Vikaspath: Crowdsourced Civic Issue Reporting and Resolution System
DOI:
https://doi.org/10.15662/IJEETR.2026.0802129Keywords:
Smart City, Urban Intelligence, Civic Issue Reporting, Multimodal Artificial Intelligence, Agentic Systems, Computer Vision, Natural Language Processing, Predictive Analytics, E-Governance, Crowd ValidationAbstract
The rapid expansion of urban areas has heightened the intricacy of civic management, resulting in ongoing issues such as traffic congestion, infrastructure breakdowns, waste overflow, and disturbances related to crowds. Traditional civic grievance systems tend to be reactive, disjointed, and lacking in transparency, which leads to slow responses and a decline in public trust. This paper presents Vikas Path, an AI-driven urban intelligence platform aimed at facilitating real-time, citizen-focused, and predictive city management. The system consolidates various inputs—including images, text, voice, and geolocation—through a single mobile application. Utilizing computer vision, natural language processing, and data deduplication methods, the platform automatically classifies, verifies, and prioritizes civic issues, while crowd validation improves data accuracy. A conversational interface allows for natural language reporting, and predictive analytics pinpoint potential urban risk hotspots. Experimental findings indicate enhanced classification accuracy, decreased complaint redundancy, quicker resolution times, and heightened civic engagement, underscoring the platform’s efficacy in fostering transparent, proactive, and sustainable governance in smart cities.
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