Multi-level Processing of Sensory Data with Evidence Theory

There is no doubt that Internet of Things becomes an important component of future governmental, industrial, commercial and private infrastructures. Interconnected devices, from intelligent ones to simple sensors, will continuously generate enormous amounts of data. It seems impossible to have all this data being transmitted to dedicated processing centres. More and more often, attention is being put on different forms of local, multi-source and multi-level data processing schemas. In this paper, we propose a novel approach to process sensory data in a multi-level fashion. We use elements of Evidence Theory and adopt a newly developed method suitable for satisfying uncertain targets to assess the most adequate state of monitored system/phenomena. We perform this in stages, where observable values are required at the lowest level of processing, while calculations occurring on higher levels use the results of lower level computations. At the same time, levels of belief in the assessed states of a system/phenomena are determined.