## 3 State of the Art
### Financial Viability of Selected IoT Communication Technologies
The assessment encompassed various smart city use cases representing distinct domains, including traffic management, environmental monitoring, citizen science, and energy management. The artifact was evaluated based on its ability to effectively monitor and optimize specific aspects within each domain. For example, in the traffic management domain, the artifact was assessed for its capability to monitor traffic flow, parking availability, and air quality. Similarly, in the environmental monitoring domain, the artifact's performance was evaluated in terms of monitoring air and water quality. The citizen science use case involved assessing the artifact's ability to collect data on weather conditions and noise levels. Lastly, the energy management use case focused on evaluating the artifact's effectiveness in optimizing energy consumption and production in buildings and industrial facilities. Through these assessments, this study aimed to determine the artifact's applicability and effectiveness in addressing the unique challenges and requirements of each domain within the context of smart cities. In each use case, the tool was used to calculate the life cycle costs of the IoT devices, including procurement costs, training and usage costs, maintenance costs, disposal costs, and external project costs. The tool used different cost assumptions and parameters for each use case depending on the specific requirements and characteristics of the scenario. The validation of the tool involved several steps, including verifying the accuracy of the calculations, assessing the usability and accessibility of the tool, and analyzing the results to identify any patterns or trends across the different use cases [32]. To verify the accuracy of the calculations, the tool was compared to other established methods for calculating life cycle costs, such as the traditional cost accounting approach and the Total Cost of Ownership (TCO) framework. The results showed that the tool was able to produce accurate and reliable cost estimates for each use case, and that the results were consistent with the results obtained from other methods. To assess the usability and accessibility of the tool, the tool was evaluated by a group of experts in each use case domain. The experts were asked to evaluate the tool based on several criteria, including ease of use, clarity of instructions, and accessibility of the tool for non-experts. The feedback from the experts was positive, and they found the tool to be user-friendly and intuitive, with clear instructions and a simple interface. Table 3 delivers an overview on the assessment approach for the Pragmatic Computational Tool. For the assessment, a total of 15 entities were initially contacted, representing diverse sectors and domains in the smart city context. Out of these fifteen entities, nine responded and actively participated in the assessment, providing valuable insights into their specific use cases. The assessment involved the utilization of the Pragmatic Computational Tool to calculate the life cycle costs of IoT devices in the domains of traffic management, environmental monitoring, citizen science, and energy management. In addition to using the tool, a qualitative interview approach was adopted to gather in-depth information and perspectives from the participating entities. This combination of quantitative analysis through the tool and qualitative interviews allowed for a comprehensive assessment of the artifacts' effectiveness and applicability in addressing the unique challenges and requirements of each use case within the smart city context. The assessment results provide valuable insights into the costs associated with using LoRaWAN and NB-IoT technologies in various smart city use cases. The findings indicate that, initially, NB-IoT has lower costs compared to LoRaWAN for a smaller number of installed nodes (up to 5000 nodes). However, as the number of nodes increases beyond this threshold, the cost advantage shifts towards LoRaWAN, making it a more cost-effective option (c.f. Figure 6).