The aims of this pilot project are thus:
To create a lightweight model to represent information about devices in the IoT such as: capabilities, security properties, ownership and provenance of devices and services. This will involve building upon existing work being conducted within the dot.rural Digital Economy Hub on vocabularies to describe sensors and Internet enabled devices using the W3C Semantic sensor network ontology and existing work on provenance.
To build a “Trusted Things” software framework based on Semantic Web technologies and services to store and query information about devices in the IoT and their associated provenance. (This will involve attaching NFC tags to ‘things’; To develop an initial set of guidelines that could support IoT developers to describe information about devices according to our model. This will include specific guidelines on how provenance of the information generated by such devices can be tracked and how devices can be instrumented to provide real_time information to the “Trusted Things” software platform.
To evaluate this approach using a demonstrator application based on two transport related scenarios: the use of passive NFC tags in bus shelters in Aberdeenshire; the use of in-car black boxes to track the behaviour of drivers for insurance purposes. The latter will be possible by building a black box based on an Arduino programmable board and sensors. This will collect driving data such as speed, acceleration braking forces, route data and timing of journeys using a combination of GPS and accelerometer data and will transmit this to a our framework using an on_board 3G connection.
Edoardo Pignotti leader of Trusted Tiny Things is a Research Fellow working on trust and provenance issues in Linked Data at the dot.rural Digital Economy Hub at the University of Aberdeen. He has more than seven years experience in Semantic Web technologies, provenance and policy based reasoning gained during his involvement with a number of UK eScience projects.
Further information here: http://t3.abdn.ac.uk