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ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue XI November 2025

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City Solution: A Decentralized Smart City Incident Management

Platform

Muccharla Praveen

, Dubba Rohith

, Tangudu Swetha

, Kanchu Naveen

, Patnala Satish Kumar

1,2,3,4

B. Tech graduate Dept of CSE – Artificial Intelligence & Machine Learning GMR Institute of

Technology, Rajam, India

Assoc. Professor Dept of CSE – Artificial Intelligence & Machine Learning GMR Institute of

Technology, Rajam, India

DOI: https://dx.doi.org/10.51584/IJRIAS.2025.101100012

Received: 12 November 2025; Accepted: 23 November 2025; Published: 03 December 2025

ABSTRACT

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.

Keywords: Centralized, Blockchain, Inter Planetary File System (IPFS), City Solution, Tamper-Resistant

Storage.

INTRODUCTION

The rapid growth of urban population has amplified several civic challenges, including inefficient waste

collection, traffic congestion, flooding, and deteriorating public infrastructure. These issues not only disrupt

daily activities but also weaken the effectiveness and credibility of local administrations. Traditional incident

reporting systems are typically centralized, hierarchical, and time-consuming, which often leads to delays, poor

citizen engagement, and limited transparency in the resolution process.

As cities move toward smart and connected governance, there is a growing need for platforms that empower

citizens to actively participate in problem reporting and monitoring. CitySolution addresses this need through a

decentralized, web-based framework designed to handle real-time civic issue submission, tracking, and

management. The system employs a Node.js (Express) backend combined with a React.js frontend to deliver a

responsive and user-friendly interface. Citizens can register and report incidents by providing details such as

category, description, image, and geolocation, ensuring structured and accurate data collection.

To maintain data security and trust, the platform integrates blockchain technology for immutable record keeping

and InterPlanetary File System (IPFS) for decentralized media storage. Each report is authenticated through

JSON Web Tokens (JWT) and managed using role-based access control (RBAC) to prevent unauthorized

actions. An interactive analytics dashboard further enhances administrative efficiency by presenting live

visualizations, including issue trends, user activity, and category-wise distributions.

The current implementation of CitySolution functions with an in-memory database for testing purposes but is

designed to easily integrate with scalable, persistent data storage systems. By combining decentralization,

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)

ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue XI November 2025

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transparency, and citizen participation, CitySolution establishes a robust foundation for smart urban governance,

promoting accountability, efficiency, and community-driven decision-making.

Literature Survey

A range of studies in recent years has explored intelligent and decentralized approaches for managing urban

incidents, reflecting the growing interest in smart city governance and citizen participation. Mónica Aguilar

Igartua et al. (2020) introduced INRISCO, a framework that leverages citizen devices, vehicles, and social media

to function as real-time sensors for community incident detection. Their system integrates structured and

unstructured data to improve anomaly detection and situational awareness through big data analytics, enabling

faster and more informed responses to urban challenges.

Luís B. Elvas et al. (2020) performed a large-scale analysis of over six thousand incidents reported in Lisbon,

including fires and infrastructure failures. Using the CRISP-DM data-mining methodology, the authors

demonstrated how statistical modeling and visualization techniques such as heatmaps can help identify spatial

and environmental correlations among urban risks.

In a related direction, Eduardo Felipe Zambom Santana et al. (2016) outlined the architectural requirements of

software platforms for smart cities. Their proposed unified framework emphasized interoperability, scalability,

and real-time data processing, laying the foundation for future integrated urban management systems.

El-hacen Diallo et al. (2024) proposed a decentralized reporting model built on blockchain, where each citizen

submission is verified and stored immutably using smart contracts. This approach significantly enhances data

reliability, eliminates duplicate reports, and strengthens trust between citizens and authorities.

Advances in artificial intelligence have also influenced civic issue detection. Shanu Kumar et al. (2019)

employed an adversarial scene graph model that uses object detection and relational reasoning to identify and

interpret civic problems from images. Their work demonstrated how AI can capture spatial relationships and

improve the accuracy of issue classification.

J. González-Villa et al. (2024) designed a decision-support system that integrates sensor data, citizen inputs, and

social media to assess safety risks in real time. Their framework combines predictive analytics and visualization

dashboards to aid authorities in risk forecasting and resource allocation.

Similarly, Dario Rodríguez-García et al. (2021) developed CrowDSL, a distributed platform that enables

collective reporting and verification of incidents through crowdsourcing. The system uses task allocation

strategies to validate citizen reports efficiently, optimizing response time and resource management.

Farhatun Shama et al. (2024) presented a blockchain-enabled mobile application, also named CitySolution, that

combines deep learning-based image classification with decentralized storage. Their design highlights the

potential of integrating AI and blockchain to enhance transparency and prioritization in civic complaint handling.

Mohammad Dib et al. (2025) proposed a blockchain-based trust framework aimed at securing smart city IoT

networks. Their model focuses on ensuring data integrity and accountability through tamper-proof

communication between sensors, citizens, and authorities.

Luke Summers et al. (2020) developed a decision-support platform for disaster response using real-time sensors

and predictive modeling. This system provides situational awareness and automates resource distribution during

emergencies, demonstrating the importance of data fusion in urban resilience.

Further, Mohammad Dib et al. (2019) introduced BlockIPFS, which combines blockchain and IPFS to guarantee

verifiable, traceable, and scalable data management in smart city infrastructures. The fusion of these technologies

addresses the challenge of storing large civic datasets securely and transparently.

Mohammad Jlil et al. (2024) implemented a blockchain-based mobile system for traffic incident reporting,

ensuring that verified cases are immutably recorded and that notifications reach authorities instantly.

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)

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In another contribution, Mohammad Dib et al. (2023) proposed a decentralized edge-AI infrastructure capable

of local data processing for public safety monitoring. By minimizing latency and reducing dependency on

centralized servers, this approach supports real-time responsiveness.

Mohammad Dib et al. (2024) also examined the integration of blockchain and federated learning for

cybersecurity in smart city environments, emphasizing privacy-preserving model training and secure data

exchange across IoT nodes.

Finally, Luke Summers et al. (2020) emphasized that the combination of artificial intelligence, blockchain, and

IoT technologies can dramatically improve decision-making processes in disaster management. Their model

showcased how predictive analytics and integrated communication systems enhance early risk detection and

coordinated emergency response.

Collectively, these studies illustrate the evolution of smart city solutions toward decentralized, intelligent, and

citizen-oriented systems. The insights derived from this body of research directly inform the design of

CitySolution, which seeks to integrate blockchain, IPFS, and data analytics for efficient, transparent, and

participatory urban incident management.

METHODOLOGY

Citizen Interaction

Fig 2.1.1: Interactive Page for Users

The CitySolution platform is designed to provide an intuitive and accessible interface that encourages citizens

to report the civic problems such are like potholes, garbage accumulation, drainage blockages etc., The frontend,

developed using React.js, HTML, and CSS, communicates seamlessly with a Node.js (Express) backend to

ensure smooth and responsive data exchange. When a citizen submits a report, they provide essential details—

such as the issue category, description, image, and geolocation coordinates—automatically tagged with a

timestamp for accuracy. This real-time reporting process strengthens civic participation by allowing users to

contribute directly to improving their surroundings while supplying city administrators with valuable, location-

specific data for analysis.

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)

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Data Management and Blockchain Integration

Once a report is submitted, the backend processes and stores the information securely through JWT-based

authentication and Role-Based Access Control (RBAC) to ensure only for authorized accessed people. Each

incident’s metadata—such as type, timestamp, and location—is stored in a MySQL relational database for

structured retrieval and analysis.

To uphold data transparency and immutability, verified reports are written onto a blockchain ledger, where smart

contracts validate each submission and prevent duplication or falsification. In parallel, associated media files

(e.g., images) are uploaded to the Inter Planetary File System (IPFS), providing a decentralized, tamper-resistant

storage that scales efficiently with growing data volumes. This integration of blockchain and IPFS ensures trust,

auditability, and long-term data preservation within the civic reporting ecosystem.

Output Generation and Visualization

After the successful verification and recording of incidents, the platform generates dynamic reports summarizing

crucial information such as incident type, location, submission time, and current status.

Administrators and authorized personnel can access an interactive analytics dashboard that provides real-time

visualizations, including heatmaps, frequency distributions, and issue trends. The dashboard supports multiple

filtering options by category, severity, or location, enabling decision-makers to prioritize issues effectively.

Furthermore, embedded statistical tools reveal community voting trends, report resolution rates, and user

participation metrics—allowing data-driven planning and resource allocation for city authorities.

Fig 2.3.1: Output Generation and Visualization

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)

ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue XI November 2025

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Workflow Overview

Fig 2.4.1: Workflow of the Project

The CitySolution workflow begins when citizens submit reports via the web interface. The backend authenticates

the user, validates the data, and records the verified report on the blockchain ledger. Uploaded images are

simultaneously stored on IPFS, and all incident details are made accessible through the administrative dashboard.

This modular and scalable architecture ensures continuous synchronization between components, resulting in

transparent data management, enhanced scalability, and improved accountability. By combining decentralized

storage, secure authentication, and real-time visualization, CitySolution demonstrates a comprehensive model

for next-generation digital governance and civic management.

RESULTS & CONCLUSION

Demonstrated Feasibility and System Performance

The developed CitySolution prototype successfully demonstrates the viability of a decentralized reporting

framework for smart city governance. The integration of React-based frontend, blockchain ledger, and IPFS

INTERNATIONAL JOURNAL OF RESEARCH AND INNOVATION IN APPLIED SCIENCE (IJRIAS)

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storage confirms that the proposed system can securely handle and manage large volumes of civic data in a

transparent and scalable manner.

The complete workflow—from incident submission to verification and display on the dashboard—was

implemented using well-defined APIs. This ensures smooth data exchange, integrity, and real-time traceability

of citizen reports. The use of IPFS significantly improves scalability by offloading large media files from the

blockchain, thereby maintaining system efficiency. For an estimated 10⁸ incident records, the combined storage

requirement remains under 200 GB, demonstrating the compactness of the design.

User testing indicates that the interface is intuitive and responsive, providing citizens with location-based

reporting through GPS integration and map visualization. The built-in voting mechanism enables collective

validation of incidents, strengthening the participatory nature of the system and creating opportunities for future

incentive-based engagement.

From a performance perspective, adopting the Quorum blockchain (Raft consensus) architecture resulted in an

average latency below 15 seconds and throughput between 200–500 transactions per second (TPS). These results

indicate that the framework can support near real-time updates, outperforming traditional centralized

architectures in both responsiveness and data integrity.

Table 3.1.1: System Performance Summary

Parameter

Measured Value

Technology Used

Throughput

200–500 TPS

Quorum (Raft Consensus)

Latency

< 15 seconds

Quorum Blockchain

Estimated Storage (10⁸ incidents)

< 200 GB

Blockchain + IPFS

CONCLUSION

The CitySolution framework presents an innovative and practical approach to decentralized urban incident

management. By merging Blockchain, IPFS, and a React-based decentralized application (DApp), it establishes

a secure, transparent, and citizen-focused reporting ecosystem. The system ensures a complete incident life

cycle—from data submission and validation to visualization and analysis—while maintaining data integrity and

privacy.

Compared with conventional centralized models, CitySolution demonstrates substantial improvements in

accountability, data transparency, and operational scalability. The immutable nature of blockchain records and

distributed image storage enhances trust and reliability in civic governance.

For future work, the project aims to implement a Reputation and Incentive Model through smart contracts,

rewarding citizens for valid and verified reports. Additional research will focus on integrating AI-driven

analytics for automated issue classification and trend detection, as well as extending the system to support large-

scale real-world deployments. Improvements to user experience, feedback collection, and adaptive dashboards

will also contribute to the platform’s long-term sustainability and impact.

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