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Course Outline
Session 1: Business Overview of Why IoT is So Important
- Case studies from Nest, CISCO, and leading industries.
- The growth rate of IoT in North America and how companies are aligning their future business models and operations around IoT.
- Broad-scale application areas.
- The Smart Factory of 2020.
- Industrial Internet concepts.
- Predictive and preventative machine maintenance.
- Tracking machine utilization and productivity.
- Energy and cost optimization for manufacturing plants.
- Business rule generation for IoT.
- Three-layer architecture of Big Data: Physical (Sensors), Communication, and Data Intelligence.
Session 2: Introduction to IoT: All About Sensors
- Basic functions and architecture of sensors: sensor body, mechanism, calibration, maintenance, cost, pricing, and legacy vs. modern sensor networks.
- Development of sensor electronics: IoT vs. legacy systems, and open-source vs. traditional PCB design styles.
- Evolution of sensor communication protocols: from legacy protocols like Modbus, relay, and HART to modern standards like Zigbee, Z-Wave, X10, Bluetooth, and ANT.
- Business drivers for sensor deployment: FDA/EPA regulations, fraud/tempering detection, supervision, quality control, and process management.
- Different types of calibration techniques: manual, automation, in-field, primary, and secondary calibration, and their implications in IoT.
- Powering options for sensors: battery, solar, WiTricity, mobile power, and PoE.
- Hands-on training with single-silicon and other sensors such as temperature, pressure, vibration, magnetic field, and power factor.
Demo: Logging data from a temperature sensor
Session 3: Fundamentals of M2M Communication: Sensor Network and Wireless Protocols
- Understanding sensor networks and ad-hoc networks.
- Comparison of Wireless vs. Wireline networks.
- WiFi 802.11 families (N to S): application of standards and common vendors.
- Zigbee and Z-Wave: advantages of low-power mesh networking, long-distance Zigbee, and introduction to various Zigbee chips.
- Bluetooth/BLE: low power vs. high power, detection speed, BLE classes, and an overview of Bluetooth vendors.
- Creating networks with wireless protocols, such as Piconet via BLE.
- Protocol stacks and packet structure for BLE and Zigbee.
- Other long-distance RF communication links.
- Line of Sight (LOS) vs. Non-Line of Sight (NLOS) links.
- Capacity and throughput calculations.
- Application issues in wireless protocols: power consumption, reliability, Packet Error Rate (PER), Quality of Service (QoS), and LOS.
- Sensor networks for WAN deployment using Low-Power Wide-Area Networks (LPWAN): comparing emerging protocols like LoRaWAN and NB-IoT.
- Hands-on training with sensor networks.
Demo: Device control using BLE
Session 4: Review of Electronics Platform, Production and Cost Projections
- PCB vs. FPGA vs. ASIC design: how to make the right decision.
- Prototyping electronics vs. production-grade electronics.
- QA certifications for IoT: CE, CSA, UL, IEC, RoHS, IP65: What are they and when are they needed?
- Basic introduction to multi-layer PCB design and its workflow.
- Electronics reliability: basic concepts of FIT (Failures In Time) and early mortality rates.
- Environmental and reliability testing: basic concepts.
- Basic open-source platforms: Arduino, Raspberry Pi, Beaglebone: when to use them.
Session 5: Hardware/Protocol Elements of IIoT for Manufacturing
- State of the art and review of existing marketplace technology.
- PLC architecture.
- Cloud integration of PLC data.
- Visualization of PLC data.
- Digital Twin concepts.
- PLC protocols (Modbus, Fieldbus, Profibus) and their integration with the Cloud.
- Concept of the Industrial Gateway.
Session 6: Introduction to Mobile App Platform for IoT
- Protocol stack of Mobile apps for IoT.
- Mobile-to-server integration: key factors to consider.
- Intelligent layers that can be introduced at the Mobile app level.
- iBeacon in iOS.
- Windows Azure.
- Amazon AWS-IoT.
- Web interfaces for Mobile Apps (REST/WebSockets).
- IoT Application layer protocols (MQTT/CoAP).
- Security for IoT middleware: Keys, Tokens, and random password generation for authenticating gateway devices.
Demo: Mobile app for tracking IoT-enabled trash cans
Session 7: Machine Learning for Intelligent IIoT
- Introduction to Machine Learning.
- Learning classification techniques.
- Bayesian Prediction: preparing training files.
- Support Vector Machine (SVM).
- Predicting machine failure through vibrational analysis.
- Current signature analysis.
- Time series data and prediction.
Demo: Using KNN Algorithm for regression analysis
Demo: SVM-based classification for image and video analysis
Session 8: Analytic Engine for IIoT
- Insight analytics.
- Visualization analytics.
- Structured predictive analytics.
- Unstructured predictive analytics.
- Recommendation Engine.
- Pattern detection.
- Root cause discovery for electrical failures in factories.
- Root cause of machine failure.
- Logistics supply chain analysis for manufacturing.
Session 9: Security in IoT Implementation
- Why security is absolutely essential for IoT.
- Mechanisms of security breaches in the IoT layer.
- Privacy-enhancing technologies.
- Fundamentals of network security.
- Encryption and cryptography implementation for IoT data.
- Security standards for available platforms.
- European legislation for security in IoT platforms.
- Secure booting.
- Device authentication.
- Firewalling and IPS (Intrusion Prevention Systems).
- Updates and patches.
Session 10: Database Implementation for IoT Cloud
- SQL vs. NoSQL: Which is better for your IoT application?
- Open-source vs. Licensed Databases.
- Available M2M cloud platforms.
- Cassandra for Time Series Data.
- MongoDB.
- Siemens MindSphere.
- GE Predix.
- IBM Bluemix.
- AWS IoT.
Session 11: A Few Common IIoT Systems for Manufacturing
- Energy Optimization in Manufacturing.
- Vibration analysis to build predictive maintenance.
- Power Quality analysis to build preventative maintenance.
- Recommendation system for logistics supply chain.
- IIoT system for Industrial Safety.
- IIoT system for asset identification.
- IIoT system for Utilities in manufacturing plants (Chillers, Air compressors, HVAC).
Demo: Retail, Transportation & Logistics Use case for IoT
Session 12: Big Data for IoT
- The 4Vs of Big Data: Volume, Velocity, Variety, and Veracity.
- Why Big Data is important in IoT.
- Big Data vs. legacy data in IoT.
- Hadoop for IoT: when and why to use it.
- Storage techniques for image, Geospatial, and video data.
- Distributed database: Cassandra as an example.
- Basics of parallel computing for IoT.
- Microservices Architecture.
Demo: Apache Spark
Requirements
Fundamental 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).
21 Hours
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.
