{"title":"Proactive Computing in Process Monitoring: Information Agents for Operator Support","authors":"A. Pakonen, T. Pirttioja, I. Seilonen, T. Tommila","doi":"10.1109/ETFA.2006.355408","DOIUrl":null,"url":null,"abstract":"While automation systems can track thousands of measurements it is still up to human process operators to determine the operational situation of the controlled process, particularly in abnormal situations. To fully exploit the computing power of embedded processors and to release humans from simple data harvesting activities, the concept of proactive computing tries to exploit the strengths of both man and machine. Proactive features can be implemented using intelligent agent technology, enabling humans to move from simple interaction with computers into supervisory tasks. Autonomous information agents can handle massive amounts of heterogeneous data. They perform tedious tasks of information retrieving, combining and monitoring on the behalf of their users. This paper presents a multi-agent-based architecture for process automation, which aims to support process operators in their monitoring activities. The approach is tested with a scenario inspired by a real-world industrial challenge.","PeriodicalId":431393,"journal":{"name":"2006 IEEE Conference on Emerging Technologies and Factory Automation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Emerging Technologies and Factory Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2006.355408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
While automation systems can track thousands of measurements it is still up to human process operators to determine the operational situation of the controlled process, particularly in abnormal situations. To fully exploit the computing power of embedded processors and to release humans from simple data harvesting activities, the concept of proactive computing tries to exploit the strengths of both man and machine. Proactive features can be implemented using intelligent agent technology, enabling humans to move from simple interaction with computers into supervisory tasks. Autonomous information agents can handle massive amounts of heterogeneous data. They perform tedious tasks of information retrieving, combining and monitoring on the behalf of their users. This paper presents a multi-agent-based architecture for process automation, which aims to support process operators in their monitoring activities. The approach is tested with a scenario inspired by a real-world industrial challenge.