GIS is Smart City
The smart city concept is developing very quickly around the world, because it provides a comprehensive digital environment that improves the efficiency and security of urban systems and reinforces the involvement of citizens in urban development. This concept is based on the use of geospatial data concerning the urban built environment, the natural environment and urban services. The successful implementation of a smart city project requires the development of a digital system that can manage and visualise the geospatial data in a user-friendly environment. The geographic information system (GIS) offers advanced and user-friendly capabilities for smart city projects.
The smart city concept aims at developing a comprehensive system that uses geospatial data to enhance the understanding of complex urban systems and to improve the efficiency and security of these systems. This geospatial data concerns the following.

Urban Environment: The urban built environment such as infrastructure, buildings and public spaces.
Natural Environment: The natural environment such as biodiversity, green spaces, air quality, soil and water.
Urban Services: Urban services such as transport, municipal waste, water, energy, health and education.

The smart city concept also aims at transforming the silo-based management of cities into a shared system that involves urban stakeholders in the design, realisation and evaluation of urban projects.

The implementation of smart city projects is based on a number of steps including the construction of the urban digital model, data collection using the sensing layer, then data analysis, interactive data visualisation and system control. GIS plays a role in these steps, as described below.

Construction of the urban digital model:
The first step in the implementation of smart city projects concerns the construction of the urban digital model that describes the components of the urban built and natural environments. For each urban component, the digital model provides the geolocalisation and characteristics (attributes). GIS is generally used for the construction of the digital model of urban ‘horizontal components’ such as urban networks, transport facilities and natural environment, while building information modelling (BIM) is used for the description of ‘vertical components’ such as buildings. The combination of GIS and BIM provides a powerful tool for the construction of the urban digital model with georeferenced data and the visualisation of this data in a user-friendly environment.

Sensing layer:
The second step in smart city projects concerns the construction of the sensing layer that transfers urban operating data to the smart city information system. This layer includes sensors used for monitoring urban networks and infrastructures. Data could also be enhanced by images, videos and audio files resulting in the construction of urban big data. The drinking water system uses automatic meter readers (AMRs) to record water consumption, pressure sensors to record water pressure and water quality devices to track the water quality (turbidity, pH, chlorine, conductivity). The drainage system uses sensors to monitor the water level and flow, water quality (turbidity, temperature, pH, etc.) and pumping equipment. It allows early detection of flood and faults in pumping equipment. The electrical grid uses sensors to measure the electrical tension, current and frequency. It allows early detection of faults in the electrical grid. The district heating system is monitored by sensors to record fluid temperature, pressure and flow as well as the state of the valve. It allows early fault detection and the improvement of the system performance. GIS offers the possibility to visualise the monitoring system as well as the sensors’ characteristics and status. It also provides the possibility to visualise real-time and historical data on GIS maps.

Data Analysis:
The third step in implementing a smart city project concerns the development of the analytic environment, which converts real-time and historical data into operational data that improves the security, efficiency and quality of urban systems. The analytic environment includes engineering, management and safety software for urban systems as well as advanced digital tools such as artificial intelligence (AI). In smart city projects, GIS provides tools for (i) geospatial data analysis (distance and directional analysis, geometrical processing, grid models), (ii) spatiotemporal analysis, (iii) spatial statistics (spatial autocorrelation and egression), (iv) surface analysis (surface form and flow analysis, gridding and interpolation methods) and, (v) location analysis (shortest path calculation, facility location).

Interactive data visualisation:
Interactive data visualisation allows users to interact with the smart city’s components and the stakeholders in a user-friendly environment. Web applications are used to create this interactive environment. The use of HTML popups enables users to access web-based content such as graphics referenced by URLs. The interactive GIS graphic environment allows the visualisation of urban components and sensors maps. Users and managers can utilise these maps to access static and dynamic data concerning urban systems as well as to update the data.

Control layer:
Data analysis of historical and real-time data results in commands for the optimal and safe management of urban systems. These commands are transmitted to the control layer, which includes different electronic devices such as smart valves, pumps, motors, switches, breakers and locks. The GIS system allows real-time visualisation of these devices as well as their status. It could also visualise faults in device command.

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