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Authors: Petri Kannisto 1 ; David Hästbacka 1 ; Lauri Palmroth 2 and Seppo Kuikka 1

Affiliations: 1 Tampere University of Technology, Finland ; 2 John Deere Forestry, Finland

ISBN: 978-989-758-027-7

Keyword(s): Distributed Knowledge Management, Rule based Reasoning, Operator Performance Assessment, Mobile Machines.

Related Ontology Subjects/Areas/Topics: Applications of Expert Systems ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Cloud Computing ; Collaboration and e-Services ; Data Engineering ; Databases and Information Systems Integration ; e-Business ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Mobile Databases ; Mobile Software and Services ; Ontologies and the Semantic Web ; Services Science ; Society, e-Business and e-Government ; Software Agents and Internet Computing ; Software Engineering ; Software Engineering Methods and Techniques ; Strategic Decision Support Systems ; Telecommunications ; Web Information Systems and Technologies ; Web Services ; Wireless Information Networks and Systems

Abstract: The performance of mobile machine operators has a great impact on productivity that can be translated to, for example, wasted time or environmental concerns such as fuel consumption. In this paper, solutions for improving the assessment of mobile machine are studied. Usage data is gathered from machines and utilized to provide feedback for operators. The feedback is generated with rules that define in what way different measures indicate performance. The study contributes to developing an architecture to manage both data collection and inference rules. A prototype is created: rule knowledge is managed with decision tables from which machine-readable rules are generated. The rules are then distributed to application instances executed in various locations. The results of the prototype promote several benefits. Rules can be maintained independent of the actual assessment application, and they can also be distributed from a centrally managed source. In addition, no IT expertise is requir ed for rule maintenance so the rule administrator can be a pure domain expert. The results bring the architecture towards a scalable cloud service that combines the benefits of both centralized knowledge and distributed data management. (More)

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Paper citation in several formats:
Kannisto, P.; Hästbacka, D.; Palmroth, L. and Kuikka, S. (2014). Distributed Knowledge Management Architecture and Rule Based Reasoning for Mobile Machine Operator Performance Assessment.In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-027-7, pages 440-449. DOI: 10.5220/0004870004400449

@conference{iceis14,
author={Petri Kannisto. and David Hästbacka. and Lauri Palmroth. and Seppo Kuikka.},
title={Distributed Knowledge Management Architecture and Rule Based Reasoning for Mobile Machine Operator Performance Assessment},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2014},
pages={440-449},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004870004400449},
isbn={978-989-758-027-7},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Distributed Knowledge Management Architecture and Rule Based Reasoning for Mobile Machine Operator Performance Assessment
SN - 978-989-758-027-7
AU - Kannisto, P.
AU - Hästbacka, D.
AU - Palmroth, L.
AU - Kuikka, S.
PY - 2014
SP - 440
EP - 449
DO - 10.5220/0004870004400449

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