AI-based Intelligent Smart City Complaint Management System
Keywords:
Artificial intelligence, Complaint management system, Cosine similarity, Machine learning, Naive Bayes, Natural language processing, Smart city, TF-IDFAbstract
As urbanization increases, the complexities faced while handling citizen problems and complaints increase as well. Complaint management systems in smart cities rely on artificial intelligence (AI). This project revolves around a complaint management system for smart cities that aims to streamline the process by reducing human intervention while handling complaints effectively and accurately. The system is fully automated; complaints are raised by citizens, and then AI processes them automatically by prioritizing, deduplicating, classifying and tracking them. The system was coded in Python language using Tkinter library for its user interface design, whereas for record-keeping and storage of information, SQLite database is used. Complaints management involves the implementation of natural language processing techniques to analyze complaints received in the form of texts. For classification of complaints, the text-to-vector conversion technique called term frequency-inverse document frequency (TF-IDF) and Naive Bayesian classifier were applied. Furthermore, cosine similarity technique was implemented to detect duplicate complaints. Moreover, a priority system was developed that ranks complaints in the order of urgency, so complaints with high priority come first and get processed. When a complaint is raised, a tracking ID is provided to the complainant so he/she can track its progress. All this will ensure that the reaction time is reduced while improving accuracy, thus making the entire process easier and better scalable. Ultimately, it can be argued that this is an intelligent solution to problems of smart cities.
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