Quantified specific objectives. Objective #1: Self-* capabilities of sensors and sensor ensembles. Self description: We will investigate metadata formats for sensor self-descriptions, i.e. investigate markup languages suitable for metadata description of sensor typology and interoperability, develop (XML) parsing technologies for very small and tiny execution platforms (i.e. small form factors, low memory footprint, etc.), develop metadata similarity analysis and semantic interoperability of sensor systems, and develop a sensor ontology particularly addressing scenarios of opportunistic sensing. Success Criteria. The ability to provide adequate description of all relevant sensor parameters and variations for different sensor types in the OPPORTUNITY case studies (see objective 7) within a small microcontroller based node (8/16 bit, 4 MHz, <64kByte memory) Dynamic sensor self-characterisation: We develop methods that allow sensors to automatically characterize themselves. In particular we want sensor to be able to automatically detect when their performance degrades. The detection ability should work for degradation caused by internal factors (e.g. drift) as well as environment related degradation (occlusion, displacement). The specific measures that we intend to develop are • Degradation detection based on sudden events followed by long term change in the statistical properties of the signal. Thus for example we might detect a sudden drop in the intensity of the sound detected through a mobile phone microphone followed by all the statistical properties except the intensity being unchanged. This would indicate that the phone was placed in a pocket damping the sound intensity. • Using information about user activity and context to re-calibrate the sensors. In previous work we have demonstrated how the knowledge that the user is walking can be used to determine the on body placement of an acceleration sensor. We intend to develop similar methods for other sensors and variation types. Success Criteria: Demonstration in the OPPORTUNITY cases studies (see objective 7) that we can detect degradation with a precision and recall both in the range of 90% and an accuracy (in terms of degree of degradation) of about plus/minus 20%. Examples of specific types of degradation that we will focus on are position changes of on body motion sensors, intensity variations in on body sound sensors caused by different enclosures (e.g. e mobile phone being put onto a bag) and signal strength variations in RF pos...
