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Course Outline
Session 1: Business Overview of Why IoT Is So Important
- Case studies from Nest, CISCO, and leading industries.
- I IoT adoption rates 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.
- The Industrial Internet.
- Predictive and preventative maintenance of machinery.
- Tracking machine utilization and productivity.
- Energy and cost optimization for manufacturing plants.
- Business rule generation for IoT.
- Three-layered architecture of Big Data: Physical (Sensors), Communication, and Data Intelligence.
Session 2: Introduction to IoT: All About Sensors
- Basic functions and architecture of a sensor: sensor body, mechanism, calibration, maintenance, cost, and pricing structure, legacy versus modern sensor networks—all the basics.
- Development of sensor electronics: IoT versus legacy systems, and open-source versus traditional PCB design styles.
- Development of sensor communication protocols: history to modern day. Legacy protocols like Modbus, relay, and HART versus modern protocols like Zigbee, Z-Wave, X10, Bluetooth, and ANT.
- Business drivers for sensor deployment: FDA/EPA regulations, fraud/tampering detection, supervision, quality control, and process management.
- Different kinds of calibration techniques: manual, automation, in-field, primary, and secondary calibration—and their implications in IoT.
- Powering options for sensors: battery, solar, Witricity, mobile, and Power over Ethernet (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
- What is a sensor network? What is an ad-hoc network?
- Wireless versus 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-range Zigbee. Introduction to different Zigbee chips.
- Bluetooth/BLE: low power versus high power, detection speed, BLE classes. Introduction to Bluetooth vendors and their reviews.
- 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) versus 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). Comparison of various emerging protocols such as 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 versus FPGA versus ASIC design: how to make the right decision.
- Prototyping electronics versus production electronics.
- QA certificates 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 rate.
- 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 present art and review of existing technology in the marketplace.
- 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 the Mobile app 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 gateway device authentication.
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 the 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 engines.
- Pattern detection.
- Root cause discovery for electrical failures in the factory.
- 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 Intrusion Prevention Systems (IPS).
- Updates and patches.
Session 10: Database Implementation for IoT Cloud
- SQL versus NoSQL: which is better for your IoT application?
- Open-source versus 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 systems for logistics supply chains.
- IIoT systems for industrial safety.
- IIoT system asset identification.
- IIoT systems 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: Volume, velocity, variety, and veracity of Big Data.
- Why Big Data is important in IoT.
- Big Data versus legacy data in IoT.
- Hadoop for IoT: when and why?
- Storage techniques for image, geospatial, and video data.
- Distributed databases: Cassandra as an example.
- Basics of parallel computing for IoT.
- Microservices Architecture.
Demo: Apache Spark.
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).
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.
