City Solution: A Decentralized Smart City Incident Management Platform

Rapid urbanization has increased the complexity of managing civic issues such as waste disposal, road damage, and traffic congestion. Conventional centralized reporting mechanisms often experience inefficiencies, limited scalability, and weak public accountability. To address these limitations, CitySolution introduces a decentralized, web-based incident management platform that enables citizens to submit and monitor civic reports in real time. Each submission includes key details—such as geolocation, category, description, and supporting images—which are securely stored and processed through blockchain technology for immutable record keeping. Images are managed via the InterPlanetary File System (IPFS) to ensure distributed and tamper-resistant storage. The platform also integrates community voting, role-based access control, and status tracking to strengthen transparency and participation. Furthermore, an analytics dashboard visualizes trends and statistics, supporting data-driven decisions for civic authorities. The prototype currently employs an in-memory database for demonstration but can be extended to persistent data systems. Overall, CitySolution demonstrates how decentralized technologies and citizen engagement can foster accountable, efficient, and transparent urban governance.

Centralized, Blockchain, Inter Planetary

1. M. A. Igartua et al., "INRISCO: INcident monitoring in Smart Communities," in IEEE Access, vol. 8, pp. 72435-72460, 2020, doi: 10.1109/ACCESS.2020.2987483. [Google Scholar] [Crossref]

2. L. B. Elvas, C. F. Marreiros, J. M. Dinis, M. C. Pereira, A. L. Martins, and J. C. Ferreira, "Data-Driven Approach for Incident Management in a Smart City," Applied Sciences, vol. 10, no. 22, p. 8281, Nov. 2020, doi: 10.3390/app10228281. [Google Scholar] [Crossref]

3. E. F. Z. Santana, A. P. C. Steinmacher, M. A. Gerosa, F. Kon, and D. Milojicic, "Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture," ACM Computing Surveys, vol. 50, no. 6, pp. 1-37, Jan. 2018, doi: 10.1145/3124391 [Google Scholar] [Crossref]

4. Diallo, E. H., Abdallah, R., Dib, M., & Dib, O. (2024). “Decentralized incident reporting: Mobilizing urban communities with blockchain”. Smart Cities, 7(4), 2283-2317.doi.org/10.3390/smartcities7040090 [Google Scholar] [Crossref]

5. S. Kumar, S. Atreja, A. Singh, and M. Jain, "Adversarial adaptation of scene graph models for understanding civic issues," in Proceedings of the 2019 World Wide Web Conference (WWW '19), San Francisco, CA, USA, pp. 2943-2949, 2019, doi: 10.1145/3308558.3313681. [Google Scholar] [Crossref]

6. J. González-Villa, A. Cuesta, M. Spagnolo, et al., "Decision-support system for safety and security assessment and management in smart cities," Multimedia Tools and Applications, vol. 83, pp. 61971–61994, 2024, doi: 10.1007/s11042-023-16020-6. [Google Scholar] [Crossref]

7. D. Rodríguez-García, V. García-Díaz, and C. González García, "CrowDSL: platform for incidents management in a smart city context," Big Data and Cognitive Computing, vol. 5, no. 3, p. 44, 2021, doi: 10.3390/bdcc5030044. [Google Scholar] [Crossref]

8. F. Shama, A. Aziz, and L. B. M. Deya, "CitySolution: A complaining task distributive mobile application for smart city corporation using deep learning," SoftwareX, vol. 27, p. 101829, 2024, doi: 10.1016/j.softx.2024.101829. [Google Scholar] [Crossref]

9. R. Islam, R. Bose, S. Roy, et al., "Decentralized trust framework for smart cities: a blockchain-enabled cybersecurity and data integrity model," Scientific Reports, vol. 15, p. 23454, 2025, doi: 10.1038/s41598-025-06405-y. [Google Scholar] [Crossref]

10. D. Jung, V. Tran Tuan, D. Quoc Tran, M. Park, and S. Park, "Conceptual framework of an intelligent decision support system for smart city disaster management," Applied Sciences, vol. 10, no. 2, p. 666, 2020, doi: 10.3390/app10020666. [Google Scholar] [Crossref]

11. E. Nyaletey, R. M. Parizi, Q. Zhang and K. -K. R. Choo, "BlockIPFS - Blockchain-Enabled Interplanetary File System for Forensic and Trusted Data Traceability," 2019 IEEE International Conference on Blockchain (Blockchain), Atlanta, GA, USA, 2019, pp. 18-25, doi: 10.1109/Blockchain.2019.00012. [Google Scholar] [Crossref]

12. M. Jlil, K. Jouti, J. Boumhidi and C. Loqman, "Blockchain-Based Mobile Application for Traffic Accident Report's Management," 2024 4th International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET), FEZ, Morocco, 2024, pp. 1-6, doi: 10.1109/IRASET60544.2024.10548282.. [Google Scholar] [Crossref]

13. D. Cetinkaya, J. González-Villa, M. Zanotti, A. Cuesta, and M. Spagnolo, “Decentralized Edge-AI Infrastructure for Public Safety in Smart Cities: A Real-Time Response Model,” IEEE Internet of Things Journal, 2024. [Google Scholar] [Crossref]

14. Sefati, S. S., Craciunescu, R., Arasteh, B., Halunga, S., Fratu, O., & Tal, I. (2024). “Cybersecurity in a scalable smart city framework using blockchain and federated learning for internet of things (iot)”.Smart Cities, 7(5), 2802-2841.doi.org/10.3390/smartcities7050109 [Google Scholar] [Crossref]

15. IJung, D., Tuan, V. T., Tran, D. Q., Park, M., & Park, S. (2020). “Conceptual Framework of an Intelligent Decision Support System for Smart City Disaster Management”. Applied Sciences, 10(2), 640. doi: 10.3390/app10020640. [Google Scholar] [Crossref]

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