SoProMon – Sonification for Process Monitoring

SoProMon (Sonification for Process Monitoring) investigates how to best support users in the real-time monitoring of processes by presenting process-relevant data using both visuals and audio. The project is being carried out as a joint cooperation between the Ambient Intelligence Group at CITEC/Bielefeld University and the research group Workflow Systems and Technology of University of Vienna.  As process monitoring is a task that is often performed in parallel to other tasks, we specifically investigate the usage of sonification, the presentation of data as (non-speech) sound, to enhance current visual-based monitoring approaches. Auditory alerts and alarms are already in use in many control centers but come with several drawbacks, such as the possibility of so-called "alarm floods", in which operators do not take alarms as seriously as they are or ignore them altogether due to an excessive amount of occurring alerts.  However, apart from simple auditory cues, more complex sonifications are capable to represent continuous data streams for instance by mapping data to auditory features of sound, such as pitch, level, duration, timbre, brightness, roughness or spatial location of sound events.  The SoProMon project thus aims at investigating the use of sonification to enhance current visual process monitoring systems for a) its application in control centers, such as e.g. in Industrial production and logistics, Power Plants, Road traffic or Mass Transit Control Centers, but also for b), areas that typically do not feature full-time monitoring personnel, but rather employees that need to monitor processes in parallel to their main work, such as e.g. office clerks that need to monitor administrative processes, such as e.g. insurance claims, Managers and supervisors that want to keep an overview over their business processes, IT administrators that monitor e-commerce processes or need to be informed about potential network intrusions. The SoProMon project specifically tries to answer the question which kind of sound-assisted monitoring is best suited for what kind of usage scenarios, as well as how different types of sound-enhanced process monitoring attract and direct attention and concentration. To reach these goals, we develop specific methods for specific information types and tools for their integration into practical multi-modal monitoring scenarios, and we evaluate their effectiveness, acceptance and utility to organize a user’s focus of attention.

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