# Cyber-Physical-Social Frameworks for Urban Big Data Systems: A Survey
## 4 Data Sources
### Physical Sensor Deployments  
A basic sensor network deployment approach in urban areas involves fixed installations, where the location configurations of the deployed sensors remain static. Without any change in the location, the sensed data generated by the sensors form a continuous time-series, whose resolutions depend on the sampling rate of the sensors. The London Air Quality Network (LAQN) ([[https://www.londonair.org.uk/LondonAir/Default.aspx](https://www.londonair.org.uk/LondonAir/Default.aspx)]([https://www.londonair.org.uk/LondonAir/Default.aspx](https://www.londonair.org.uk/LondonAir/Default.aspx))) is one such real deployment which has multiple types of weather sensors and air pollution sensors in London. LAQN deploys sensors in four different types of locations, including roadside, suburban, urban background, and industrial. The sensed air pollution data mainly consists of Carbon Monoxide (CO), Nitrogen Dioxide (NO\({}_{2}\)), Ozone (O\({}_{3}\)), PM\({}_{10}\) Particulates, PM\({}_{2.5}\) Particulates, and Sulphur Dioxide (SO\({}_{2}\)). These data are normally sampled every 15 min by each sensing site. LAQN offers access to the real-time air pollution data through heat maps and historical data downloads in comma-separated values (CSV) format. The available data includes the following parameters: site ID, sensing species, measurement date and time, measured value, measurement units, and whether the value is provisional or ratified. It also enables APIs for data access in eXtensible Markup Language (XML) and JavaScript Object Notation (JSON) formats according to different sensing sites or sensing species. Due to the provenance of the sensed data and known static context, fixed sensing has been applied for numerous sensing applications, such as air quality sensing [32; 65], weather conditions [72], water distribution data [71] and traffic data [56; 72]. Different supporting frameworks are also proposed [18; 40; 56]. The fixed sensors involved in the water distribution network system [71] include the water sensors, which monitor the flow and pressure, and water quality sensors. The fixed sensor installation in the noise mapping architecture in [18]  
Figure 5: A taxonomy of CPSS data sources. is based on the SmartSantander IoT architecture and is a realization of a WSN for urban sensing, with sensors mounted on public properties such as on street and traffic lights and on building facades. Mobile extensions for this architecture include sensors mounted on vehicles. The SmartSantander ([[http://www.smartsantander.eu/](http://www.smartsantander.eu/)]([http://www.smartsantander.eu/](http://www.smartsantander.eu/))) project aims at a large number of sensor deployments in four different places: Belgrade, Guildford, Lubeck and Santander. The Santander testbed is a notable one as it has deployed heterogeneous sensors at a city scale. The sensors cover multiple areas: (1) environmental monitoring that can provide data for temperature, CO, noise, light and car presence; (2) traffic monitoring that involves data for traffic volumes, road occupancy, vehicle speed or queue length; (3) availability of parking slots; and (4) agriculture monitoring that provides data for moisture, temperature and humidity, pluviometer, anemometer. These data are publicly accessible through the SmartSantander Map ([[http://maps.smartsantander.eu/](http://maps.smartsantander.eu/)]([http://maps.smartsantander.eu/](http://maps.smartsantander.eu/))) in JSON and HTML format. The data contains information fields such as sensor node id, location of the sensor node, encoded sensing value, update date and time and multiple sensing values. An example of a SmartSantander observation data point is shown in Figure 6.  
In addition to deployments of fixed sensors, SmartSantander also has deployments consisting of sensors attached to public vehicles, which enable a mobile sensing scenario that provides sensing data with changing locations.