License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.Fog-IoT.2020.4
URN: urn:nbn:de:0030-drops-119985
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Harjuhahto, Jaakko ; Debner, Anton ; Hirvisalo, Vesa

Processing LiDAR Data from a Virtual Logistics Space

OASIcs-Fog-IoT-2020-4.pdf (5 MB)


We study computing solutions that can be used close to the network edge in I2oT systems (Industrial Internet of Things). As a specific use case, we consider a factory warehouse with AGVs (Automated Guided Vehicles). The computing services for such systems should be dependable, yield high performance, and have low latency. For understanding such systems, we have constructed a hybrid system that consists of a simulator yielding virtual LiDAR sensor data streams in real-time and a sensor data processor on a real cluster that acts as a fog computing node close to the warehouse. The processing merges the observations done from the individual sensor streams without using the vehicle-to-vehicle communication links for the complicated computing. We present our experimental results, which show the feasibility of the computing solution.

BibTeX - Entry

  author =	{Jaakko Harjuhahto and Anton Debner and Vesa Hirvisalo},
  title =	{{Processing LiDAR Data from a Virtual Logistics Space}},
  booktitle =	{2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
  pages =	{4:1--4:12},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-144-3},
  ISSN =	{2190-6807},
  year =	{2020},
  volume =	{80},
  editor =	{Anton Cervin and Yang Yang},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-119985},
  doi =		{10.4230/OASIcs.Fog-IoT.2020.4},
  annote =	{Keywords: simulation, hybrid systems, new control applications, fog computing}

Keywords: simulation, hybrid systems, new control applications, fog computing
Collection: 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)
Issue Date: 2020
Date of publication: 08.04.2020

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