Udemy - IIoT and Industry 4.0 - MQTT, UNS and Digital Twin

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Udemy - IIoT and Industry 4.0 - MQTT, UNS and Digital Twin (Size: 3.3 GB)
  Get Bonus Downloads Here.url 204.8 B
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  1. Industry 4.0 & IIoT — What It Actually Means for Automation Engineers.mp4 277.2 MB
  10. Implementing IIoT in an Industrial Plant — The Practical Roadmap.mp4 259.1 MB
  11. Smart Plant Case Studies — Real Implementations.mp4 232.1 MB
  12. Exam Preparation — ISA CAP Advanced Automation Topics.mp4 176.4 MB
  2. IIoT Architecture — Edge, Fog & Cloud.mp4 288.1 MB
  3. IIoT Protocols — MQTT, Sparkplug B & OPC UA Pub-Sub.mp4 282.6 MB
  4. The Unified Namespace — Connecting OT to the Enterprise.mp4 302.3 MB
  5. Digital Twin Technology for Industrial Plants.mp4 319.4 MB
  6. Advanced Process Control & Model Predictive Control.mp4 346.2 MB
  7. Predictive Maintenance & Condition Monitoring.mp4 325.3 MB
  8. Cloud Platform Selection & Cost Modelling for Industrial IIoT.mp4 321.5 MB
  9. Data Quality & Governance for IIoT.mp4 239.6 MB
  Bonus Resources.txt 102.4 B

Description


IIoT & Industry 4.0: MQTT, UNS & Digital Twin
https://WebToolTip.com
Published 6/2026

Created by ProjectEngPro Engineering and Project Management

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Level: Beginner | Genre: eLearning | Language: English | Duration: 12 Lectures ( 2h 25m ) | Size: 3.3 GB
MQTT Sparkplug B & Unified Namespace | edge computing | digital twin & MPC | predictive maintenance
What you'll learn

⚡ Separate the substance of IIoT and Industry 4.0 from the marketing for a process plant

⚡ Design IIoT architecture across the sensor, edge and cloud layers

⚡ Decide what to compute at the edge based on latency, bandwidth and resilience

⚡ Implement MQTT with Sparkplug B for report-by-exception industrial messaging

⚡ Build a Unified Namespace as a single, structured, real-time source of plant state

⚡ Select cloud platforms and analytics for industrial data

⚡ Apply digital twins to simulation, monitoring and optimisation

⚡ Apply advanced process control and model predictive control to a process

⚡ Implement predictive maintenance from condition and process data

⚡ Govern industrial data — quality, ownership and security — across the architecture

⚡ Choose what to connect and what to leave alone to keep a programme delivering value

⚡ Produce a smart-plant IIoT architecture as a section project
Requirements

❗ A background in C&I, control, automation or electrical engineering is assumed

❗ Familiarity with DCS, PLC or SCADA systems and basic networking

❗ This is a practitioner-level course, not a first introduction to automation

❗ No specific IIoT platform or licence is required to follow the material

❗ A willingness to think about data architecture, not just devices

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