Storing and Indexing IoT Context for Smart City Applications

IoT system interoperability, data fusion, data discovery and access control for providing Context-as-a-Service as well as tools for building context-aware smart city applications are all significant research challenges for IoT-enabled smart cities. These middleware platforms have to cope with potentially big data generated from millions of devices in large cities. The amount of context, metadata, annotations in IoT ecosystems equals and may even exceed the amount of raw data. This paper discusses the challenges of context storage, retrieval and indexing for smart city applications. We analyse, compare and categorise existing approaches, tools and technologies relevant to the identified challenges. The paper proposes a conceptual architecture of a hybrid context storage and indexing mechanism that enables and supports the Context Spaces theory based representation of context for large-scale smart city applications. We illustrate the proposed approach using solid waste management system with adaptive on-demand garbage collection from IoT-enabled garbage bins.