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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).
- The IoT adaptation 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, and Smart Grids: brief definitions, adoption trends, and challenges.
- Business rule generation for IoT.
- The 3-layered architecture of Big Data: Physical (Sensors), Communication, and Data Intelligence.
- Evolving standards and platform players like Azure, AWS, and Google: brief introductions, what they offer, and what they lack.
Module 2: Sensors, Hardware and Sensor Networks
- Basic function and architecture of a sensor: sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, and legacy vs. modern sensor networks. All fundamentals regarding sensors.
- Development of sensor electronics: IoT vs. legacy approaches, and open-source vs. traditional PCB design styles.
- Development of sensor communication protocols: from history to modern days. Legacy protocols like Modbus, relay, and HART to modern protocols like Zigbee, Z-Wave, X10, Bluetooth, ANT, 6LoPAN, WiFi, NB-IoT, SignalFx, and LoRa.
- Powering options for sensors: Battery, solar, mobile, and PoE (Power over Ethernet).
- Energy harvesting solutions for wearables.
- SoC (Sensors on Chips) and MEMS-based sensors.
- Matching sampling rate with application: why it matters for business.
- What is a sensor network? What is an ad-hoc network?
- Wireless vs. wireline networks.
- Autopairing and reconnection mechanisms.
- 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 risks: 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, Web Socket, etc.).
- Vulnerability of API endpoints: a list of all possible APIs in IoT architecture.
- Vulnerability of gateway devices and services.
- Vulnerability of connected sensors and gateway communication.
- Vulnerability of gateway-to-server communication.
- Vulnerability of cloud database services in IoT.
- Vulnerability of application layers.
- Vulnerability of gateway management services: both local and cloud-based.
- Risk of log management in edge and non-edge architectures.
Module 4: Machine learning, AI, Analytics for intelligent IoT
- What is the return on investment for Intelligent IoT?
- Applications in Utility: Power Quality, Energy management, and other Analytic as a Service (AAS) solutions.
- Introduction to Analytic Stacks in IoT: Feature extraction, Signal Processing, and Machine learning.
- Introduction to digital signal processing.
- Fundamentals of analytics 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 and 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 C 2.18 Protocols.
- NIST Standard for HAN (Home Area Network).
- Home Plug Powerline Alliance.
- Security Standard for Smart Meters: IEC 62056.
- Security vulnerability of smart metering: case studies.
Module 6: Cloud Platform for IoT/IaaS/PaaS/SaaS for IoT
- IaaS: Infrastructure as a Service - evolving models.
- Mechanisms of security breaches in the IoT layer for IaaS.
- Middleware for IaaS business implementation in healthcare, home automation, and farming.
- IaaS case study for vehicular information for auto-insurance and agriculture.
- PaaS: Platform as a Service in IoT. Case studies of some IoT middleware.
- SaaS: Software/System as a Service for IoT business models.
- Updates and patches via web-OTA mechanisms.
- 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.
- EVs as mobile batteries and charger wallets.
- Large Battery storage: Hydro Battery, Lithium Battery, 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: A few 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 Modem, 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 standard 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 and gateway connectivity.
- Managing device and gateway health.
- Managing sensor calibration and QC.
- Managing OTA/Patching on a bulk 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 PLCs for power plants, sub-stations, 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 clouds for more efficient management of Critical Assets.
- Strategy for new policies regarding the adoption of smart devices.
Requirements
- Candidates should possess basic knowledge of business operations, devices, electronic systems, and data systems.
- A basic understanding of software and systems is mandatory.
A basic understanding of statistics (at an Excel level) is also required.
Target Audience
- Decision-makers, strategists, and policy-makers.
- Engineering leaders, lead developers, and security experts.
Breakdown of the Module (Each module is 2 hours; customers can request any number of modules): Total 22 hours, spread over 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.
