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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 adoption rates 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.
- Three-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 structure, legacy and modern sensor networks. All basics regarding sensors.
- Development of sensor electronics: IoT vs. legacy, open source vs. traditional PCB design styles.
- Development of sensor communication protocols: History to modern day. Legacy protocols like Modbus, relay, HART to modern protocols like Zigbee, Z-Wave, X10, Bluetooth, ANT, 6LoPAN, WiFi, NB-IoT, SignalFx, 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.
- Which applications to use and where.
- Mathematical exercises to determine which network to select and for what purpose.
Module 3: Key Security and Risk Concerns in IoT
- Firmware patching risks: The weak point of IoT.
- Detailed review of IoT communication protocol security: Transport layers (NB-IoT, 4G, 5G, LoRa, Zigbee, etc.) and application layers (MQTT, WebSockets, etc.).
- Vulnerability of API endpoints: List of all possible APIs in IoT architecture.
- Vulnerability of gateway devices and services.
- Vulnerability of connected sensors via 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.
- Risk of log management in edge and non-edge architectures.
Module 4: Machine Learning, AI, and Analytics for Intelligent IoT
- Return on investment (ROI) for intelligent IoT.
- Applications in Utilities: Power Quality, Energy Management, and other Analytic as a Service (AAS).
- Introduction to analytic 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 (SVM).
- Image and video analytics for IoT.
- Fraud and alert analytics through IoT.
- Real-time analytics and 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 C12.18 Protocols.
- NIST Standard for HAN (Home Area Network).
- HomePlug 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 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 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 - 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 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 and gateway connectivity.
- Managing device and gateway health.
- Managing sensor calibration and quality control (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 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 on 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 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
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 5200 € + VAT*
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Testimonials (3)
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).
Jeremy Chicon - TE Connectivity
Course - NB-IoT for Developers
I enjoyed the relaxed mood. Also there was a very good balance between theoretical presentation and practical side.
