The Internet of Things (IoT) aims to integrate arbitrary things with the Internet. Sadly, the majority of things lacks of the ability to communicate which makes a direct integration with a communication network, i.e., the Internet, impossible. We overcome this limitation by introducing refined versions of Semantic Entities, i.e., Web representations of arbitrary real-world things states using (possibly aggregated) sensor values. Sensors can be considered ubiquitous, e.g., due to the omnipresence of smartphones. Our architecture of a Semantic Web of Things bases on sensors providing their measurements in the form of RDF1. We account for the common fact of resource constraints on sensor platforms by introducing a scalable caching mechanism for RDF data within a network of proxies (SSPs). Consequently, the individual Semantic Entities find and aggregate relevant (sensor) data via SPARQL. Besides scalability, the proxies also solve the issue of the sensor platforms diversity in terms of communication interfaces.
['Oliver Kleine', 'Sebsatian Ebers', 'Myriam Leggieri']
Monitoring urban traffic using semantic web services on smartphones - a case study