monitoring is a major concern in the development of smart cities. Indeed, the World Health Organization launched the Global Platform on Air Quality and Health, for governments to collaborate in the development of strategies to reduce air pollution. Within this program, a lot of actions have been conducted. A recent example is the monitoring environmental parameters in the city of Pisa, Italy (Bacco et al., 2017). Urban noise has also been properly monitored to obtain useful information for urban planning. A good example of this initiative is the experience developed in the city of Dublin, Ireland (Alfaro Navarro et al., 2017).
3. Technologies for smart urban planning: a citizen-centric approach
FIGURE 11.4 Knowledge sources for understanding city needs.
However, as drawn in Fig. 11.4, the knowledge needed for city planning includes the physical, social, cultural, technological, and economic domains and incorporates multiple perspectives, such as the understanding of social and cultural dynamics and needs, to create new knowledge. A good deal of recent research concerns locative social networks as open sources of data to acknowledge which city places are preferred, used, and liveable. Some of these studies propose methodologies, for example, to identify city’s successful public spaces through the location-based social media network Foursquare (Martı´ et al., 2017); to discover popular tourist attractions within the urban areas through the Flickr geotagged images (Peng and Huang, 2017); or to depict urban boundaries with geolocated Twitter data (Yin et al., 2017). The generation of data and communication to the social network is usually done automatically through users’ mobile devices, such as smart phones and other wearables provided with GPS technology. In regard to this valuable information for the planning of cities, an important issue to be taken into account is how to show the data retrieved from different sources. Many studies focus on how visualization of social network data allows researchers and professionals from the field of urban planning to explore the relationship between citizens’ movements and activity distributions all over the city (Zeng et al., 2017). For smart urban planning, it is essential to understand the relationship between activities and human mobility. Given the pace of technology and the current use of mobile phones, there is a large amount of data that can be used to create high reliability models. In this regard, some of the studies referred to above propose novel data representations such as graphs to characterize spatial and temporal
193
194
CHAPTER 11 Knowledge society technologies for smart cities
people mobility (Wu et al., 2017). In addition, some studies propose visual analytics systems to measure opinion propagation, for example, among Twitter users (Xu et al., 2013), and others focus on the analysis of urban emotions (Resch et al., 2015, 2016). Comprehensive systems and solutions for smart urban planning and smart strategies for developing more resilient and sustainable cities (Falco, 2015; Mora et al., 2017; Visvizi and Lytras, 2018) have been proposed over the past few years. This has become a growing trend, and therefore, in a near future, other systems and solutions for smart cities will be suggested. All of these smart initiatives, which are aimed to help cities for a more sustainable development, are without a shadow of a doubt the result of the joint efforts and collaboration of different fields of knowledge.
4. Conclusions The accelerated technological development in recent years has transformed the way of living and understanding the world. As a consequence, the current knowledge society and its technological environment have brought profound social and economic changes. Today’s cities need to position themselves in a competitive global context and they have to assume a new lead role. The current context opens new possibilities for city development and allows adopting modern strategies to address their challenges. In this sense, the concept of smart city represents a model of urban development base on smart application of technology. To become it, cities may face a new key challenge, which is to begin incorporating technologies as a part of the urban organism. The concepts of ubiquitous and smart cities make use of processing technologies, sensing, and communications to provide intelligence to the city, while offering connectivity resources, power supply and interoperability. These conditions facilitate the deployment of interconnected smart elements that provide services to citizens for efficient decision-making and to make better use of resources. To consolidate this smart urban model, a commitment is required from the responsible for management and city government. Definitely, new technologies and communications solutions have revolutionized the way of knowing cities and, consequently, the way of planning and designing cities. Communication technologies, geographic information systems, and cloud computing paradigm are some of the most relevant technologies, which currently help cities move toward a smarter, more sustainable, and inclusive development model.
Acknowledgments This work has been funded by the Conselleria de Educacio´n, Investigacio´n, Cultura y Deporte of the Community of Valencia, Spain, within the program of support for research under project AICO/2017/134.
References
References Alfaro Navarro, J.L., Lo´pez Ruiz, V.R., Nevado Pen˜a, D., 2017. The effect of ICT use and capability on knowledge-based cities. Cities 60, 272e280. Babar, M., Arif, F., 2017. Smart urban planning using big data analytics to contend with the interoperability in Internet of Things. Future Generation Computer Systems 77, 65e76. Bacco, M., Delmastro, F., Ferro, E., Gotta, A., 2017. Environmental monitoring for smart cities. IEEE Sensors Journal 17 (23), 7767e7774. Bagloee, S.A., Tavana, M., Di Caprio, D., Asadi, M., Heshmati, M., 2017. A multi-user decision support system for online city bus tour planning. Journal of Modern Transportation 25 (2), 59e73. Bahbouh, K., Wagner, J.R., Morency, C., Berdier, C., 2017. Travel demand corridors: modelling approach and relevance in the planning process. Journal of Transport Geography 58, 196e208. Bao, J., Xu, C., Liu, P., Wang, W., 2017. Exploring bikesharing travel patterns and trip purposes using smart card data and online point of interests. Networks and Spatial Economics 17 (4), 1231e1253. Bohn, J., Coroama, V., Langheinrich, M., Mattern, F., Rohs, M., 2004. Living in a world of smart everyday objects-social, economic, and ethical implications. Human and Ecological Risk Assessment: An International Journal 10, 763e785. Castells, M., 2011. The Rise of the Network Society - the Information Age: Economy, Society, and Culture, vol. 1. John Wiley & Sons. Cesario, E., Comito, C., Talia, D., 2017. An approach for the discovery and validation of urban mobility patterns. Pervasive and Mobile Computing 42, 77e92. Chen, Z., Gong, X., Xie, Z., 2017. An analysis of movement patterns between zones using taxi GPS data. Transactions in GIS 21 (6), 1341e1363. Chen, Y.-S., Tsai, Y.-T., 2018. A mobility management using follow-me cloud-cloudlet in fog-computing-based RANs for smart cities. Sensors 8 (2), 489. https://doi.org/10.3390/ s18020489. Cossetta, A., Palumbo, M., 2014. The Co-production of social innovation: the case of living lab. In: Smart City: How to Create Public and Economic Value with High Technology in Urban Space. Springer, pp. 221e235. Dameri, R.P., 2017. Smart City Implementation: Creating Economic and Public Value in Innovative Urban Systems. Springer. Etezadzadeh, C., 2016. Smart City e Future City?: Smart City 2.0 as a Livable City and Future Market. Springer. Falco, G.J., 2015. City resilience through data analytics: a human-centric approach. Procedia engineering 118, 1008e1014. Ferrari, L., Berlingerio, M., Calabrese, F., Reades, J., 2014. Improving the accessibility of urban transportation networks for people with disabilities advances. Transportation Research Part C: Emerging Technologies 45, 27e40. Franke, T., Winters, M., McKay, H., Chaudhury, H., Sims-Gould, J., 2017. A grounded visualization approach to explore sociospatial and temporal complexities of older adults’ mobility. Social Science and Medicine 193, 59e69. Garcia-Martin, M., Fagerholm, N., Bieling, C., Gounaridis, D., Kizos, T., Printsmann, A., Plieninger, T., 2017. Participatory mapping of landscape values in a Pan-European perspective. Landscape Ecology 32 (11), 2133e2150.
195
196
CHAPTER 11 Knowledge society technologies for smart cities
Gilart-Iglesias, V., Mora, H., Pe´rez-delHoyo, R., Garcı´a-Mayor, C., 2015. A computational method based on radio frequency technologies for the analysis of accessibility of disabled people in sustainable cities. Sustainability 7 (11), 14935e14963. Hanna, N.K., 2010. Transforming Government and Building the Information Society: Challenges and Opportunities for the Developing World. Springer. Jasso, M., Petrı´kova´, D., 2016. Place attachment and social communities in the concept of smart cities. In: Smart City 360 . Springer, pp. 721e728. Kim, M.S., 2018. Research issues and challenges related to Geo-IoT platform. Spatial Information Research 26 (1), 113e126. Korpilo, S., Virtanen, T., Lehva¨virta, S., 2017. Smartphone GPS trackingdinexpensive and efficient data collection on recreational movement. Landscape and Urban Planning 157, 608e617. Kummitha, R.K.R., Crutzen, N., 2017. How do we understand smart cities? An evolutionary perspective. Cities 67, 43e52. Landry, C., 2016. The changing face of urban planning: towards collaborative and creative cities. In: Human Smart Cities. Rethinking the Interplay between Design and Planning. Springer, pp. 238e250. Lenormand, M., Ramasco, J., 2016. Towards a better understanding of cities using mobility data. Built Environment 42 (3), 356e364. Lu, S., Fang, Z., Zhang, X., Shaw, S.L., Yin, L., Zhao, Z., Yang, X., 2017. Understanding the representativeness of mobile phone location data in characterizing human mobility indicators. ISPRS International Journal of Geo-Information 6 (1), 7. Lv, Z., Li, X., Wang, W., Zhang, B., Hu, J., Feng, S., 2018. Government affairs service platform for smart city. Future Generation Computer Systems 81, 443e451. Lytras, M.D., Visvizi, A., 2018. Who uses smart city services and what to make of it: toward interdisciplinary smart cities research. Sustainability 10, 1998. https://doi.org/10.3390/ su10061998. Martı´, P., Serrano-Estrada, L., Nolasco-Cirugeda, A., 2017. Using locative social media and urban cartographies to identify and locate successful urban plazas. Cities 64, 66e78. Marsal-Llacuna, M.L., Leung, Y.T., Ren, G.J., 2011. Smarter urban planning: match land use with citizen needs and financial constraints. In: International Conference on Computational Science and its Applications. Springer, pp. 93e108. Meijer, A., Rodrı´guez Bolı´var, M.P., 2016. Governing the smart city: a review of the literature on smart urban governance. International Review of Administrative Sciences 82 (2), 392e408. McLain, R.J., Banis, D., Todd, A., Cerveny, L.K., 2017. Multiple methods of public engagement: disaggregating socio-spatial data for environmental planning in western Washington, USA. Journal of Environmental Management 204, 61e74. Mora, H., Gilart-Iglesias, V., Gil, D., Sirvent-Llamas, A., 2015. A computational architecture based on RFID sensors for traceability in smart cities. Sensors 15 (6), 13591e13626. https://doi.org/10.3390/s150613591. Mora, H., Gilart-Iglesias, V., Pe´rez-delHoyo, R., Andu´jar-Montoya, M.D., 2017. A comprehensive system for monitoring urban accessibility in smart cities. Sensors 17 (8), 1834. Mueller, J., Lu, H., Chirkin, A., Klein, B., Schmitt, G., 2018. Citizen design science: a strategy for crowd-creative urban design. Cities 72, 181e188.
References
Navarro, J.M., Tomas-Gabarron, J.B., Escolano, J., 2017. A big data framework for urban noise analysis and management in smart cities. Acta Acustica United with Acustica 103 (4), 552e560. Oliveira, M.A., Carvalho, A., Ba´rtolo, L., 2004. Public discussion of Oporto’s municipal master plan: an e-democracy service supported by a geographical information system. In: Third International Conference on Electronic Government. Springer, pp. 410e413. Pearce, J., 2010. Participation and Democracy in the Twenty-First Century City. Springer. Peng, X., Huang, Z.A., 2017. Novel popular tourist attraction discovering approach based on geo-tagged social media big data. ISPRS International Journal of Geo-Information 6 (7), 216. Pe´rez-delHoyo, R., Garcı´a-Mayor, C., Mora-Mora, H., Gilart-Iglesias, V., Andu´jar-Montoya, M.D., 2016. Making smart and accessible cities: an urban model based on the design of intelligent environments. In: 2016 5th International Conference on Smart Cities and Green ICT Systems. (SMARTGREENS), pp. 1e8. Pe´rez-delHoyo, R., Garcia-Mayor, C., Mora, H., Gilart, V., Andu´jar-Montoya, M.D., 2017. Improving urban accessibility: a methodology for urban dynamics analysis in smart, sustainable and inclusive cities. International Journal of Sustainable Development and Planning 12 (3), 357e367. Pina, I., 2012. Participac¸a˜o Pu´blica e SIG: Do potential a` pra´tica, da pra´tica aos resultados Discussa˜o Pu´blica do PDM de Lisboa (Doctoral dissertation). Qian, H., Lu, Y., 2017. Simplifying GPS trajectory data with enhanced spatial-temporal constraints. ISPRS International Journal of Geo-Information 6 (11), 329. Resch, B., Summa, A., Sagl, G., Zeile, P., Exner, J.P., 2015. Urban emotions: geo-semantic emotion ex-traction from technical sensors, human sensors and crowdsourced data. In: Progress in Location-Based Services 2014. Springer, pp. 199e212. Resch, B., Summa, A., Zeile, P., Strube, M., 2016. Citizen-centric urban planning through extracting emotion information from twitter in an interdisciplinary space-time-linguistics algorithm. Urban Planning 1 (2), 114e127. Ridding, L.E., Redhead, J.W., Oliver, T.H., Schmucki, R., McGinlay, J., Graves, A.R., Bullock, J.M., 2018. The importance of landscape characteristics for the delivery of cultural ecosystem services. Journal of Environmental Management 206, 1145e1154. Saaty, T.L., De Paola, P., 2017. Rethinking design and urban planning for the cities of the future. Buildings 7 (3), 76. Samsel, C., Krempels, K.H., Garbereder, G., 2016. Personalized, context-aware intermodal travel information. In: Proceedings of the 12th International Conference on Web Information Systems and Technologies, vol. 1. WEBIST 2016), pp. 148e155. Smarticipate Project, 2018. Funded Project by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 693729. https:// www.smarticipate.eu/. Taczanowska, K., Bielanski, M., Gonza´lez, L.M., Garcia-Masso´, X., Toca-Herrera, J.L., 2017. Analyzing spatial behavior of backcountry skiers in mountain protected areas combining GPS tracking and graph theory. Symmetry 9 (12), 317. Visvizi, A., Lytras, M., 2018. Rescaling and refocusing smart cities research: from mega cities to smart villages. Journal of Science and Technology Policy Management (JSTPM). https://doi.org/10.1108/JSTPM-02-2018-0020.
197
198
CHAPTER 11 Knowledge society technologies for smart cities
Vogt, M., Fro¨hlich, P., 2016. Understanding cities and citizens: developing novel participatory development methods and public service concepts. In: REAL CORP 2016eSMART ME UP! How to Become and How to Stay a Smart City, and Does This Improve Quality of Life? Proceedings of 21st International Conference on Urban Planning, Regional Development and Information Society. CORPeCompetence Center of Urban and Regional Planning, pp. 991e995. Wu, F., Zhu, M., Wang, Q., Zhao, X., Chen, W., Maciejewski, R., 2017. Spatialetemporal visualization of city-wide crowd movement. Journal of Visualization 20 (2), 183e194. Wu, S.M., Chen, T., Wu, Y.J., Lytras, M., 2018. Smart cities in Taiwan: a perspective on big data applications. Sustainability 10 (1). https://doi.org/10.3390/su10010106. Xu, P., Wu, Y., Wei, E., Peng, T.Q., Liu, S., Zhu, J.J., Qu, H., 2013. Visual analysis of topic competition on social media. IEEE Transactions on Visualization and Computer Graphics 19 (12), 2012e2021. Yin, J., Soliman, A., Yin, D., Wang, S., 2017. Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located twitter data. International Journal of Geographical Information Science 31 (7), 1293e1313. Zeng, W., Fu, C.W., Arisona, S.M., Schubiger, S., Burkhard, R., Ma, K.L., 2017. Visualizing the relationship between human mobility and points of interest. IEEE Transactions on Intelligent Transportation Systems 18 (8), 2271e2284.
Knowledge society technologies for smart cities development
11
Raquel Pe´rez-delHoyo1, Higinio Mora2 Department of Building Sciences and Urbanism, University of Alicante, Alicante, Spain1; Department of Computer Science Technology and Computation, University of Alicante, Alicante, Spain2
Chapter outline 1. Knowledge society in the new era .......................................................................185 2. Knowledge society and new technologies in the governance of cities ...................186 3. Technologies for smart urban planning: a citizen-centric approach .......................188 4. Conclusions .......................................................................................................194 Acknowledgments ...................................................................................................194 References .............................................................................................................195
1. Knowledge society in the new era The world is immersed in the era of the knowledge society. Unlike the information society, the knowledge society goes further and is able to transform this information into solutions that allow effective actions to be taken to improve society. In such a way, this knowledge society is based on the generation, distribution and use of knowledge to improve the quality of life of citizens. The technologies that have played an essential role in this development correspond to the area of information and communications technologiesdICT. They are the set of technologies that allow us to interact with the digital world and analyze the data acquired from it. The set of technologies reviewed in this chapter are the new communication technologies, the geopositioning services, and cloud computing paradigm. All of these technologies working in a combined way allow enabling new forms of building the knowledge society. Currently, there are many applications of the knowledge society in the real world. Perhaps, one of them that has contributed more to the increased of wellness of the citizens is the smart city concept. A smart city can be defined, therefore, as a model of urban management able of responding to the problems and needs of 21st century cities, which arises as a result of the development of the current knowledge society and its technological environment. Smart Cities: Issues and Challenges. https://doi.org/10.1016/B978-0-12-816639-0.00011-9 Copyright © 2019 Elsevier Inc. All rights reserved.
185
186
CHAPTER 11 Knowledge society technologies for smart cities
There are many smart city applications oriented toward improving the life of citizens (Gilart-Iglesias et al., 2015; Mora et al., 2017; Chen and Tsai, 2018). In this chapter, we put the focus on the urban planning of the city as one of the key processes to handle the sustainable and integrated development of today’s cities. The concept of “smart urban planning” (Babar and Arif, 2017) mainly relies on conducting this task aided with new knowledge technologies. The remaining part of this chapter is organized as follows. Section 2 describes the connection between the knowledge society and new technologies in the governance of cities. Next, Section 3 introduces the smart urban planning concept, and finally, we conclude the chapter in Section 4.
2. Knowledge society and new technologies in the governance of cities The ICT and the knowledge society have definitely changed the way in which citizens relate to the city (Mueller et al., 2018) and the way in which its management is carried out, and this new way of developing activities in the city also implies a change and modernization of their public institutions. This means, as shown in Fig. 11.1, that the smart city model only makes sense if it is linked to innovation to define a future city project to ensure together, in a balanced manner, the social sustainabilitydcohesion and social development, the economic sustainabilityda competitive economic strategy, the environmental sustainabilitydawareness and care for the environment, and the accessibilitydsocial integration. Within this context, it is clear that the concept of city governance requires major changes to respond to the new realities. The knowledge society and the latest technologies play an essential role in the governance of the city and its objective of achieving a sustainable economic, social, and institutional development, by promoting an intelligent balance between institutions, civil society, and the economy market. For this purpose, a smart city model allows governance to progress from its traditional structures to a greater relationship between public institutions and their environment (Meijer and Rodrı´guez-Bolı´var, 2016).
FIGURE 11.1 Smart city model and sustainable urban development.
2. Knowledge society and new technologies in the governance of cities
The possibilities offered by new technologies to maintain an efficient political and administrative structure are well known by public opinion: to facilitate the management of the city among the different administrations or institutions, to optimize the management of services and resources, to speed up administrative procedures and proceedings, to provide citizens with access to basic services, and to promote a sense of citizenship and citizen participation (Hanna, 2010; Lv et al., 2018; Lytras and Visvizi, 2018). In addition, new technologies allow connections for greater political, social, economic, cultural, and ideas exchange with other cities at all levels of government. In the field of urban planning, the planning and design of cities nowadays cannot be understood without the participation of citizens. Increasingly, an informed citizenry constitutes an active citizenry capable of self-organizing, having an opinion, and making the best decisions about the matters that affect the community. Therefore, beyond the urban development projects’ conventional periods of public exhibition established by law, it is necessary to set in motion innovative citizen participation processes before any urban development project has begun its development. The benefits of ICT for this purpose are very important and varied (Alfaro et al., 2017). For example, they can provide citizens with web 2.0 platforms that allow them interact and discuss the projects that should be developed with priority in the city or with citizens’ mailboxes in each website to facilitate consultations or suggestions on any matter related with the city, in addition to offering information on any urban project in all its phases of development. Knowledge is no longer found especially in a given space, and civil society plays an essential role in its production (Cossetta and Palumbo, 2014). People are the main source of information to build knowledge about the real problems and needs of the city they inhabit. It is only necessary to offer an effective channel of communication between citizens and public institutions to obtain, directly and in real time, accurate and up-to-date information about the experience of citizens in the city, the problems they perceive, and their priority (Dameri, 2017). The latest technologies are the key for developing these communication channels, which must be accessible and simple to usedthrough intuitive applications for mobile devices, for exampledso that they can be distributed among the greatest number of citizens. In this way, it is possible to obtain up-to-date information and build knowledge on any issue that affects the public space in the city: urban accessibility, operation of urban facilities and services, operation of public transport, cycle and pedestrian paths, and needs in specific environments such as schools or parks in certain time bands. In addition, involving citizens in solving the problems of the city allows neighbors to identify with their neighborhood and feel it as their own, preventing its abandonment and long-term deterioration (Jasso and Petrı´kova´, 2016), which also means the improvement of the relationship with the nearby neighborhoods and with the rest of the city. The democratization of urban planning and the active citizen participation processes are mechanisms against exclusion and for social development (Pearce, 2010).
187
188
CHAPTER 11 Knowledge society technologies for smart cities
Therefore, the commitment to social cohesion finds an important space in the city of the knowledge society, where citizens interact by developing more participative and interactive dynamics, with each other and with the city, thanks to technology, even allowing their habits, preferences, and positioning are known. Knowing citizen traceability, i.e., the level of use that citizens make of public spacedwhat obvious and not-so-obvious places they use to develop a specific type of activity such as running, riding a bicycle, or doing other sportsdallows, for example, the inclusive spaces of a city to be identified, i.e., the spaces used by all people regardless of their abilities or profiles, as well as learning from these spaces to serve as urban design models (Pe´rez-delHoyo et al., 2017). This information allows for better planning of the city, not only respecting those habits and preferences but also discovering new singularities and opportunities. These initiatives set in motion management dynamics within the context of the smart city that contribute to social cohesion and the empowerment of citizens. On the other hand, knowing the habits and preferences of citizens helps us to plan and design the smart city (Mora et al., 2015; Lenormand and Ramasco, 2016). The role of citizens has changed definitively by participating in what researchers have started to refer to as an “urban planning of ideas.” For this purpose, the virtual space is a new social space, and specialized social networks are a very powerful source of information. But the city of the knowledge society can go a step further, by adapting itself to citizens instead of citizens having to adapt to the city. The latest technologies allow citizens to be identified when they approach an urban environment and transform some of its elementsdsuch as traffic lights, information panels, or othersdto facilitate the use of these environments by citizens according to their abilities (Pe´rez-delHoyo et al., 2016). All these initiatives are part of the smart city project, thanks to technology (Etezadzadeh, 2016). In short, in the field of cities’ government, it is a need to humanize the smart city concept and work on initiatives that relates to the citizen as a receiver of actions that improve quality of life and serve to acquire information for planning and designing smart cities. In this way, it is a challenge for the government to move toward a type of city that could be called “citizen-centric smart city”, in which a circular relationship between administrators and citizens is built to improve their quality of life, focused on their needs, habits, and preferences. Fig. 11.2 illustrates this idea.
3. Technologies for smart urban planning: a citizen-centric approach From the point of view of urban planning, the smart city is a new urban model based on knowledge in a deep research exploration and a wide application of the latest information and communication technologies (Kummitha and Crutzen, 2017).
3. Technologies for smart urban planning: a citizen-centric approach
FIGURE 11.2 Citizen-centric smart city.
An urban development model aims to solve real problems and needs and pursues specific objectives and strategies. It is the reflection of the evolution of a society and draws a vision for the future city by answering the questions: what kind of place do we want the cities to be? and how should the goal of quality of life be defined? (Saaty and De Paola, 2017). As already mentioned in previous section, the smart urban planning concept, within the context of smart city, cannot be understood without citizen participation. The knowledge society and the latest information and communication technologies have transformed the traditional meaning of citizen participation, by placing people at the center of planning, design, and management of the cities of the future (Castells, 2011). Consequently, we are witnessing a reformulation of the urban planning paradigm (Landry, 2016; Marsal-Llacuna et al., 2011). Urban planning becomes a process where the city learns from itself and from the people’s habits, needs, and desires. A process that uses the imagination and collective intelligence of citizens cocreate and shape the city of tomorrow. This citizen-centric approach is critical for the future of urban planning within the context of smart city. A wide and proper use of technology is essential for urban planning to push ahead in this direction. The new information and communication technologies, the geopositioning services, and cloud computing paradigm offer new opportunities for cities to be smarter and more sustainable. Fig. 11.3 schematically draws this idea. This recurring idea is discussed in this section. The discussion is conducted by the analysis of some current approaches and the study of some real cases on how technologies can improve urban design and planning processes. One of the core urban initiatives in which technologies have facilitated new opportunities has been to give citizens a voice to express their opinion on the projects that are carried out in the city. For this purpose, ICT provide institutions with open public debate spaces on the internet where citizens, anonymously or as registered users, can comment and contribute ideas to improve their city. Good examples of these initiatives are some projects developed by some municipalities
189
190
CHAPTER 11 Knowledge society technologies for smart cities
FIGURE 11.3 Key technologies in urban planning for smart city.
in Portugal: the e-Democracy Service supported by a Geographical Information SystemdGISddeveloped for the public discussion of Oporto’s Municipal Master Plan (Oliveira et al., 2004) and the use of an interactive discussion map for public discussion of Lisbon Master Plan (Pina, 2012). In both projects, GIS technologies have served to drive public participation processes. Geographic Information Systems in Public ParticipationdPPGISdis an area with an increasing importance in the context of Geographic Information Science. These technologies have been used on a larger scale for a large number of different and varied projects, for example, to elicit information on outdoor places important to citizens in Wiltshire, England (Ridding et al., 2018); for the environmental planning and management of Mt. Baker-Snoqualmie National Forest in western Washington, USA (McLain et al., 2017); and for analyzing how landscape values are perceived by citizens in different areas of Europe (Garcia-Martin et al., 2017), among many others participatory mapping studies. The relationship between GIS and the knowledge society has allowed participatory mapping methodologies to be implemented. Mapping exercises are capable of providing communities with useful information. Processes for informing citizens in real time about the number of urban opportunities in a particular urban area, i.e., information on shops, facilities and services available, cultural routes and itinerary,es, up-to-date traffic or public transport
3. Technologies for smart urban planning: a citizen-centric approach
information, are also possible, thanks to ICT technologies. Knowing this information allows citizens to make smarter use of the opportunities offered by a city, reduce transport times, and use the appropriate services at any particular time. This intelligent use of the services and resources of a city is more in line with the principles of sustainable urban development. Processes for informing citizens have been mainly based on the calculation of close relationships and intensities of use, and they have been primarily supported by Global Positioning Systems technologiesdGPSd for positioning and GIS technologies for displaying data and spatial analysis. There are many projects recently developed in this field, for example, a smart decision support system determining the most efficient way to plan the tourist itineraries. Operations are managed through a mobile app/website. The system was implemented in the city of Melbourne, Australia (Bagloee et al., 2017). Another recent initiative funded by the German Government is about providing citizens with personalized, context-aware intermodal travel information. The aim of the initiative is to enhance travel information systems by analyzing the available itineraries to better suit the traveler, based on his personal preferences, context information, and popular selections (Samsel et al., 2016). On the other hand, urban geospatial data allow local industry and public institutions to develop applications that improve life of citizens. Therefore, the management of geospatial data is a big challenge for smart cities. Emerging technologies such as Semantic Web technologies to build up relations and connections between concepts, or open data web applications with well-performing search engines, can help public institutions to contextualize geospatial data by transforming the general information into useful knowledge. This knowledge will enable citizens, businesses, and public institutions to codesign new public information services to participate and understand what is going on in their city. In addition, geospatial data and open data are often used within the context of big data (Wu et al., 2018). Therefore, the use of cloud technology is almost mandatory. In line with this approach, some projects have been developed, for example, the European Union funded Project Smarticipate (Smarticipate Project, 2018), which is driven by the pilot cities of London; Britain; Rome, Italy; and Hamburg, Germany, with the aim of empowering citizens and businesses and fostering their involvement in the city’s governance system. The development of iterative processes in the field of the participatory urban planning and user-centered design of applications are some of the actions that have been carried out (Vogt and Fro¨hlich, 2016). Moving on to other issues, the knowledge of the people’s habits, preferences, needs, and desires is an essential factor for the smart urban planning within the context of smart cities. The study of urban places preferred and citizens’ movement patterns supports a better understanding of modern cities and enables a more comprehensive strategy for urban planning (Mora et al., 2015). In line with this overall vision, a wide range of studies has been developed, for example, using GPS and mobiles devices to analyze the movement patterns of taxis
191
192
CHAPTER 11 Knowledge society technologies for smart cities
between different urban areas in Beijing, China (Chen et al., 2017); the sociospatial and temporal complexities of older adults’ mobility in Metro Vancouver, Canada (Franke et al., 2017); or the spatial behavior of backcountry skiers in Tatra National Park, Poland (Taczanowska et al., 2017). The large development of ICT allows us to interact with an urban environment providing a huge amount of data and information about the cities we live in (Bohn et al., 2004). In these cases, the cloud is an essential tool for conducting advanced data analytics (Babar and Arif, 2017). Internet of things (IoT) devices, smart phones location data, and smart cards data have been used in a large number of urban planning initiatives within the context of the hyperconnected society and the big data phenomenon. Big data has aided understanding of human mobility (Lu et al., 2017). For example, to explore the spatial distribution and density of recreational movement in multiple-use urban forests in Helsinki, Finland (Korpilo et al., 2017) or the bike-sharing travel patterns and purposes in New York City (Bao et al., 2017). Much research on Geo-IoT technologies has been conducted even to described future scenes (Kim, 2018). The study of the citizens’ mobility has seen significant growth due the prevalence of mobile devices. By combining these data with the city’s points of interests, both travel patterns and purposes can be known. Increasingly, the methods for addressing the aspects that affect the functioning of the city are based on evidence, i.e., in the study of the citizens’ behaviors. For this purpose, many methodologies have been developed, for example, to improve urban accessibility for people with disabilities, a computational method based on new communications technologies (Gilart-Iglesias et al., 2015; Mora et al., 2017). The means of public transportdtrains, buses, and bike sharingd are also being continuously monitored with sensors that send important information about urban routes, travel times, and traffic intensity to the cities’ governments. A good example of this trend is the information system on the public transport of London, Britain (Ferrari et al., 2014). Actually, these participatory processes based on the analysis of urban dynamics are part of a challenging field of research to improve urban planning. To this end, some recent studies identify trajectories from origin-destination data and potential development axes (Bahbouh et al., 2017) and propose new algorithms to extract knowledge, i.e., patterns, rules, and regularities, from user trajectories (Cesario et al., 2017; Qian and Lu, 2017). On another level, sensor networks allow cities to monitor their environmental conditions and, therefore, not to make the mistakes of the past and move toward more sustainable development models. Environmental pollution monitoring is a major concern in the development of smart cities. Indeed, the World Health Organization launched the Global Platform on Air Quality and Health, for governments to collaborate in the development of strategies to reduce air pollution. Within this program, a lot of actions have been conducted. A recent example is the monitoring environmental parameters in the city of Pisa, Italy (Bacco et al., 2017). Urban noise has also been properly monitored to obtain useful information for urban planning. A good example of this initiative is the experience developed in the city of Dublin, Ireland (Alfaro Navarro et al., 2017).
3. Technologies for smart urban planning: a citizen-centric approach
FIGURE 11.4 Knowledge sources for understanding city needs.
However, as drawn in Fig. 11.4, the knowledge needed for city planning includes the physical, social, cultural, technological, and economic domains and incorporates multiple perspectives, such as the understanding of social and cultural dynamics and needs, to create new knowledge. A good deal of recent research concerns locative social networks as open sources of data to acknowledge which city places are preferred, used, and liveable. Some of these studies propose methodologies, for example, to identify city’s successful public spaces through the location-based social media network Foursquare (Martı´ et al., 2017); to discover popular tourist attractions within the urban areas through the Flickr geotagged images (Peng and Huang, 2017); or to depict urban boundaries with geolocated Twitter data (Yin et al., 2017). The generation of data and communication to the social network is usually done automatically through users’ mobile devices, such as smart phones and other wearables provided with GPS technology. In regard to this valuable information for the planning of cities, an important issue to be taken into account is how to show the data retrieved from different sources. Many studies focus on how visualization of social network data allows researchers and professionals from the field of urban planning to explore the relationship between citizens’ movements and activity distributions all over the city (Zeng et al., 2017). For smart urban planning, it is essential to understand the relationship between activities and human mobility. Given the pace of technology and the current use of mobile phones, there is a large amount of data that can be used to create high reliability models. In this regard, some of the studies referred to above propose novel data representations such as graphs to characterize spatial and temporal
193
194
CHAPTER 11 Knowledge society technologies for smart cities
people mobility (Wu et al., 2017). In addition, some studies propose visual analytics systems to measure opinion propagation, for example, among Twitter users (Xu et al., 2013), and others focus on the analysis of urban emotions (Resch et al., 2015, 2016). Comprehensive systems and solutions for smart urban planning and smart strategies for developing more resilient and sustainable cities (Falco, 2015; Mora et al., 2017; Visvizi and Lytras, 2018) have been proposed over the past few years. This has become a growing trend, and therefore, in a near future, other systems and solutions for smart cities will be suggested. All of these smart initiatives, which are aimed to help cities for a more sustainable development, are without a shadow of a doubt the result of the joint efforts and collaboration of different fields of knowledge.
4. Conclusions The accelerated technological development in recent years has transformed the way of living and understanding the world. As a consequence, the current knowledge society and its technological environment have brought profound social and economic changes. Today’s cities need to position themselves in a competitive global context and they have to assume a new lead role. The current context opens new possibilities for city development and allows adopting modern strategies to address their challenges. In this sense, the concept of smart city represents a model of urban development base on smart application of technology. To become it, cities may face a new key challenge, which is to begin incorporating technologies as a part of the urban organism. The concepts of ubiquitous and smart cities make use of processing technologies, sensing, and communications to provide intelligence to the city, while offering connectivity resources, power supply and interoperability. These conditions facilitate the deployment of interconnected smart elements that provide services to citizens for efficient decision-making and to make better use of resources. To consolidate this smart urban model, a commitment is required from the responsible for management and city government. Definitely, new technologies and communications solutions have revolutionized the way of knowing cities and, consequently, the way of planning and designing cities. Communication technologies, geographic information systems, and cloud computing paradigm are some of the most relevant technologies, which currently help cities move toward a smarter, more sustainable, and inclusive development model.
Acknowledgments This work has been funded by the Conselleria de Educacio´n, Investigacio´n, Cultura y Deporte of the Community of Valencia, Spain, within the program of support for research under project AICO/2017/134.
References
References Alfaro Navarro, J.L., Lo´pez Ruiz, V.R., Nevado Pen˜a, D., 2017. The effect of ICT use and capability on knowledge-based cities. Cities 60, 272e280. Babar, M., Arif, F., 2017. Smart urban planning using big data analytics to contend with the interoperability in Internet of Things. Future Generation Computer Systems 77, 65e76. Bacco, M., Delmastro, F., Ferro, E., Gotta, A., 2017. Environmental monitoring for smart cities. IEEE Sensors Journal 17 (23), 7767e7774. Bagloee, S.A., Tavana, M., Di Caprio, D., Asadi, M., Heshmati, M., 2017. A multi-user decision support system for online city bus tour planning. Journal of Modern Transportation 25 (2), 59e73. Bahbouh, K., Wagner, J.R., Morency, C., Berdier, C., 2017. Travel demand corridors: modelling approach and relevance in the planning process. Journal of Transport Geography 58, 196e208. Bao, J., Xu, C., Liu, P., Wang, W., 2017. Exploring bikesharing travel patterns and trip purposes using smart card data and online point of interests. Networks and Spatial Economics 17 (4), 1231e1253. Bohn, J., Coroama, V., Langheinrich, M., Mattern, F., Rohs, M., 2004. Living in a world of smart everyday objects-social, economic, and ethical implications. Human and Ecological Risk Assessment: An International Journal 10, 763e785. Castells, M., 2011. The Rise of the Network Society - the Information Age: Economy, Society, and Culture, vol. 1. John Wiley & Sons. Cesario, E., Comito, C., Talia, D., 2017. An approach for the discovery and validation of urban mobility patterns. Pervasive and Mobile Computing 42, 77e92. Chen, Z., Gong, X., Xie, Z., 2017. An analysis of movement patterns between zones using taxi GPS data. Transactions in GIS 21 (6), 1341e1363. Chen, Y.-S., Tsai, Y.-T., 2018. A mobility management using follow-me cloud-cloudlet in fog-computing-based RANs for smart cities. Sensors 8 (2), 489. https://doi.org/10.3390/ s18020489. Cossetta, A., Palumbo, M., 2014. The Co-production of social innovation: the case of living lab. In: Smart City: How to Create Public and Economic Value with High Technology in Urban Space. Springer, pp. 221e235. Dameri, R.P., 2017. Smart City Implementation: Creating Economic and Public Value in Innovative Urban Systems. Springer. Etezadzadeh, C., 2016. Smart City e Future City?: Smart City 2.0 as a Livable City and Future Market. Springer. Falco, G.J., 2015. City resilience through data analytics: a human-centric approach. Procedia engineering 118, 1008e1014. Ferrari, L., Berlingerio, M., Calabrese, F., Reades, J., 2014. Improving the accessibility of urban transportation networks for people with disabilities advances. Transportation Research Part C: Emerging Technologies 45, 27e40. Franke, T., Winters, M., McKay, H., Chaudhury, H., Sims-Gould, J., 2017. A grounded visualization approach to explore sociospatial and temporal complexities of older adults’ mobility. Social Science and Medicine 193, 59e69. Garcia-Martin, M., Fagerholm, N., Bieling, C., Gounaridis, D., Kizos, T., Printsmann, A., Plieninger, T., 2017. Participatory mapping of landscape values in a Pan-European perspective. Landscape Ecology 32 (11), 2133e2150.
195
196
CHAPTER 11 Knowledge society technologies for smart cities
Gilart-Iglesias, V., Mora, H., Pe´rez-delHoyo, R., Garcı´a-Mayor, C., 2015. A computational method based on radio frequency technologies for the analysis of accessibility of disabled people in sustainable cities. Sustainability 7 (11), 14935e14963. Hanna, N.K., 2010. Transforming Government and Building the Information Society: Challenges and Opportunities for the Developing World. Springer. Jasso, M., Petrı´kova´, D., 2016. Place attachment and social communities in the concept of smart cities. In: Smart City 360 . Springer, pp. 721e728. Kim, M.S., 2018. Research issues and challenges related to Geo-IoT platform. Spatial Information Research 26 (1), 113e126. Korpilo, S., Virtanen, T., Lehva¨virta, S., 2017. Smartphone GPS trackingdinexpensive and efficient data collection on recreational movement. Landscape and Urban Planning 157, 608e617. Kummitha, R.K.R., Crutzen, N., 2017. How do we understand smart cities? An evolutionary perspective. Cities 67, 43e52. Landry, C., 2016. The changing face of urban planning: towards collaborative and creative cities. In: Human Smart Cities. Rethinking the Interplay between Design and Planning. Springer, pp. 238e250. Lenormand, M., Ramasco, J., 2016. Towards a better understanding of cities using mobility data. Built Environment 42 (3), 356e364. Lu, S., Fang, Z., Zhang, X., Shaw, S.L., Yin, L., Zhao, Z., Yang, X., 2017. Understanding the representativeness of mobile phone location data in characterizing human mobility indicators. ISPRS International Journal of Geo-Information 6 (1), 7. Lv, Z., Li, X., Wang, W., Zhang, B., Hu, J., Feng, S., 2018. Government affairs service platform for smart city. Future Generation Computer Systems 81, 443e451. Lytras, M.D., Visvizi, A., 2018. Who uses smart city services and what to make of it: toward interdisciplinary smart cities research. Sustainability 10, 1998. https://doi.org/10.3390/ su10061998. Martı´, P., Serrano-Estrada, L., Nolasco-Cirugeda, A., 2017. Using locative social media and urban cartographies to identify and locate successful urban plazas. Cities 64, 66e78. Marsal-Llacuna, M.L., Leung, Y.T., Ren, G.J., 2011. Smarter urban planning: match land use with citizen needs and financial constraints. In: International Conference on Computational Science and its Applications. Springer, pp. 93e108. Meijer, A., Rodrı´guez Bolı´var, M.P., 2016. Governing the smart city: a review of the literature on smart urban governance. International Review of Administrative Sciences 82 (2), 392e408. McLain, R.J., Banis, D., Todd, A., Cerveny, L.K., 2017. Multiple methods of public engagement: disaggregating socio-spatial data for environmental planning in western Washington, USA. Journal of Environmental Management 204, 61e74. Mora, H., Gilart-Iglesias, V., Gil, D., Sirvent-Llamas, A., 2015. A computational architecture based on RFID sensors for traceability in smart cities. Sensors 15 (6), 13591e13626. https://doi.org/10.3390/s150613591. Mora, H., Gilart-Iglesias, V., Pe´rez-delHoyo, R., Andu´jar-Montoya, M.D., 2017. A comprehensive system for monitoring urban accessibility in smart cities. Sensors 17 (8), 1834. Mueller, J., Lu, H., Chirkin, A., Klein, B., Schmitt, G., 2018. Citizen design science: a strategy for crowd-creative urban design. Cities 72, 181e188.
References
Navarro, J.M., Tomas-Gabarron, J.B., Escolano, J., 2017. A big data framework for urban noise analysis and management in smart cities. Acta Acustica United with Acustica 103 (4), 552e560. Oliveira, M.A., Carvalho, A., Ba´rtolo, L., 2004. Public discussion of Oporto’s municipal master plan: an e-democracy service supported by a geographical information system. In: Third International Conference on Electronic Government. Springer, pp. 410e413. Pearce, J., 2010. Participation and Democracy in the Twenty-First Century City. Springer. Peng, X., Huang, Z.A., 2017. Novel popular tourist attraction discovering approach based on geo-tagged social media big data. ISPRS International Journal of Geo-Information 6 (7), 216. Pe´rez-delHoyo, R., Garcı´a-Mayor, C., Mora-Mora, H., Gilart-Iglesias, V., Andu´jar-Montoya, M.D., 2016. Making smart and accessible cities: an urban model based on the design of intelligent environments. In: 2016 5th International Conference on Smart Cities and Green ICT Systems. (SMARTGREENS), pp. 1e8. Pe´rez-delHoyo, R., Garcia-Mayor, C., Mora, H., Gilart, V., Andu´jar-Montoya, M.D., 2017. Improving urban accessibility: a methodology for urban dynamics analysis in smart, sustainable and inclusive cities. International Journal of Sustainable Development and Planning 12 (3), 357e367. Pina, I., 2012. Participac¸a˜o Pu´blica e SIG: Do potential a` pra´tica, da pra´tica aos resultados Discussa˜o Pu´blica do PDM de Lisboa (Doctoral dissertation). Qian, H., Lu, Y., 2017. Simplifying GPS trajectory data with enhanced spatial-temporal constraints. ISPRS International Journal of Geo-Information 6 (11), 329. Resch, B., Summa, A., Sagl, G., Zeile, P., Exner, J.P., 2015. Urban emotions: geo-semantic emotion ex-traction from technical sensors, human sensors and crowdsourced data. In: Progress in Location-Based Services 2014. Springer, pp. 199e212. Resch, B., Summa, A., Zeile, P., Strube, M., 2016. Citizen-centric urban planning through extracting emotion information from twitter in an interdisciplinary space-time-linguistics algorithm. Urban Planning 1 (2), 114e127. Ridding, L.E., Redhead, J.W., Oliver, T.H., Schmucki, R., McGinlay, J., Graves, A.R., Bullock, J.M., 2018. The importance of landscape characteristics for the delivery of cultural ecosystem services. Journal of Environmental Management 206, 1145e1154. Saaty, T.L., De Paola, P., 2017. Rethinking design and urban planning for the cities of the future. Buildings 7 (3), 76. Samsel, C., Krempels, K.H., Garbereder, G., 2016. Personalized, context-aware intermodal travel information. In: Proceedings of the 12th International Conference on Web Information Systems and Technologies, vol. 1. WEBIST 2016), pp. 148e155. Smarticipate Project, 2018. Funded Project by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No 693729. https:// www.smarticipate.eu/. Taczanowska, K., Bielanski, M., Gonza´lez, L.M., Garcia-Masso´, X., Toca-Herrera, J.L., 2017. Analyzing spatial behavior of backcountry skiers in mountain protected areas combining GPS tracking and graph theory. Symmetry 9 (12), 317. Visvizi, A., Lytras, M., 2018. Rescaling and refocusing smart cities research: from mega cities to smart villages. Journal of Science and Technology Policy Management (JSTPM). https://doi.org/10.1108/JSTPM-02-2018-0020.
197
198
CHAPTER 11 Knowledge society technologies for smart cities
Vogt, M., Fro¨hlich, P., 2016. Understanding cities and citizens: developing novel participatory development methods and public service concepts. In: REAL CORP 2016eSMART ME UP! How to Become and How to Stay a Smart City, and Does This Improve Quality of Life? Proceedings of 21st International Conference on Urban Planning, Regional Development and Information Society. CORPeCompetence Center of Urban and Regional Planning, pp. 991e995. Wu, F., Zhu, M., Wang, Q., Zhao, X., Chen, W., Maciejewski, R., 2017. Spatialetemporal visualization of city-wide crowd movement. Journal of Visualization 20 (2), 183e194. Wu, S.M., Chen, T., Wu, Y.J., Lytras, M., 2018. Smart cities in Taiwan: a perspective on big data applications. Sustainability 10 (1). https://doi.org/10.3390/su10010106. Xu, P., Wu, Y., Wei, E., Peng, T.Q., Liu, S., Zhu, J.J., Qu, H., 2013. Visual analysis of topic competition on social media. IEEE Transactions on Visualization and Computer Graphics 19 (12), 2012e2021. Yin, J., Soliman, A., Yin, D., Wang, S., 2017. Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located twitter data. International Journal of Geographical Information Science 31 (7), 1293e1313. Zeng, W., Fu, C.W., Arisona, S.M., Schubiger, S., Burkhard, R., Ma, K.L., 2017. Visualizing the relationship between human mobility and points of interest. IEEE Transactions on Intelligent Transportation Systems 18 (8), 2271e2284.