Real time air quality monitoring with fog computing enabled IoT system: an experimental study

Fog computing has the benefits to handle and reduce data traffic load towards the central cloud in IoT systems. These benefits are facilitated with the help of offloaded fog services that participate in the decision making processes. Besides, fog-based systems have the potential to mitigate scalability bottlenecks that occur in cloud-based systems. In this study, we elaborate on fog based design for a scalable real time air quality monitoring and alert generation system. We established an emulation test bed with real data collected from air quality sensing nodes deployed around Bangkok and vicinity areas to understand the behavior of the proposed solution in terms of waiting time characteristics. We analyzed the performance of the system in two design scenarios; first scenario is built with the proposed fog solution and the second one is the cloud-based approach. We present the performance results revealing the advantages of the proposed model, for the number of air box nodes scaling up to 120 and the number of client nodes up to 200.