This paper introduces a minimum viable softwareproduct to filter large datasets of engine data recorded duringlaboratory experiments of combustion engines. The aim is to supportanalysts in the identification and analysis of specific physicalphenomenon within hours of recorded engine experimental data.Specifically, the tool has been designed considering the use case ofidentifying Low Speed Pre-Ignition events. This work describesthe tool's graphical user interface and its scalable architecturebased on mainstream web and big-data technologies as wellas the practical application to pre-ignition events identification.The paper provides details on the architecture's performance,providing evidence of its scalability by increasing the number ofavailable computing workers.
|Title of host publication||IEEE-INDIN 2016 14th international conference on industrial informatics|
|Place of Publication||Poitiers, France|
|Number of pages||6|
|Publication status||Published - 18 Jul 2016|
|Event||IEEE-INDIN 2016 14th international conference on industrial informatics - University of Poitiers, France, 18-21 July 2016|
Duration: 18 Jul 2016 → …
|Conference||IEEE-INDIN 2016 14th international conference on industrial informatics|
|Period||18/07/16 → …|
Bibliographical note© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
FingerprintDive into the research topics of 'Filter Large-scale Engine Data using Apache Spark'. Together they form a unique fingerprint.