Taxonomy and software architecture for real-time context-aware collaborative smart environments

The widespread of Internet of Things (IoT) and the price reduction and ubiquity of telecommunications has led to the emergence of smart environments where devices are becoming increasingly smarter and everything is connected and from which society aims to benefit. The data obtained from IoT is rapidly processed in various domains for the achievement of smart cities and societies. However, in many cases, applications are not contextualized by using data from outside the domain but are only contextualized using data from the domain itself, missing the opportunity for further contextualization. The lack of common criteria for the integration of data from different application domains is one of the main reasons that significantly hinders the integration of third-party data into real-time processing and decision-making systems and thus, the context awareness of developed applications. Although the use of several taxonomies and ontologies for context awareness in various application domains have been proposed, in many cases they are highly domain specific and/or difficult to integrate with other systems, which makes it challenging to facilitate data sharing between different systems and their processing to achieve enhanced context awareness. We aim to contribute to the addressing of these limitations through a reusable and extensible multi-domain taxonomy targeted to collaborative IoT and smart environments, which is also automatically integrated into a software architecture with real-time complex event processing technologies. The proposed solution has been illustrated through a case study and performance tests have been carried out in different computing capacity scenarios, showing its feasibility and usefulness.