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Course Outline
Module 1: Introduction, Basics and Case Studies from Power Utility Companies
- Fundamentals of all technology stacks in IIoT.
- 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 Meter, Smart Car, 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 and 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, Zwave, 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.
- Matching sampling rate with application requirements: Why it matters for business.
- Defining sensor networks and ad-hoc networks.
- Wireless vs. Wireline networks.
- Autopairing and reconnection mechanisms.
- Application selection: Which technologies to use and where.
- Mathematical exercises to determine the appropriate network selection and deployment location.
Module 3: Key Security and Risk Concerns in IoT
- Firmware Patching risks: The vulnerability of IoT.
- Detailed review of security in IoT communication protocols: 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: Local and cloud-based.
- Risks associated with log management in edge and non-edge architectures.
Module 4: Machine learning, AI, Analytics for intelligent IoT
- Return on Investment (ROI) for Intelligent IoT.
- Utility applications: Power Quality, Energy management, and Other Analytics as a Service (AAS).
- Introduction to Analytics Stacks in IoT: Feature extraction, Signal Processing, 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 / Stream Analytics.
- Scalability issues in 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 Meter (IEC 62056).
- Security vulnerabilities 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 in 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.
- EV as a mobile battery and charger wallet.
- 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 systems.
- 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 large scale.
- Managing Firmware, Middleware, and analytics 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, 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 SCADA/PLC to intelligent local cloud for more efficient management of Critical Assets.
- Strategy for new policies regarding the adoption of 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 proficiency level).
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, 3 days.
22 Hours
Testimonials (2)
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.
Masilonyane - Revenue Services Lesotho
Course - Big Data Business Intelligence for Govt. Agencies
The oral skills and human side of the trainer (Augustin).
