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  4. Data-driven, sensor-based taxonomy for environmental life cycle assessment of pallets
 
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2024
Journal Article
Title

Data-driven, sensor-based taxonomy for environmental life cycle assessment of pallets

Abstract
Pallets are one of the most important load carriers for international supply chains. Yet, continuously tracking activities such as Driving, Lifting or Standing along their life cycle is hardly possible. This contribution is the first to propose a taxonomy for sensor-based activity recognition of pallets. Different types of acceleration sensors are deployed in three logistical scenarios for creating a benchmark dataset. A random forest classifier is deployed for supervised learning. The results demonstrate that automated, sensor-based life cycle assessment based on the proposed taxonomy is feasible. All data and corresponding videos are published in the SPARL dataset
Author(s)
Franke, Sven Robin
Fraunhofer-Institut für Materialfluss und Logistik IML  
Bommert, Andrea  
Technische Universität Dortmund
Brandt, Marc Julian
Fraunhofer-Institut für Materialfluss und Logistik IML  
Kuhlmann, Jean Lenard
Fraunhofer-Institut für Materialfluss und Logistik IML  
Olivier, Marie-Claire
TU Dortmund  
Schorning, Kirsten  
Technische Universität Dortmund
Reining, Christopher  
Fraunhofer-Institut für Materialfluss und Logistik IML  
Kirchheim, Alice
Fraunhofer-Institut für Materialfluss und Logistik IML  
Journal
Logistics Journal. Proceedings. Online journal  
Conference
Wissenschaftliche Gesellschaft für Technische Logistik (WGTL Fachkolloquium) 2024  
DOI
10.2195/lj_proc_franke_en_202410_01
Language
English
Fraunhofer-Institut für Materialfluss und Logistik IML  
Keyword(s)
  • logistics

  • warehousing

  • taxonomy

  • activity recognition

  • inertial measurement unit

  • life cycle

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