Industrial IoT
Get the full GTU study material, English & Gujarati textbook PDFs, syllabus curriculum, and solved previous year question papers.
English Book & Chapters
English Book Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesGTU Previous Year Papers
Papers Coming Soon
We are working hard to add this material. Stay tuned for updates!
Follow on Instagram for UpdatesIndustrial IoT Syllabus — Unit-wise Content
The official GTU curriculum for Industrial IoT (subject code ME02062091) as prescribed for IOT · Semester 2 divides the course into 6 units, covering 33 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME02062091)Unit 1 Introduction to Internet of Things: IoT Architecture,
- Application-based IoT Protocols
- Business Models of IoT, IoT reference architecture
- Emerging IoT Technologies
Unit 2 Industry 4.0:Cyber Physical Systems and Next
- Generation Sensors
- Collaborative Platform and Product Lifecycle Management
- Augmented Reality and Virtual Reality
- Artificial Intelligence
- Big Data and Advanced Analysis
- Cybersecurity in Industry 4.0
- Basics of Industrial IoT
Unit 3 Introduction to IIoT: Prerequisites of IIoT, Basics of
- CPS, CPS and IIoT
- Modeling for CPS and CMS, Design requirements of Industry 4.0
- Drivers of Industry 4.0
- Industrial internet and sensing
- Industrial processing
Unit 4 Architecture of IIoT: Architecture of IIoT, IIRA
- Categorization of IIRA frameworks
- Business models of IIoT
- Cloud Computing
- Fog Computing
- Augmented Reality
- Virtual Reality
- Big Data and Advanced Analytics
- Lean manufacturing systems
Unit 5 Industrial Data Transmission:Sensors and Actuators,
- Foundation Fieldbus
- Controller Area Network
- LoRa and LoRaWAN
- Recent and Upcoming Technologies
- Industrial Data Acquisition
Unit 6 Machine Learning and Data Science in Industries
- Machine Learning
- Categorization of ML, Applications of ML in Industries
- Data Science in Industries
- Deep Learning
- Application of Deep Learning in Industries
Study on Android App:
