Discrete-event requirements model for sensor fusion to provide real-time diagnostic feedback

Abstract

Minimally-invasive surgical techniques reduce the size of the access corridor and affected zones resulting in limited real-time perceptual information available to the practitioners. A real-time feedback system is required to offset deficiencies in perceptual information. This feedback system acquires data from multiple sensors and fuses these data to extract pertinent information within defined time windows. To perform this task, a set of computing components interact with each other resulting in a discrete event dynamic system. In this work, a new discrete event requirements model for sensor fusion has been proposed to ensure logical and temporal correctness of the operation of the real-time diagnostic feedback system. This proposed scheme models system requirements as a Petri net based discrete event dynamic machine. The graphical representation and quantitative analysis of this model has been developed. Having a natural graphical property, this Petri net based model enables the requirements engineer to communicate intuitively with the client to avoid faults in the early phase of the development process. The quantitative analysis helps justify the logical and temporal correctness of the operation of the system. It has been shown that this model can be analyzed to check the presence of deadlock, reachability, and repetitiveness of the operation of the sensor fusion system. This proposed novel technique to model the requirements of sensor fusion as a discrete event dynamic system has the potential to realize highly reliable real-time diagnostic feedback system for many applications, such as minimally invasive instrumentation.