# A Web-Based Application for Smart City Data Analysis and Visualization
## 6 Conclusions and Future Work  
This article proposes a modular, web-based platform for analyzing and visualizing urban sensor input streams, developed using datasets provided by the Basel _Smarte Strasse_ project. Our application unifies diverse data streams, including air quality, traffic noise, vehicle counts, parking occupancy, and EV charging, to provide a comprehensive view of environmental and infrastructural conditions in urban areas. Based on SARIMAX, \(k\)-NN imputation, and random forest regressors, the platform's backend processes heterogeneous data effectively, addressing missing values and improving data reliability. On the contrary, its frontend combines interactive maps, time-series plots, and correlation heatmaps. Visualization is an efficient and intuitive tool for representing urban data and enabling users to explore trends and relationships across space and time, enhancing decision-making. In addition, for experts, these visual tools offer actionable insights into infrastructure optimization and environmental interventions. At the same time, our web-based platform emphasizes usability and adaptability through a responsive interface, while integrated caching strategies ensure smooth performance during repeated and data-intensive exploration tasks.  
Future plans include extending the pipeline to support real-time sensor data, enabling live dashboards, and triggering alerts for environmental and traffic monitoring purposes. Integrating more advanced predictive models could also support the casting  
Figure 15: Sample output from the privacy-aware low-resolution camera used in the project. Despite limited fidelity, parking occupancy detection remained effective while protecting individual identities. The entire field of view, except for the parking spots, is blacked out to ensure no surrounding personal or identifiable information is visible [68].  
of pollutant concentrations, noise levels, or traffic flows, thereby assisting in proactive urban planning. Furthermore, linking the platform with public transport APIs, weather data, or health records could enable cross-domain insights, e.g., analyzing the relationship between pollution spikes and respiratory health indicators.  
Conceptualization, P.K. and K.A.T.; methodology, P.K.; software, P.K.; validation, P.K., D.I., and K.A.T; formal analysis, D.I. and P.C.; investigation, K.A.T.; resources, P.K.; data curation, P.K.; writing--original draft preparation, P.K.; writing--review and editing, D.I., P.C., and K.A.T.; visualization, P.K.; supervision, K.A.T.; project administration, K.A.T.; funding acquisition, K.A.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The dataset used is available online at [[https://data.bs.ch/explore/?refine.tags=smarte+strasse](https://data.bs.ch/explore/?refine.tags=smarte+strasse)]([https://data.bs.ch/explore/?refine.tags=smarte+strasse](https://data.bs.ch/explore/?refine.tags=smarte+strasse)) (accessed on 3 February 2025) and the source code of the developed system can be found at [[https://github.com/[PERSON]/Web-Based-Data-Analysis-and-Visualization](https://github.com/PanagiotisKara/Web-Based-Data-Analysis-and-Visualization)]([https://github.com/PanagiotisKara/Web-Based-Data-Analysis-and-Visualization](https://github.com/PanagiotisKara/Web-Based-Data-Analysis-and-Visualization)) (accessed on 21 April 2025).  
This work was conducted as part of the COST Action (Grant CA20120), _Intelligence-Enabling Radio Communications for Seamless Inclusive Interactions (INTERACT)_  
The authors declare no conflicts of interest.