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Investigating and Deploying an AI model on Raspberry Pi IoT platform using FIWARE and Docker in the context of the Bonseyes AI Ecosystem
Blekinge Institute of Technology.
Blekinge Institute of Technology.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Many high-end sophisticated devices are being replaced by small single-board IoT devices. It is estimated that by the year 2025 there will be about 75 billion IoT connected devices worldwide. This project buttresses the earlier statements. The project will be focused on how to deploy a complex AI face-recognition model on a simple, less power consumption, single-board IoT device Raspberry Pi3. Also, to simplify the whole process of deploying the AI model on Raspberry Pi3 by dockerizing. By just pulling the respective docker image and running it on the end device (Raspberry Pi3), we can make face recognition happen. Finally, the obtained results will be sent to the cloud (Fiware) using NGSI API. Instead of sending the whole video feed to the Cloud platform and performing the computing there, we managed to perform the computing at the edge and then send the results to the cloud and making the results accessible to requested users.

Place, publisher, year, edition, pages
2019. , p. 64
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-18418OAI: oai:DiVA.org:bth-18418DiVA, id: diva2:1335109
Subject / course
ET2580 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Telecommunication Systems
Educational program
ETATE Master of Science Programme in Electrical Engineering with emphasis on Telecommunication Systems
Presentation
2019-06-04, Blekinge Institute of Technology, Blekinge, Karlskrona, 21:08 (English)
Supervisors
Examiners
Available from: 2019-07-08 Created: 2019-07-03 Last updated: 2019-08-06Bibliographically approved

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fulltext(1370 kB)18 downloads
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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf