Real-Time Data Infrastructure Enhancements for Smart City Applications

As a forward-thinking SME dedicated to the evolution of Smart Cities, we aim to upgrade our existing data infrastructure to support real-time data streaming and analytics. The project's core objective is to build a scalable and efficient data engineering pipeline that can manage diverse data sources, including IoT devices, sensors, and public data feeds. By leveraging technologies such as Apache Kafka for event streaming and Apache Spark for data processing, we aim to enhance our data mesh architecture, allowing for decentralized data management and better data observability. Additionally, we seek to implement MLOps practices to streamline the deployment and monitoring of machine learning models, ensuring that our smart city solutions are data-driven, agile, and responsive to urban changes. The successful implementation of this project will provide our city management clients with actionable insights, improve operational efficiency, and significantly enhance citizen services.