Recent advances in sensor technology and information processing have allowed connected environments to impact various application domains. In order to detect events in these environments, existing works rely on the sensed data. However, these works are not re-usable since they statically define the targeted events (i.e., the definitions are hard to modify when needed). Here, we present a generic framework for event detection composed of (i) a representation of the environment; (ii) an event detection mechanism; and (iii) an Event Query Language (EQL) for user/framework interaction. This paper focuses on detailing the EQL which allows the definition of the data model components, handles instances of each component, protects the security/privacy of data/users, and defines/detects events. We also propose a query optimizer in order to handle the dynamicity of the environment and spatial/temporal constraints. We finally illustrate the EQL and conclude the paper with some future works.

Semantic web techniques (e.g., ontologies) have been recently adopted for sensor network modeling. However, existing works do not fully address these challenges: (i) representing different sensor types (e.g., mobile/static sensors) to enrich the network with different data and ensure better coverage; (ii) representing a variety of platforms (e.g., environments, devices) for sensor deployment, thus, integrating new components (e.g., mobile phones); (iii) representing the diverse data (scalar/multimedia) needed for various applications (e.g., event detection); and (iv) proposing a generic model to allow re-usability in various application domains. In this paper, we propose HSSN, an ontology that extends the Semantic Sensor Network (SSN) ontology which is already re-usable and considers various platforms. We extend the representation of sensors, sensed data, and deployment environments to cope with these challenges. We evaluate the consistency, accuracy, clarity, and performance of HSSN.