Cities, buildings, and spaces are smart when their "behavior" properly mimics their contexts, accommodating changes and evolving situations. This is only possible if they are able to collect data from the environment using distributed probes, and to filter, correlate, and analyze them appropriately. In this paper we adopt service-based solutions to abstract the probes that are distributed in the environment, as well as to provide the analysis capabilities required to make timely analyses on how a space is evolving. In such scenarios the amount of sensor data that one might need to deal with can be extremely high. Therefore, we provide an infrastructure that can manipulate high degrees of raw sensor data efficiently. The solution is based on complex event processing and recurring patterns, and is exemplified in the context of smart buildings.
['Luciano Baresi', 'Sam Guinea']
Event-Based Monitoring of Service-Oriented Smart Spaces (Invited Paper)