Entity Notation: enabling knowledge representations for resource-constrained sensors
The forthcoming ambient systems will contain a large amount of sensors. Representing the data produced by these sensors in a format suitable for ambient intelligence applications would enable a large number of useful services. However, such formats tend to require processing power and communication bandwidth not available in many sensors utilizing ultra low-power microcontrollers and radio chip solutions. This paper presents a lightweight data representation, Entity Notation, to tackle this problem. Sensors with limited computation and communication capabilities can use Entity Notation to describe the data they produce. Entity Notation can be transformed into knowledge representations in a straightforward manner, and hence, the data produced by sensor nodes can be utilized with ease by any ambient intelligence system compatible with the common knowledge representations. This paper presents the design of Entity Notation, its implementations on embedded sensors and the evaluation of its performance.
lightweight knowledge representation embedded sensing semantic web technologies rdf