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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 Tekniska Högskola.
Blekinge Tekniska Högskola.
2019 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
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.

sted, utgiver, år, opplag, sider
2019. , s. 64
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-18418OAI: oai:DiVA.org:bth-18418DiVA, id: diva2:1335109
Fag / kurs
ET2580 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Telecommunication Systems
Utdanningsprogram
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 (engelsk)
Veileder
Examiner
Tilgjengelig fra: 2019-07-08 Laget: 2019-07-03 Sist oppdatert: 2025-09-30bibliografisk kontrollert

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