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Course Outline
Module 1: Introduction, Basics, and Case Studies from Power Utility Companies
- Fundamentals of all technology stacks in Industrial IoT (IIoT)
- IoT adoption rate in the Power Utility Market and how companies are aligning their future business models and operations around IoT
- Broad Scale Application Areas
- Smart Meters, Smart Cars, Smart Grid: Brief definitions, adoption trends, and challenges
- Business Rule Generation for IoT
- 3-Layered Architecture of Big Data: Physical (Sensors), Communication, and Data Intelligence
- Evolving Standards and Platform Players like Azure, AWS, and Google: Brief introductions, offerings, and limitations
Module 2: Sensors, Hardware, and Sensor Networks
- Basic Function and Architecture of a Sensor: Sensor body, mechanism, calibration, maintenance, cost/pricing structures, and legacy vs. modern sensor networks
- Development of Sensor Electronics: IoT vs. Legacy, and Open Source vs. Traditional PCB design styles
- Development of Sensor Communication Protocols: From legacy protocols (Modbus, Relay, HART) to modern ones (Zigbee, Z-Wave, X10, Bluetooth, ANT, 6LoPAN, WiFi-x, NB-IoT, SignalFx, LoRa)
- Powering Options for Sensors: Battery, Solar, Mobile, and PoE
- Energy Harvesting Solutions for Wearables
- SoC (Sensors on Chips) and MEMS-based Sensors
- Sampling Rate Matching with Application: Why it matters in business
- What is a Sensor Network? What is an Ad-hoc Network?
- Wireless vs. Wireline Networks
- Autopairing and Reconnection
- Which applications to use and where
- Mathematical exercises to determine which network to select and where
Module 3: Key Security and Risk Concerns in IoT
- Firmware Patching Risk: The 'soft belly' of IoT
- Detailed Review of IoT Communication Protocol Security: Transport Layers (NB-IoT, 4G, 5G, LoRa, Zigbee, etc.) and Application Layers (MQTT, WebSocket, etc.)
- Vulnerability of API Endpoints: List of all possible APIs in IoT architecture
- Vulnerability of Gateway Devices and Services
- Vulnerability of Connected Sensors: Gateway Communication
- Vulnerability of Gateway-Server Communication
- Vulnerability of Cloud Database Services in IoT
- Vulnerability of Application Layers
- Vulnerability of Gateway Management Services: Local and Cloud-based
- Risk of Log Management in Edge and Non-Edge Architecture
Module 4: Machine Learning, AI, and Analytics for Intelligent IoT
- Return on Investment (ROI) for Intelligent IoT
- In Utility: Power Quality, Energy Management, and Other Analytics as a Service (AAS)
- Introduction to Analytic Stacks in IoT: Feature Extraction, Signal Processing, Machine Learning
- Introduction to Digital Signal Processing
- Fundamentals of Analytic Stacks in IoT Applications
- Learning Classification Techniques
- Bayesian Prediction: Preparing Training Files
- Support Vector Machine
- Image and Video Analytics for IoT
- Fraud and Alert Analytics through IoT
- Real-Time Analytics / Stream Analytics
- Scalability Issues of IoT and Machine Learning
- Fog Computing
- Edge Architecture
Module 5: Smart Metering - Standards, Security, and Future
- Smart Metering
- Open Smart Grid Protocols (OSGP)
- ANSI C2.18 Protocols
- NIST Standard for HAN (Home Area Network)
- HomePlug Powerline Alliance
- Smart Meter Security Standard (IEC 62056)
- Security Vulnerabilities of Smart Metering: Case Studies
Module 6: Cloud Platforms for IoT / IaaS / PaaS / SaaS for IoT
- IaaS: Infrastructure as a Service - Evolving Models
- Mechanism of Security Breaches in the IoT Layer for IaaS
- Middleware for IaaS Business Implementation in Healthcare, Home Automation, and Farming
- IaaS Case Study: Vehicular Information for Auto-Insurance and Agriculture
- PaaS: Platform as a Service in IoT. Case Studies of IoT Middleware
- SaaS: Software/System as a Service for IoT Business Models
- Updates and Patches via Web-OTA Mechanism
- Microsoft IoT Central as an Example of a PaaS Platform
- Google IoT and AWS IoT PaaS Platforms
Module 7: Future of Smart Grid and Smart Metering
- EV Charging as a Service
- EV as a Mobile Battery and Charger Wallet
- Large Battery Storage: Hydrogen Batteries, Lithium Batteries, and Other Initiatives
- Charging and Storage as a Service
- Grid as a Service for P2P Energy Trading
- Use of Distributed Ledger Technology in P2P Energy Trading: Blockchain, HyperLedger, and DAG
- IOTA/Tangle in P2P Charging
- IOTA/Tangle in Smart Energy and Smart Contracts
Module 8: Common IoT Systems for Utility Monetization
- Home Automation
- Smart Parking
- Energy Optimization
- Automotive: OBD / IaaS / PaaS for Insurance and Car Parking
- Mobile Parking Ticketing System
- Indoor Location Tracking
- Smart Lighting for Smart Cities
- Smart Waste Disposal System
- Smart Pollution Control in Cities
Module 9: Mobile IoT Modems, 4G, 5G, NB-IoT
- 4G IoT Standards for IoT: LTE-M applications, NB-IoT, UNB standard for 3GPP, 4G, LTE CAT-1 IoT
- 5G IoT Standards for IoT: LPWA, eMTC, IMT 2020 5G
- Detailed Architecture of IoT Mobile Modems
- Security Vulnerabilities of 4G/5G and Radio Networks
- IoT Gateways: Architecture, Classification, and Security Issues
Module 10: Managed IoT Service: IoT Management Layers
- Sensor Onboarding
- Sensor Mapping
- Digital Twin
- Asset Management
- Managing Third-Party Devices and Gateways
- Managing Sensor Connectivity and Gateway Connectivity
- Managing Device and Gateway Health
- Managing Sensor Calibration and QC
- Managing OTA/Patching at Scale
- Managing Firmware, Middleware, and Analytic Builds in Distributed Systems
- Security and Risk Management
- API Management
- Log Management
Module 11: Managing Critical Assets
- Review of Existing Fiber Optical Networks, SCADA, and PLC for Power Plants, Substations, and Critical Transformers
- SHM (Structural Health Monitoring) of Dam Systems: ICOLD Standard for Dam Monitoring
- Upgrading from SCADA to Local Cloud-Based Systems (Not Public Cloud)
- Transitioning from SCADA/PLC to Intelligent Local Cloud for More Efficient Management of Critical Assets
- Strategy for New Policies Adopting Smart Devices
Requirements
- Basic knowledge of business operations, devices, electronics systems, and data systems
- Basic understanding of software and systems
Basic understanding of Statistics (at an Excel level)
Target Audience
- Decision-makers, Strategists, Policy-makers
- Engineering Leaders, Lead Developers, Security Experts
Module Breakdown (Each module is 2 hours; customers can request any number of modules): Total 22 hours, 3 days
22 Hours
Testimonials (1)
The ability of the trainer to align the course with the requirements of the organization other than just providing the course for the sake of delivering it.
