## 3 Analytical Methods and Applications
### Network Analysis  
Network analysis can be used in graph measures, least-cost shortest path problems and flow modeling. In this sense, it is closely related to distance and proximity analysis. Network analysis can be used to solve transportation problems that would be very challenging to solve otherwise. Examples of classical transportation problems that require network analysis include finding closest facilities (see Figure 6), discovering optimal service areas, calculating multi-point vehicle routing, performing location allocation, doing time-dependent analysis and creating a origin-destination cost matrix [31]. Route planning is a sub-category of network analysis, which is about finding optimal means of traveling between two or more given locations (i.e., vector points), based on criteria such as fastest or shortest path, cheapest route, etc.  
Figure 5: An example of heat map analysis (adapted from [31]).  
IoT projects using network analysis involve BALLADE ([[http://sensorsandsystems.com/tuning-the-ballade-geospatial-infrastructure-for-plug-in-electric-vehicles/](http://sensorsandsystems.com/tuning-the-ballade-geospatial-infrastructure-for-plug-in-electric-vehicles/)]([http://sensorsandsystems.com/tuning-the-ballade-geospatial-infrastructure-for-plug-in-electric-vehicles/](http://sensorsandsystems.com/tuning-the-ballade-geospatial-infrastructure-for-plug-in-electric-vehicles/))), an e-mobility initiative for managing networks of intelligent geo-located charging stations for plug-in electric vehicles. Network analysis was also used in [49], for studying the role of landscape connectivity in assembling exotic plant communities, observing that invasive species can spread more easily in fragmented landscapes than native species, which may make communities more homogeneous over time. Finally, network analysis has been employed in agriculture, for estimating the impact of livestock agriculture and especially animal manure on the physical environment [50].  
The CityPulse project developed an IoT-enabled route planning demonstration [12], which takes into account real-time traffic conditions at the city of Aarhus, Denmark and considers various user preferences. A snapshot of the demo is shown in Figure 7. In addition, UPS implemented a system called ORION [15], which is powered by GIS technology. The system acts as a logistics command center, weighing the stops a driver must make against variables such as timed deliveries and fuel usage.  
ApprokB ([[https://www.areaverda.cat/es/operar-con-el-movil/quasapparkb/](https://www.areaverda.cat/es/operar-con-el-movil/quasapparkb/)]([https://www.areaverda.cat/es/operar-con-el-movil/quasapparkb/](https://www.areaverda.cat/es/operar-con-el-movil/quasapparkb/))) directs the user to open parking spots in Barcelona while tourist guide services navigate the users to suggested nearby attractions [51]. Finally, a demonstration of optimized municipal solid waste recycle management  
Figure 6: An example of network analysis related to finding closest facilities (adapted from [31]).  
Figure 7: A snapshot of the CityPulse route planner demonstration (Source: [12]).  
based on IoT technology, is described in [52], while SmartBin ([[https://www.smartbin.com/](https://www.smartbin.com/)]([https://www.smartbin.com/](https://www.smartbin.com/))) offers intelligent remote monitoring solutions for collection of waste and recycling.