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Event-driven Architecture for Sensor Data Integration for Logistics Services

: Leveling, Jens; Weickhmann, Luise; Nissen, Christian; Kirsch, Christopher


Institute of Electrical and Electronics Engineers -IEEE-:
IEEE International Conference on Industrial Engineering & Engineering Management, IEEM 2018 : 16-19 December 2018, Bangkok, Thailand
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-6786-6
ISBN: 978-1-5386-6785-9
ISBN: 978-1-5386-6787-3
International Conference on Industrial Engineering and Engineering Management (IEEM) <2018, Bangkok>
Fraunhofer IML ()
Internet of Things; sensor device; sensor data; data integration; data fusion

Sensor data offers a massive potential for the logistics sector. To achieve an optimal, effective and productive supply chain, operators and manufacturers are challenged to use this information and extract value from it. They have to comply with the main task of efficiently managing logistics processes as well as fulfilling requirements and guidelines. To do so, it is necessary to monitor all processes and understand exceptions and anomalies. Sensor and Internet of Things (IoT) data is the key for these tasks. Currently, the data is available but not (sufficiently) used. The heterogeneity of sensor data is a major obstacle for the usage. Therefore, we present an architecture, which addresses these challenges by integrating heterogenic data in well-formed data sets.