Smart Civic Issue Reporting and Reward System Using Node.js and AI Chatbot

This work presented the architecture, implementation, and experimental evaluation of a Smart Civic Issue Reporting and Reward System designed to improve the efficiency of urban civic issue management. The proposed platform integrates a stateless Node.js/Express.js REST backend secured with JWT authentication, a MongoDB Atlas cloud database with geospatial indexing, a gamified reward computation engine, and a React.js citizen-facing website alongside a dedicated React.js administrative dashboard. An NLP-driven conversational chatbot was incorporated to provide interactive access to civic information and personalised user feedback. Experimental evaluation across eight operational scenarios confirmed reliable system functionality and stable performance. The platform demonstrated an average API response latency of 312 ms. Reward score computation introduced an overhead of less than 50 ms. The integrated chatbot achieved an intent classification accuracy of 94.2%. These results indicate the proposed architecture is technically feasible and suitable for real-world deployment within municipal reporting infrastructures. The system design incorporates behavioural engagement mechanisms derived from established gamification research, ensuring citizen participation aligns with municipal service priorities. By combining incentive-driven citizen reporting and conversational interaction, the platform contributes a unified framework for strengthening digital collaboration between citizens and urban governance systems. Future work will focus on extending the platform through integration with Smart City Integrated Command and Control Centres (ICCC), blockchain-based reward tokenisation, multilingual voice-enabled chatbot capabilities, predictive hotspot analytics using historical reporting data, and direct interoperability with municipal ERP systems for automated work-order management.

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