Unified Data Model for Wireless Sensor Network

The constant evolution of technology in terms of inexpensive and embedded wireless interfaces and powerful chipsets has led to the massive usage and deployment of wireless sensors networks (WSNs). These networks are made of a growing number of small sensing devices and are used in multiple use cases, such as home automation (e.g., smart buildings), energy management and smart grids, crisis management and security, e-Health, entertainment, and so forth. Sensor devices, generally self-organized in clusters and domain dedicated, are provided by an increasing number of manufacturers, which leads to interoperability problems (e.g., heterogeneous interfaces and/or grounding, heterogeneous descriptions, profiles, models, and so forth). Furthermore, the data provided by these WSNs are very heterogeneous because they are coming from sensing nodes with various abilities (e.g., different sensing ranges, formats, coding schemes, and so forth). In this paper, we propose a solution for handling WSNs’ heterogeneity, as well as easing interoperability management. The solution consists of a semantic open data model for sensor and sensor data generic description. This data model, designed for handling any kind of sensors/actuators and measured data (which is still not the case of existing WSNs data models), is fully detailed and formalized in an original ontology format called MyOntoSens and written using Ontology Web Language 2 description logic language. The proposed ontology has been implemented using Protégé 4.3, prevalidated with pellet reasoner, and is being standardized (A Body Area Network (BAN) dedicated instance of the proposed “MyOntoSens” ontology is being standardized as a Technical Specification (TS) within the SmartBAN Technical Committee of the ETSI (European Telecommunications Standards Institute) standardization body: ETSI SmartBAN Technical Committee website: portal.etsi.org/portal/server.pt/community/SmartBAN/368v). In addition, this original ontology has been prequalified through a runner’s exercise monitoring application, using in particular SPARQL query language, within a small wireless body area network platform comprising heartbeat, GPS sensors, and Android mobile phones.