Using BPM technology to deploy and manage distributed analytics in collaborative IoT-driven business scenarios

Tim d'Hondt, Anna Wilbik, Paul Grefen, Heiko Ludwig, Nathalie Baracaldo, Ali Anwar

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
1 Downloads (Pure)


Increasing competition forces business organizations to improve the efficiency of their operational business processes, certainly where costly physical resources are involved. By integrating real-time, IoT-based information from these resources into business processes, advanced real-time decision making can be realized to enable the required efficiency increase. There are various challenges though. Firstly, the resources can be large in number, heterogeneous in nature and owned by different business parties. Secondly, the data is typically heterogeneous in format and large in volume. Thirdly, business scenarios are diverse and evolve over time. Consequently, converting IoT data into usable information to drive business processes is not a trivial task. To address this, we propose the use of a novel combination of existing technologies in distributed analytics (DA) and business process management (BPM). To deal with the size, heterogeneity and ownership of data, we don’t bring the data to the analytics, but bring the analytics in a distributed format to the data. We use parameterized micro-services that are packed into software containers to make them dynamically deployable from a service repository into the IoT edge. To deal with the number of IoT resources and the diversity of scenarios, we automate the
deployment and management processes of the containerized microservices
using a BPM engine. This engine interprets graphically specified process models that define the data flow between the DA modules and business decision making. Our approach leaves large amounts of raw data at its origin and is highly flexible in its data processing scheme. We show the feasibility of our approach in a proof-of-concept prototype implementation.
Original languageEnglish
Title of host publicationProceedings of the 9th International Conference on the Internet of Things, IoT 2019
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Number of pages8
ISBN (Electronic)978-1-4503-7207-7
Publication statusPublished - 22 Oct 2019
Event9th International Conference on the Internet of Things - Bilbao, Spain
Duration: 22 Oct 201925 Oct 2019

Publication series

NameACM International Conference Proceeding Series


Conference9th International Conference on the Internet of Things


  • Business process management
  • Machine learning
  • Distributed artificial intelligence
  • Internet of Things
  • Edge Computing
  • Distributed Analytics
  • Fog Computing
  • Federated Learning
  • BPM
  • IoT


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