Industrial Internet of Things (IIoT)
This course lays a solid methodological foundation for advanced studies in Industrial Internet of Things (IIoT) architecture, industrial platforms, cybersecurity, and distributed systems. It acts as a crucial integration module between programming and systems architecture, while also serving as an introduction to systems engineering within the master’s programme.
Dive into the fascinating world of distributed cyber‑physical systems with our comprehensive course! You’ll follow the entire journey of engineering solution development — from identifying needs and formalising requirements to building a prototype, conducting tests, and assessing the Technology Readiness Level (TRL).
You won’t just gain theoretical knowledge — you’ll develop a true culture of navigating the life cycle of engineering solutions. You’ll learn to prepare design documentation with confidence, understand the logic of the technological maturity spiral, and build a strong foundation in distributed cyber‑physical systems, IIoT architecture, and industrial digital platforms.
Throughout the course, you’ll cultivate systems engineering thinking: you’ll master the logic of the IIoT product life cycle, learn to formalise requirements and design documentation, and grasp the fundamental principles of digital control, management, and data transmission. You’ll also foster a culture of engineering maturity and TRL assessment. A special focus is placed on working with large language models (LLMs) — you’ll learn to leverage them as powerful tools to support every stage of the development life cycle.
In hands‑on projects, you’ll build a cyber‑physical system prototype using Arduino and Python, implement basic data transfer between devices, and integrate a local node into a distributed model. By the end of the course, you’ll have a clear understanding of the cyber‑physical system life cycle stages, be able to justify technical solution choices, and critically analyse results — including through the use of LLMs. You’ll gain practical skills in microcontroller programming, design documentation preparation, and engineering argumentation, setting a strong foundation for your professional growth.
LLMs are integrated throughout the course as practical engineering assistants — helping students at every stage: from initial reflection and requirements analysis to coding, testing, documentation, and final reporting. This approach builds a culture of using AI tools to support the full lifecycle of cyber‑physical system development.
OBJECTIVES
Developing systems engineering thinking in the field of cyber‑physical systems;
Mastering the logic of the IIoT product life cycle;
Developing skills in formalizing requirements and design documentation;
Mastering the basic principles of digital control, management, and data transmission;
Fostering a culture of engineering maturity and TRL assessment;
Mastering a conscious model of interaction with LLM as a tool for supporting the development life cycle.
KEY TASKS
Identifying needs and creating a stakeholder map;
Forming functional and non‑functional requirements;
Developing a conceptual project;
Preparing technical specifications;
Designing the testing program and methodology;
Developing a prototype of a cyber‑physical system on a training base (Arduino + Python);
Implementing basic data transfer between devices;
Integrating a local node into a distributed model;
Assessing the level of technological readiness;
Developing skills in using LLM for planning, documentation, and engineering reflection.
Main topics of the course:
Module 1. Lifecycle of IIoT Cyber‑Physical Systems
1. Introduction to IIoT and cyber‑physical systems: key differences between IoT and IIoT, system class examples, product lifecycle overview, and fundamentals of Technology Readiness Level (TRL).
2. Needs analysis and stakeholder mapping: methods for identifying problems and formulating problem statements, using large language models (LLMs) as customer and operator emulators.
3. Requirements engineering: forming functional and non‑functional requirements, defining acceptance criteria, and leveraging LLMs to structure requirements and detect inconsistencies.
4. Technical solution development: generating and selecting solutions, comparing alternatives, conceptual design, and using LLMs for comparative analysis.
5. Documentation in engineering: structure of technical specifications and technical design, preparing design documentation, and applying LLMs to verify logical integrity.
6. Testing and maturity assessment: designing test programs and methodologies, creating protocols and checklists, preparing user documentation, understanding the TRL spiral, and using LLMs to formalize testing and assess maturity.
Module 2. On‑Premise Cyber‑Physical Solutions
1. Microcontroller systems: architecture overview, working with sensors and signals.
2. Actuators and control logic: understanding actuators, implementing the measure‑decision‑act cycle.
3. Control algorithms: designing threshold circuits and state logic for system control.
4. Data processing and visualization: transferring data to a PC and processing/visualizing it in Python.
5. System reliability and security: handling errors, designing security algorithms to ensure robust operation.
6. Practical implementation: developing a mini‑project of a local cyber‑physical system, conducting tests, generating reports, and using LLMs to create checklists and documentation.
Module 3. Communication and Distributed IIoT Solutions
1. Networking fundamentals: basics of network interaction, Local Area Networks (LAN), and the client‑server model.
2. Wireless and internet‑based data transfer: implementing Wi‑Fi communication and data exchange via the Internet.
3. Remote data management: transferring data to remote databases, setting up notifications and incident reporting (via Telegram or email).
4. System integration and prototyping: integrating local nodes into a distributed system, demonstrating a distributed prototype, preparing user manuals, and defining pilot operation procedures — with LLMs assisting in designing interaction scenarios and operating procedures.
