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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 rates in North America and how organisations are aligning their future business models and operations around IoT.
- Broad-scale application areas.
- The smart factory of 2020.
- Industrial Internet.
- Predictive and preventative maintenance of machinery.
- Tracking the utilisation and productivity of machines.
- Energy and cost optimisation 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, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor networks – covering 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 – from history to modern days. Legacy protocols like Modbus, relay, and HART to modern-day Zigbee, Z-Wave, X10, Bluetooth, ANT, etc.
- Business drivers for sensor deployment – FDA/EPA regulations, fraud/tempering detection, supervision, quality control, and process management.
- Different kinds of 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 such as temperature, pressure, vibration, magnetic field, power factor, etc.
Demo: Logging data from a temperature sensor
Session 3: Fundamentals of M2M Communication: Sensor Networks and Wireless Protocols
- What is a sensor network? What is an ad-hoc network?
- 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. Introduction to different Zigbee chips.
- Bluetooth/BLE: Low power vs. high power, speed of detection, class of BLE. Introduction to Bluetooth vendors and their reviews.
- Creating networks with wireless protocols such as Piconet via BLE.
- Protocol stacks and packet structures 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 Platforms, Production, and Cost Projections
- PCB vs. FPGA vs. ASIC design – how to make the decision.
- Prototyping electronics vs. 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 and early mortality rates.
- Environmental and reliability testing – basic concepts.
- Basic open-source platforms: Arduino, Raspberry Pi, Beaglebone – when are they needed?
Session 5: Hardware/Protocol Elements of IIoT for Manufacturing
- State of the art and review of existing technology in the marketplace.
- PLC – architecture.
- Cloud integration of PLC data.
- Visualisation of PLC data.
- Digital Twin.
- PLC protocols (Modbus, Fieldbus, Profibus) and their integration with the cloud.
- Concept of the Industrial Gateway.
Session 6: Introduction to Mobile App Platforms for IoT
- Protocol stack of mobile apps for IoT.
- Mobile to server integration – what factors to look out for.
- What intelligent layers 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 authentication of 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.
- Predicting machine failure – 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.
- Visualisation analytics.
- Structured predictive analytics.
- Unstructured predictive analytics.
- Recommendation engine.
- Pattern detection.
- Root cause discovery for electrical failures in the 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.
- 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.
- Updates and patches.
Session 10: Database Implementation for IoT Cloud
- SQL vs. NoSQL – which is best for your IoT application?
- Open-source vs. licensed databases.
- Available M2M cloud platforms.
- Cassandra – time series data.
- MongoDB.
- Siemens MindSphere.
- GE Predix.
- IBM BlueMix.
- AWS IoT.
Session 11: A Few Common IIoT Systems for Manufacturing
- Energy optimisation in manufacturing.
- Vibration analysis to build predictive maintenance.
- Power quality analysis to build preventative maintenance.
- Recommendation systems for logistic 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
- 4Vs – 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 techniques for image, geospatial, and video data.
- Distributed databases – Cassandra as an example.
- Parallel computing basics for IoT.
- Microservices architecture.
Demo: Apache Spark
Requirements
Basic knowledge of business operations, devices, electronic systems, and data systems.
Basic understanding of software and systems.
Basic understanding of statistics (at 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.
