Telematics and Big Data Analytics – An Effective Way to Quantify Fuel Saving Potentials
- Publikations-Art
- Kongressbeitrag
- Autoren
- Köber-Fleck, B.; Ahlbrand, P.; Böttinger, S.;Korte, H.;
- Erscheinungsjahr
- 2017
- Veröffentlicht in
- VDI-Berichte
- Herausgeber
- VDI-MEG
- Verlag
- VDI Verlag , Düsseldorf
- Band/Volume
- 2300/
- ISBN / ISSN / eISSN
- 978-3-18-092300-0
- Seite (von - bis)
- 227-236
- Tagungsname
- Tagung Landtechnik
- Tagungsort
- Hannover
- Tagungsdatum
- 10./11.11.2017
- Schlagworte
- Big Data, Kraftstoffverbrauch, Simulation, Traktor
In the 21st century, humanity face two important topics that concern future developments:
Climate change and Big Data. On the one hand, climate change is a global challenge that
can only be handled successfully with well-designed systematic and cross-industry mitigation
strategies. On the other hand, Big Data offers tools, which enable us to identify potentials for
efficiency gains in process chains.
This paper describes a Proof of Concept to use telematics data from agricultural machinery
to detect fuel saving potentials. The work was carried out in the joint research project
EKoTech ’Efficient fuel use in agricultural technology’. It aims to evaluate saving potentials in
selected agricultural process chains in the period from 1990 to 2030. It is a cross-industry
approach working with project partners of competitive manufacturers, agricultural operators,
and research institutes. Consequently, a high variety of data sources have to be analysed
and merged. Furthermore, the concept has to pay attention to data privacy rights and
confidentiality of industry data.
With the Proof of Concept, the team wants to find out if the ‘Cross-Industry Standard Process
for Data Mining 1.0’ (CRISP-DM 1.0) methodology is according with the requirements of the
project as a guideline for data analytics.