Autonomous gathering of livestock using a multi-functional sensor network platform

In this paper we develop algorithms and hardware for the autonomous gathering of cattle. We present a comparison of three different autonomous gathering algorithms that employ sound and/or electric stimuli to guide the cattle. We evaluate these algorithms in simulation by extending previous behavioral simulations for cattle. We implemented one of these algorithms and present data from experiments in which cattle were equipped with sensor nodes that allowed cueing with sound and electric stimuli. We discuss the minimum requirements for algorithms and hardware for autonomous gathering

Annotated BPMN models for optimised healthcare resource planning

There is an unquestionable need to improve healthcare processes across all levels of care in order to optimise the use of resources whilst guaranteeing high quality care to patients. However, healthcare processes are generally very complex and have to be fully understood before enhancement suggestions can be made. Modelling with widely used notation such as BPMN (Business Process Modelling and Notation) can help gain a shared understanding of a process, but is not sufficient to understand the needs and demands of resources. We propose an approach to enrich BPMN models with structured annotations which enables us to attach further information to individual elements within the process model. We then use performance analysis (e.g., throughput and utilisation) to reason about resources across a model and propose optimisations. We show the usefulness of our approach for an A&E department of a sizeable hospital in the south of Brazil and how different stakeholders may profit from a richer annotated BPMN-based model.Postprin