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UAV-CPSs as a test bed for new technologies and a primer to Industry 5.0

UAV-CPSs as a test bed for new technologies and a primer to Industry 5.0

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The extensive Cloud pool of resources and infrastructure can deliver significant improvements to Unmanned Aerial Vehicle (UAV) Cyber-Physical Systems (UAV-CPSs) relying on data or code from a network to operate, but not all sensors, actuators, computation modules and memory depots from a single fixed structure. This chapter is organised around the potential benefits of the Cloud: (1) Big Data (BD) access to visual libraries containing representations/descriptive data, images, video, maps and flight paths, (2) Cloud Computing (CC) functionalities for Grid Computing (GC) on demand for statistical analysis, Machine Learning (ML) algorithms, Computational Intelligence (CI) applications and flight planning, (3) Collective UAV Learning (CUL) where UAVs share their trajectories, control guidelines and mission outcomes and (4) human-machine collaboration through crowdsourcing for analysing high-dimensional high-resolution (HDHR) images/ video, classification of scenes/objects/entities, learning and error correction/ concealment. The Cloud can also expand UAV-CPSs by offering (a) data sets, models, all sorts of literature, HDHR benchmarks and software/hardware simulators, (b) open competitions for UAV-CPS designs with Open Source Hardware (OSH) and (c) Open-Source Software (OSS). This chapter talks about some open challenges and new trends in UAV-CPSs.

Chapter Contents:

  • 1.1 Introduction
  • 1.2 Cloud computing
  • 1.3 Collective UAV learning
  • 1.4 Human computation, crowdsourcing and call centres
  • 1.5 Open-source and open-access resources
  • 1.6 Challenges and future directions
  • 1.7 Conclusions
  • References

Inspec keywords: public domain software; cyber-physical systems; statistical analysis; crowdsourcing; learning (artificial intelligence); cloud computing; industrial robots; autonomous aerial vehicles; grid computing; path planning; Big Data

Other keywords: high-dimensional high-resolution video analysis; UAV-CPSs; object classification; machine learning algorithms; HDHR image analysis; sensors; collective UAV learning; actuators; CUL; computational intelligence; flight paths; open-source software; entities classification; UAV-CPS designs; Big Data; single fixed structure; descriptive data; high-dimensional high-resolution image analysis; human-machine collaboration; cloud computing; visual libraries; crowdsourcing; Unmanned Aerial Vehicle Cyber-Physical Systems; open source hardware; extensive cloud pool; scene classification; error concealment; statistical analysis; software-hardware simulators; Industry 5.0; ML algorithms; Grid Computing; computation modules; flight planning; error correction

Subjects: Internet software; Other topics in statistics; Knowledge engineering techniques; Mobile robots; Data handling techniques; Spatial variables control; Grid computing; Aerospace control; Telerobotics

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