Searching the ´Web of Things´

With the proliferation of connected devices and the widespread adoption of the Web, ubiquitous computing success has recently been brought into the fashion of an emergent paradigm called the ´Web of Things´, where Web-enabled objects are offered through interconnected smart spaces. While some predict a near future with billions of Web-enabled objects, the success of this vision now depends on the creation of efficient processes and the availability of tools enabling users or applications to find connected objects matching a set of requirements (and expectations). We present an on-going work that aims to develop a search process dedicated to the ´Web of Things´ and that relies on three contributions. The creation and use of semantic profiles for connected objects, the establishment of similarities between semantic profiles of different connected objects to gather them into clusters and, the computation of a score associating a ´context of search´ to an incoming request and enabling the selection of the most appropriate search algorithms, involving either probabilistic or precise reasoning.