Build a Modular Cloud Platform for Industrial IoT and Edge AI
How do you connect thousands of intelligent devices while keeping the cloud platform flexible, scalable, and secure?
Description
Modern industrial systems generate enormous amounts of sensor data. Turning that information into useful insights requires more than connecting devices to the cloud. It requires reliable data pipelines, modular software architecture, and efficient ways to manage AI models deployed at the edge.
At Knowit Connectivity, we are offering a thesis opportunity focused on designing and validating a modular cloud platform for industrial IoT and Edge AI applications.
About the Project
The goal is to create a reusable cloud architecture that can integrate different industrial devices, collect and process sensor data, and manage the lifecycle of AI models running on connected edge devices.
A central challenge is modularity. The platform should make it possible to introduce new device types, communication protocols, storage technologies, and services without redesigning the entire system.
You will investigate how to combine cloud architecture, industrial data engineering, device management, cybersecurity, and Edge AI deployment into a flexible solution.
The emphasis is on reusable architectural principles rather than a platform tied to one cloud provider.
What You Will Explore
Depending on the final scope, the project may include:
Designing a modular cloud architecture using clearly defined services and APIs.
Developing reusable integration components for industrial IoT devices.
Building data pipelines for sensor telemetry, events, and historical analysis.
Exploring device onboarding, configuration, and lifecycle management.
Implementing model registration, versioning, deployment coordination, and rollback for Edge AI applications.
Investigating cloud portability, scalability, and system reliability.
Implementing observability through logging, monitoring, and performance measurements.
Exploring authentication, authorization, secure communication, and cybersecurity requirements.
Performing a preliminary Cyber Resilience Act (CRA) applicability assessment and gap analysis.
Who We're Looking For
This project could be suitable if you are studying Computer Science, Software Engineering, Cloud Computing, Information Technology, or a related field.
We believe you have an interest in:
Cloud platforms and distributed systems.
Backend development and API design.
Software architecture and microservices.
Data engineering and streaming data.
Industrial IoT and connected devices.
DevOps, automation, and cybersecurity.
Machine learning deployment and MLOps concepts.
An interest in building maintainable and reusable systems is particularly relevant.
Expected Outcomes
The thesis aims to deliver a working reference platform demonstrating industrial device integration, sensor data processing, and Edge AI model lifecycle management.
You will evaluate the platform's modularity, portability, reliability, and operational performance.
The project also includes documenting relevant cybersecurity considerations and identifying potential improvements before future product development.
The final scope will be agreed upon together with your supervisors.
Interested in This Thesis?
Interested in cloud architecture, connected devices, and the infrastructure that enables industrial AI?
Apply through our thesis application page and indicate your interest in "Modular Cloud Platform for Industrial IoT".