Ontology-based Classification and Analysis of non- emergency Smart-city Events

TL;DR

This paper introduces an ontology-based system leveraging Open311 to classify, report, and analyze non-emergency city events, enhancing citizen engagement and urban service integration in smart cities.

Contribution

It presents a novel semantic model using linked open data for classifying and managing non-emergency city events across multiple urban centers.

Findings

Improves event classification accuracy

Enables seamless citizen reporting and redressal

Facilitates data integration across civic bodies

Abstract

Several challenges are faced by citizens of urban centers while dealing with day-to-day events, and the absence of a centralised reporting mechanism makes event-reporting and redressal a daunting task. With the push on information technology to adapt to the needs of smart-cities and integrate urban civic services, the use of Open311 architecture presents an interesting solution. In this paper, we present a novel approach that uses an existing Open311 ontology to classify and report non-emergency city-events, as well as to guide the citizen to the points of redressal. The use of linked open data and the semantic model serves to provide contextual meaning and make vast amounts of content hyper-connected and easily-searchable. Such a one-size-fits-all model also ensures reusability and effective visualisation and analysis of data across several cities. By integrating urban services across various civic bodies, the proposed approach provides a single endpoint to the citizen, which is imperative for smooth functioning of smart cities.