Reasoning on Data Streams for Situation Awareness
نویسندگان
چکیده
Information overload is a severe problem for human operators of large-scale control systems, for instance, in road traffic management. In order to determine a complete and coherent view of the overall situation (i. e., gain situation awareness), an operator of such a system must consider various heterogeneous sources providing streams of information about a large number of real-world objects. Since the usage of ontologies has been regarded to be beneficial for achieving situation awareness, various ontology-driven situation awareness systems have been proposed. Coping with evolving and volatile individuals in ontologies, however, has not been their focus up to now. In this paper, we describe how concepts from data stream management systems and stream reasoning, such as sliding windows, continuous queries, and incremental reasoning, can be adjusted to support reasoning over highly dynamic ontologies for situation awareness. We conclude our paper with a prototypical implementation and a discussion of lessons learned, pointing to directions of future work.
منابع مشابه
Enhancing the Situation Awareness of Decision Makers by Applying Case-Based Reasoning on Streaming Data
Data is generally expected to continue its exponential growth the next five to ten years. However, it is commonly agreed that the amount of data that currently exist is abundant and that there is still much to achieve with it. The industry, in general, has recognized both the growth and the need to analyze the data. This is also the case with oil well drilling operations. Currently, operators m...
متن کاملTowards Managing Uncertain Spatial Information for Situational Awareness Applications
Situational awareness (SA) applications monitor the real world and the entities therein to support tasks such as rapid decision-making, reasoning, and analysis. Raw input about unfolding events may arrive from variety of sources in the form of sensor data, video streams, human observations, and so on, from which events of interest are extracted. Location is one of the most important attributes ...
متن کاملOn the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition
Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA) technology. We propose a situation recognition framework where temporal probabi...
متن کاملDENIED OPERATIONAL ENVIRONMENTS MULTI-ENTITY BAYESIAN NETWORKS LEARNING IN PREDICTIVE SITUATION AWARENESS Topic 3: Data, Information and Knowledge
Over the past two decades, machine learning has led to substantial changes in Data Fusion Systems throughout the world. One of the most important application areas for data fusion is situation awareness to support command and control. Situation Awareness is perception of elements in the environment, comprehension of the current situation, and projection of future status before decision making. ...
متن کاملSpecial Section on Intelligent Systems for the Internet of Things
Internet of Things (IoT) brings the third development wave of the global information industry, which makes users, network, and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response, and predicting the development trend of...
متن کامل