Industrial Internet of Things Course

Lesson 1 • What Is Industrial IoT

Defines IIoT, its scope, and its role in modern industry. Grounds subsequent technical content in real operational contexts.

Lesson 2 • IIoT Ecosystem and Stakeholders

Maps vendors, integrators, standards bodies, and end users in the IIoT value chain. Prepares learners to navigate real-world project environments.

Lesson 3 • Industrial Sensors and Actuators

Covers sensor types, signal conditioning, and actuator roles in IIoT systems. Links physical measurement to digital data pipelines.

Lesson 4 • Connectivity Fundamentals

Surveys wired and wireless communication options used in industrial environments. Sets the stage for protocol-level study in later chapters.

Lesson 1 • MQTT and AMQP for IIoT

Introduces lightweight messaging protocols suited for constrained and cloud-connected devices. Bridges field-level data to cloud analytics platforms.

Lesson 2 • Wireless Industrial Protocols

Covers WirelessHART, ISA100.11a, and LoRaWAN for industrial wireless deployments. Addresses reliability and coexistence challenges in plant environments.

Lesson 3 • Legacy Fieldbus Protocols

Examines Modbus, PROFIBUS, and HART as foundational industrial communication standards. Explains why legacy protocols persist in modern IIoT integrations.

Lesson 4 • OPC UA for IIoT Integration

Teaches OPC UA information modeling, security, and transport mechanisms. Positions OPC UA as the primary interoperability layer in IIoT architectures.

Lesson 1 • Data Preprocessing at the Edge

Teaches filtering, aggregation, and anomaly flagging performed locally before cloud transmission. Reduces unnecessary data volume and improves upstream analytics quality.

Lesson 2 • Edge Software and Runtimes

Covers containerization, edge middleware, and real-time operating systems for industrial edge nodes. Connects software choices to deployment reliability and update management.

Lesson 3 • Edge Orchestration and Management

Introduces remote management, monitoring, and orchestration of distributed edge nodes. Prepares learners to operate large-scale edge deployments reliably.

Lesson 4 • Industrial Edge Hardware Platforms

Surveys PLCs, industrial PCs, and purpose-built edge gateways as compute platforms. Guides hardware selection based on environmental and performance constraints.

Lesson 1 • Data Quality and Governance

Addresses data validation, cleansing, lineage tracking, and access control for industrial datasets. Ensures data trustworthiness for analytics and compliance purposes.

Lesson 2 • IT and OT System Integration

Covers integration patterns between operational technology and enterprise IT systems such as ERP and MES. Addresses data consistency and synchronization challenges.

Lesson 3 • Data Contextualization and Modeling

Teaches asset modeling, semantic tagging, and data contextualization to make raw sensor data meaningful. Links contextualized data to enterprise decision-making.

Lesson 4 • Time-Series Databases for IIoT

Introduces time-series database concepts, schema design, and query patterns for industrial data. Connects storage choices to downstream analytics and historian integration.

Lesson 1 • Scalability and High Availability

Covers horizontal scaling, load balancing, and redundancy patterns for IIoT platforms handling millions of data points. Addresses failover and disaster recovery design.

Lesson 2 • Interoperability and Open Standards

Addresses API design, open standards adoption, and vendor-neutral integration to avoid lock-in. Ensures platform longevity and ecosystem flexibility.

Lesson 3 • IIoT Platform Components

Identifies device management, data ingestion, analytics, and application enablement as core platform layers. Provides a component map used in architecture design exercises.

Lesson 4 • Cloud and Hybrid Deployment Models

Compares public cloud, private cloud, and hybrid deployment options for IIoT workloads. Guides deployment decisions based on data sovereignty and latency needs.

Lesson 1 • IIoT Security Frameworks

Introduces industrial cybersecurity frameworks and standards for risk management and control selection. Provides a structured approach to security program development.

Lesson 2 • Device Identity and Access Control

Teaches certificate-based device identity, PKI management, and role-based access control for IIoT. Prevents unauthorized device enrollment and privilege escalation.

Lesson 3 • Monitoring, Detection, and Response

Covers OT-aware intrusion detection, security information management, and incident response playbooks. Closes the security loop from detection to recovery.

Lesson 4 • IIoT Threat Landscape

Surveys attack vectors, threat actors, and historical incidents specific to industrial environments. Motivates security investment by connecting threats to operational consequences.

Lesson 1 • Feature Engineering for Sensor Data

Covers time-domain, frequency-domain, and statistical feature extraction from raw sensor streams. Prepares high-quality inputs for machine learning model training.

Lesson 2 • Predictive Maintenance Models

Teaches anomaly detection, remaining useful life estimation, and fault classification for equipment health. Connects model outputs to maintenance scheduling workflows.

Lesson 3 • Industrial Analytics Fundamentals

Introduces descriptive, diagnostic, predictive, and prescriptive analytics tiers in industrial contexts. Frames analytics maturity as a progression tied to business value.

Lesson 4 • Quality and Process Optimization

Applies regression and optimization techniques to improve product quality and process efficiency. Links model recommendations to production control systems.

Lesson 1 • Continuous Improvement in IIoT Operations

Applies iterative improvement methodologies to IIoT systems using operational data and feedback loops. Sustains long-term value delivery beyond initial deployment.

Lesson 2 • Device Provisioning and Commissioning

Teaches zero-touch provisioning, device enrollment, and field commissioning procedures for IIoT deployments. Ensures devices are securely and correctly onboarded at scale.

Lesson 3 • Change Management and Configuration Control

Covers firmware update management, configuration versioning, and change approval processes in live OT environments. Minimizes operational risk during system modifications.

Lesson 4 • IIoT Project Planning

Covers scope definition, stakeholder alignment, risk planning, and phased rollout strategies for IIoT projects. Establishes project governance structures that reduce deployment failures.