IoT-Enabled Middleware for Smart City Environmental Monitoring with Integrated Analytics and Visualization

Abstract

: Smart city systems increasingly depend on data analytics and visualization to support informed and timely decision making in complex urban environments. However, existing middleware solutions predominantly focus on data acquisition and communication, while analytical processing and visualization are typically delegated to external applications, resulting in increased development complexity, reduced reusability, and fragmented system architectures. This study presents analytics and visualization-centric middleware named “Service-Oriented Middleware for Smart City Applications” (SOMSCA), in which these capabilities are embedded directly within the middleware layer. SOMSCA adopts a service-oriented approach, exposing analytics and visualization functionalities as reusable platform services, and incorporates a data-type-oriented visualization strategy along with a template-assisted dash-boarding mechanism to enable dynamic and flexible application development. To validate the proposed approach, a prototype implementation is developed using React, FastAPI, MySQL, and TimescaleDB and evaluated using air-quality data collected from the London Air Quality Network, comprising more than one million observations across multiple pollutants and monitoring locations. The implementation supports real-time, historical, and aggregated analytical services together with dynamic dashboard generation. The results demonstrate the practical feasibility of middleware-integrated analytics and visualization through reusable service creation, flexible dashboard configuration, and interactive environmental monitoring capabilities. These findings highlight the potential of middleware-level intelligence to simplify application development and support data-driven decision making in smart city environment.