Data Mining for Predictive Maintenance in Smart Cities

This project explores the application of data mining techniques for predictive maintenance within smart cities. As urban areas become increasingly complex, the integration of Internet of Things (IoT) devices generates vast amounts of data, which can be harnessed to improve city services and infrastructure management. By employing advanced data mining algorithms, this study aims to analyze real-time data from various city systems—such as transportation, utilities, and public services—to predict equipment failures and optimize maintenance schedules. The outcomes of this research will provide insights into enhancing operational efficiency, reducing costs, and improving the quality of life for urban residents. Additionally, the project highlights the challenges and opportunities associated with implementing predictive maintenance strategies in the context of smart cities.