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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2011 Vol.1(2): 205-212 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2011.V1.30

Sensor Networks and Multi-Agents in Industrial Workflows

Emmanuel Sardis, Anastasios Doulamis and Nikolaos Matsatsinis
Abstract—Production lines need fast technologies for critical online decisions. Orchestration of different signals and processes from a number of different sensors around the industry, into related workflows are the key signals on workflows tasks recognition. The advantages of sensor networks’ technologies outputs, that their outputs are controlled by multi agents systems, in order to orchestrate and execute related production workflows, is the main point of this research work. In specific, the aim of this manuscript is to present a system that manipulates and controls these workflows executions. System architecture and sub modules are presented in more detail through the manuscript, plus a production scenario implementation.

Index Terms—Distributed architecture, Multi agents, Sensor networks, Production environments, Workflows.

Emmanuel Sardis is with the Distributed, Knowledge and Media Systems Laboratory of the National Technical University of Athens-and Adjunct to the Technical University of Crete, 9, Heroon Polytechniou street, 15773 Zografou, Athens, Greece (email: sardism@mail.ntua.gr) Anastasios Doulamis is with Technical University of Crete, Kounoupidiana, Chania, Crete, 73100, Greece (email: adoulam@ergasya,tuc.gr) Nikolaos Matsatsinis is with Technical University of Crete, Kounoupidiana, Chania, Crete, 73100, Greece (email: nikos@ergsy.tuc.gr)

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Cite: Emmanuel Sardis, Anastasios Doulamis and Nikolaos Matsatsinis, "Sensor Networks and Multi-Agents in Industrial Workflows," International Journal of Machine Learning and Computing vol. 1, no. 2, pp. 205-212, 2011.

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