Topic 14:
Azure AI / ML Integration for Real-time Manufacturing Intelligence Application


Smart IOT Highway (SIOTH®) is a scalable and modular IoT platform for data exchange and transformation purposes. Its main purpose is to securely transfer and monitor efficiently massive amounts of data from thousands of devices simultaneously. It establishes secure end-to-end pipelines to collect and orchestrate data from edge, IoT devices or any data source system and transfer data to any application, cloud and vice versa, as well as configure data flows to meet business applications requirements.
Cloud computing has been growing over the years as it gives potential to save investment costs in infrastructure, to save time in application development and deployment, and to save resource allocation overhead. It is a category of computing solutions in which a technology and/or service lets users access computing resources on demand, as needed, whether the resources are physical or virtual, dedicated, or shared, and no matter how they are accessed (via a direct connection, LAN, WAN, or the Internet). Users now benefits not only from storage and computational resources but also from different machine learning algorithms where the user can pull his data and apply training and prediction functionalities.
In this project, the intern will be asked to:

  • Perform a literature review to understand the Azure AI/ML architecture in terms of connecting to data source, creating/running models, using the different API to connect and interact with these models.
  • Propose and engineer the best technical solution to integrate Azure libraries into SIOTH.
  • Compare results with competitive products.

During this project, the intern will learn all about Industrial Internet of Things (IIoT), rule engines, Azure, AI/ML models, real- time performance management applications


At the end of the internship, the intern shall deliver a finalized solution that includes:

Design documents Source
Test tools
Documentation: user guide, project report, and test reports
Key Words:

Azure, Distributed Computing, Artificial Intelligence, Machine Learning, Communication Protocol, API, Real-time System

Interested in this end of studies project?

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