Short description
According to IDC, $204 billion will be spent globally by businesses in 2025 on hardware, software, and services related to artificial intelligence. However, as AI becomes more prevalent in sectors, businesses of all sizes are discovering that a centralized cloud computing model does not perform well when large amounts of data must be stored and transmitted, when applications must be responsive to latency, or when assets must have limited connectivity. Real-time tiny data processing at the edge is implemented using intelligent edge, which blends edge computing with AI. One of the significant aspects of the Internet of Things (IoT) is to provide data sharing to connect organizations, customers, suppliers, or other stakeholders, bringing greater added value to different stakeholders in the IoT's ecosystems, especially with AI/ML applications on Edge.
Master Project
This is a long thesis.
Research Topic focus
This MSc thesis aims at developing an approach for enabling access control of AI/ML applications on Edge to data sources and how the ML/AI-processed data can be shared with different stakeholders as a service.
Expected Results and Learning Outcome
A sound approach, a good prototype, documentation of experiments.
Qualifications:
Good knowledge in Software Engineering, good programming skills.