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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 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 Machines
  • Tracking machine utilization and productivity
  • Energy and cost optimization in 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
  • 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 (Modbus, relay, HART) to modern protocols (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 calibration techniques: manual, automation, in-field, primary, and secondary, and their implications in IoT
  • Powering options for sensors: battery, solar, WiTricity, Mobile, and PoE
  • Hands-on training with single silicon and other sensors (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 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, detection speed, classes of BLE. Introduction to Bluetooth vendors and 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
  • 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 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 make decisions
  • 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 (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

  • Current state of the 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, Fieldbus, Profibus) and their 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: 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, Token, 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
  • 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 IoT layers
  • 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 better 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 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 (Chiller, Air Compressor, 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 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, electronics systems, and data systems.

Basic understanding of software and systems.

Basic understanding of Statistics (at an Excel proficiency level).

 21 Hours

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