20 May Geographic information systems and smart cities
Geographic information systems and smart cities – The city as a data generator
Cities proliferate as the most common elements in the organization of the territory when analyzing the population and it is expected that this will be the case in the future. Whether smart, sustainable or creative, they need well-developed and precise management systems. Geographic Information Systems or GIS are a fundamental tool for ordering, classifying and planning the city. There are countless success stories in GIS management for city management and they are constantly growing.
The enormous generation of data in the city makes it a priority to know how to properly manage information in order to later treat it correctly and make the most of it. Most of this data has a place in space, in the territory and this is what allows GIS to be a powerful, practical and versatile database for the city. There are many applications for these information systems and, in our current world, where so much importance is given to mobility, there are countless location-based mobile applications to carry out the tasks that both management and the user propose.
Introduction: the city as a data generator
In recent years, thanks to information and communication technologies, the way cities are studied has changed. Until a few years ago, the data that was worked on about cities and citizens was static: population densities, income levels, travel flows, geopositioning of infrastructures… Nowadays, we could say that this offered very real knowledge of the city.
The smart city seeks to combine information and communication technologies to increase the operation and management of the city, being more efficient, competitive and providing new solutions to respond to problems of sustainability and environmental degradation. With ICT we can understand the internal nature of urban dynamics and approach decision-making with better tools, knowledge and capabilities.
The city is a large generator of data. New technologies allow us to zoom in and out and reduce scale. Cities seek to improve information technology to better understand what happens there and what the behaviors of people and companies are.
ICT is the main part of the city, just as traditional urban planning was a few years ago. Information systems not only make it possible to capture city information more efficiently, but also offer real-time information to citizens, allowing them to improve their quality of life.
Some of the ICT tools that are frequently used in smart cities are: forms of multi-access (web, TV, mobile internet, telephone channel, etc.), smart cards to access some of the city’s services, telephone services or in-person assistance, municipal points connection to the WIFI network, sensors distributed throughout the city that collect and process information (parking, lighting, traffic, environmental control, garbage), real-time information about traffic and public transport, etc.
All of these and many other urban actions that allow decision-making have a common denominator, which is that they are carried out in a specific point in the territory. The city is above all a very complex geographical space. They can be analyzed from major dynamics of daily movement from the outskirts to the center, to the most concrete dynamics of the city. Any situation that occurred in the city can be located.
In this regard, two main questions arise around data management: how to acquire the data? And how to process them?
Acquisition of data in the city
Urban sensors
The ‘sensorization’ of the city has been one of the revolutions of smart cities, in some cases discussed for leaving the streets with too many electronic elements that can interfere with urban aesthetics, or that can lead to a dispersion of electronic devices and that become useless at the same time. over time. Regardless, many municipal entities have chosen sectors to test these technologies. A wide variety of electrical terminals are being created to take environmental control in cities, created from free hardware platforms; they acquire data on pollution, allergenic elements, temperature, humidity, CO2 level, among others.
We can identify two types of sensing:
- Static sensing: these are sensors that are installed at a fixed point in the city, from which they collect the corresponding data, such as sensors for detecting free parking spaces, which are installed under the asphalt and transmit whether or not the space is occupied, or the intelligent irrigation sensors that capture data on relative humidity and soil temperature and based on this, the green areas of the city are watered with a certain intensity.
- Dynamic sensing: in this case, the sensors are installed in elements that are in motion, such as police vehicles, cleaning service vehicles or taxis, so that they collect information in different parts of the city, generating an environmental map.
Smart Cards
The proliferation of smart cards that include on the same card a variety of services such as registration for courses, reservation of sports spaces, access to swimming pools and use of libraries, parking, use of public bathrooms or use of bicycle sharing services or to public transport, they are an unlimited source of information. One of the most studied aspects of these cards is the travel of bicycle and public transport users, where it is possible to analyze the frequency of use of routes and destinations, and information on the place of origin and arrival, critical routes or assess the impact of various events. urban mobility.
Social media
Currently, social networks are the biggest source of data to know what people are talking about, when and from where. Every time we use social networks, whether consulting them or publishing content, we leave geolocated information. The main social networks have their own services for exploring spatial information, such as Facebook’s Data Science study, which investigates the phenomenon of population migration, or Twitter with its Every Day Moments project, which analyzes everyday interactions thematically and spatially.
There are also other sources of data related to urban dynamics, such as the use of credit cards and payment terminals. This is the case of BBVA’s Big Data study, which made it possible to analyze the behavior of thousands of tourists in Barcelona during a weekend, because despite working with aggregated data, they can differentiate sociodemographic factors such as age, sex or country of origin.
Municipalities are also increasingly creating open data portals, disclosing previously restricted information, to increase the transparency of municipal administration and increase the participation of companies and citizens.
Currently, ICT is becoming a fundamental tool in cities and big data or large-scale data collection is the cornerstone of smart cities. The three vectors that define a big data project are: large volume, management capacity and speed to obtain a response.
How to process the data
In general, everything we do with geographic information involves some type of analysis and there is a wide variety of spatial analysis processes. For example, the combined analysis of different factors as a tool to support decision-making or the creation of zones of influence, encompassed in a set of geographic data transformation processes.
In this context, the geographic information system must be considered as a tool that allows a better formulation of geographic questions that open a field of action in which practically all ideas can be reflected and applied in practice. This is why cities present themselves as suitable spaces for organizing information through a spatial information system, which will allow you to easily carry out calculations on data between the various sources of information.
Data processing is often complex. With the enormous amount of information processed, even at a local level, it is necessary to exhaustively treat and organize (process) the information. To this end, Spatial Data Infrastructures (IDE) were created, to rely on homogeneous, valid and ‘official’ data in most cases. Therefore, the best method for processing local information must also be based on IDE, which allows us to easily access information, not replicate data and use it in a common way. They also allow us to track and evolve cartographic and geographic information over time.
Apps as a location component
There are countless applications based on location and, ultimately, GIS. With the recent proliferation of applications for everything, the world of mobility is more than present.
Some of the location-based applications, and among the best known, are Layar or those related to urban incidents, of greater scope and repercussion among current citizens. Layar is nothing more than a commercial name for an augmented reality (AR) application format, which is the most widespread to date. It allows, through location, to view on a mobile device the elements that we have loaded into the application, presented in sections, functioning as a GIS. The difference is that the information is presented on the device’s camera, in 3D, showing items based on distance and orientation.
Geofencing is another of the main applications in the field of mobility. It consists of evaluating the user experience to provide them with personalized offers, promotions and services according to their habits and interests. But it doesn’t stop there, but also in hourly trends – which follow the “spatial routine” of each consumer. Knowledge through these habit systems, in annual, weekly and/or daily fractions, works in a similar way to Google Transit which, although it is not an application that should be directly related to geofencing, works in the same way, as it takes information of users to establish behaviors in accordance with their usual practices when moving, and subsequently process this data to offer the user of the application or tool, simulated information about traffic or vehicle flow for each moment of the day, day of the week and location per where they move.
Therefore, through this geofencing model it is also possible to retain customers. And how do we do it? Providing offers they want when they want them. This way, when a user moves through a shopping area, according to previous data analysis (preferences or hobbies), these applications offer personalized discounts or special promotions for each consumer profile. We could consider geofencing as an evolution or one of the current pillars of geomarketing, understood as the application of the “space” variable of the market or traditional marketing.
Improving the city through GIS
There are numerous applications for which GIS are used. This multiplicity of tools and destinations for this way of organizing information, spatially, marks its versatility and, in turn, transversality. In this sense, one of the comparative advantages in using Geographic Information Systems as databases, to organize information according to spatial criteria, is their transversal, horizontal or multidisciplinary (and also contemporary) nature.
Thus, the application of GIS in information management can be found in varied and very disparate sectors. From mobility, with examples such as the one explained previously with Google, through ITS (Intelligent Transport Systems) from which all types of variables and elements are controlled: emergency services, fleet management, parking lot occupancy -both underground and on the surface-, etc., to have an overview and situation of urban mobility at all times (traffic maps, flows, etc.)
Thematic maps that are based on cartography generated through a GIS itself that brings together very specific information such as those based on environmental sensors, but today’s sensors are not static, but dynamic; are incorporated into public transport fleets (city buses, taxis, etc.). All of this thematic cartography, such as pollution or contamination maps, is based on GIS which, together with sensors, provide real-time information on a range of variables.
Another recurring application is that related to ‘smart water’ solutions; Smart cities make use of the most advanced innovations that aim to optimize integrated water management processes and, thus, use GIS for their management and improvement. In water management, notable advances have been made to reduce water consumption, and also energy consumption, as well as improving living conditions, qualitative and quantitative guarantee of urban supply, sustainability and protection against natural disasters. This is where information systems with a spatial component come in. Smart water grids allow an improvement in the knowledge of water use, both industrially and in terms of citizen consumption, which can bring savings and allow us to know almost in real time where leaks occur, thanks to GIS, and faster repair. Furthermore, prevention and protection against urban flooding, thanks to the implementation of advanced drainage management systems, based on meteorological information, and remote control systems based on GIS allow management, preparation and timely warning in the face of these episodes that translate into resulting in significant savings in energy, water and other resources to deal with disasters that involve not using these systems.
Finally, it is very interesting to mention open data applied to cartography and GIS. The key to the success of this spatial information is based on collaboration, in the creation of maps by citizens. It is the users themselves who can best provide information (they may not know the best way to represent it, but they are the ones who best know the reality around them.)