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Course Outline
Session 1: Business Overview of Why IoT is So Important
- Case Studies from Nest, CISCO, and top industries.
- IoT adoption rates in North America & 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 of 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 function and architecture of a sensor: sensor body, mechanism, calibration, maintenance, cost and pricing structure, legacy and modern sensor networks—all the basics about sensors.
- Development of sensor electronics: IoT vs. legacy, and open-source vs. traditional PCB design styles.
- Development of sensor communication protocols: history to modern days. Legacy protocols like Modbus, relay, HART to modern day Zigbee, Zwave, X10, Bluetooth, ANT, etc.
- Business drivers for sensor deployment: FDA/EPA regulation, fraud/tempering detection, supervision, quality control, and process management.
- Different Calibration Techniques: manual, automation, infield, primary, and secondary calibration—and their implications in IoT.
- Powering options for sensors: battery, solar, Witricity, Mobile, and PoE.
- Hands-on training with single silicon and other sensors like temperature, pressure, vibration, magnetic field, power factor, etc.
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 vs. Wireline network.
- WiFi- 802.11 families: N to S—application of standards and common vendors.
- Zigbee and Zwave—advantage of low power mesh networking. Long distance Zigbee. Introduction to different Zigbee chips.
- Bluetooth/BLE: Low power vs high power, speed of detection, class of BLE. Introduction of Bluetooth vendors & their review.
- Creating network with Wireless protocols such as Piconet by BLE.
- Protocol stacks and packet structure for BLE and Zigbee.
- Other long distance RF communication links.
- LOS vs NLOS links.
- Capacity and throughput calculation.
- Application issues in wireless protocols—power consumption, reliability, PER, QoS, LOS.
- Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN, NB-IoT, etc.
- 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 take a decision.
- Prototyping electronics vs Production electronics.
- QA certificate for IoT—CE/CSA/UL/IEC/RoHS/IP65: What are those and when are they needed?
- Basic introduction of multi-layer PCB design and its workflow.
- Electronics reliability—basic concept of FIT and early mortality rate.
- Environmental and reliability testing—basic concepts.
- Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone, when needed?
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.
- PLC protocols (Modbus, Field bus, Profibus) and its integration with Cloud.
- Concept of Industrial Gateway.
Session 6: Introduction to Mobile App Platform for IoT
- Protocol stack of Mobile app for IoT.
- Mobile to server integration—what are the factors to look out for.
- What are the intelligent layers that can be introduced at 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, Token, and random password generation for authentication of the 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 file.
- Support Vector Machine.
- Predicting failure of the machines—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 analytic.
- Visualization analytic.
- Structured predictive analytic.
- Unstructured predictive analytic.
- Recommendation Engine.
- Pattern detection.
- Root cause discovery for electrical failures in factory.
- Root cause of machine failure.
- Logistic supply chain analysis for manufacturing.
Session 9: Security in IoT Implementation
- Why security is absolutely essential for IoT.
- Mechanism of security breach in IOT layer.
- Privacy enhancing technologies.
- Fundamental of network security.
- Encryption and cryptography implementation for IoT data.
- Security standard for available platform.
- European legislation for security in IoT platform.
- Secure booting.
- Device authentication.
- Firewalling and IPS.
- Updates and patches.
Session 10: Database Implementation for IoT Cloud
- SQL vs NoSQL—Which one is good for your IoT application.
- Open sourced vs. Licensed Database.
- Available M2M cloud platform.
- Cassandra—Time Series Data.
- Mongo-DB.
- 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 logistic supply chain.
- IIoT system for Industrial Safety.
- IIoT system asset identification.
- IIoT system for Utilities in Manufacturing plants (Chiller, Aircompressor, HVAC).
Demo : Retail, Transportation & Logistics Use case for IoT
Session 12: Big Data for IoT
- 4V—Volume, velocity, variety and veracity of Big Data.
- Why Big Data is important in IoT.
- Big Data vs legacy data in IoT.
- Hadoop for IoT—when and why?
- Storage technique for image, Geospatial and video data.
- Distributed database—Cassandra as example.
- Parallel computing basics for IoT.
- Micro services 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 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.
