Performance Evaluation of Interoperability and Control Implementation for IoT-Based Smart Spaces

Abstract

The integration of IoT devices and the development of smart cities have brought about significant changes in urban infrastructure. Smart spaces represent a pivotal use case, exemplifying the integration of IoT sensors to enhance automation and decision-making. In these environments, interoperability is critical when incompatible devices interact, enabling seamless communication and optimized performance. To the best of our knowledge, this is the first work to present a comparative evaluation of systems with and without interoperability, focusing on end-to-end system performance and highlighting the importance of interoperability in real-time smart space control. Towards this, we implemented a multi-layered architecture consisting of a novel Controller Layer (CL) that drives the interactions between air quality sensing and actuation of the window and air purifier. Additionally, the architecture consists of the Device Layer (DL), Data Monitoring Layer (DML), and Data Storage Layer (DSL). The DML uses oneM2M as middleware to achieve interoperability among indoor and outdoor air-quality sensors and actuators, such as a window controller and an air purifier. Our focus is on assessing the end-to-end performance of interconnected dependent actions and the significance of response time across incompatible devices. Experimental results show correlations between window controller and air-purifier states based on sensor data, offering insights into achieving interoperability in smart spaces and improving real-time air-quality management.