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Course Outline

Session 1 — Business Overview: Why IoT is so important

  • Case Studies from Nest, CISCO, and top industries
  • IoT adaptation rate in North America and how companies are aligning their future business models and operations around IoT
  • Broad Scale Application Areas
  • Smart House and Smart City
  • Industrial Internet
  • Smart Cars
  • Wearables
  • Home Healthcare
  • Business Rule Generation for IoT
  • 3-layered architecture of Big Data — Physical (Sensors), Communication, and Data Intelligence

Session 2 — Introduction to IoT: All about Sensors – Electronics

  • Basic function and architecture of a sensor — sensor body, sensor mechanism, sensor calibration, sensor maintenance, cost and pricing structure, legacy and modern sensor network — covering all 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, HART to modern-day Zigbee, Zwave, X10, Bluetooth, ANT, etc.
  • Business drivers for sensor deployment — FDA/EPA regulation, 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 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 protocol

  • 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 — 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 of Bluetooth vendors & their review.
  • Creating networks 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 projection

  • 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 those and when are they needed?
  • Basic introduction to multi-layer PCB design and its workflow
  • Electronics reliability — basic concepts of FIT and early mortality rate
  • Environmental and reliability testing — basic concepts
  • Basic Open source platforms: Arduino, Raspberry Pi, Beaglebone — when are they needed?

Session 5 — Conceiving a new IoT product - Product requirement document for IoT

  • State of the present art and review of existing technology in the marketplace
  • Suggestions for new features and technologies based on market analysis and patent issues
  • Detailed technical specs for new products - System, software, hardware, mechanical, installation, etc.
  • Packaging and documentation requirements
  • Servicing and customer support requirements
  • High-level design (HLD) for understanding the product concept
  • Release plan for the phased introduction of new features
  • Skill set for the development team and proposed project plan - cost & duration
  • Target manufacturing price

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 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 authentication of gateway devices.

Demo: Mobile app for tracking IoT-enabled trash cans

Session 7 — Machine learning for intelligent IoT

  • Introduction to Machine learning
  • Learning classification techniques
  • Bayesian Prediction — preparing training file
  • Support Vector Machine
  • Image and video analytics for IoT
  • Fraud and alert analytics through IoT
  • Bio-metric ID integration with IoT
  • Real-Time Analytics / Stream Analytics
  • Scalability issues of IoT and machine learning
  • What are the architectural implementations of Machine learning for IoT?

Demo: Using KNN Algorithm for regression analysis

Demo: SVM-based classification for image and video analysis

Session 8 — Analytic Engine for IoT

  • Insight analytics
  • Visualization analytics
  • Structured predictive analytics
  • Unstructured predictive analytics
  • Recommendation Engine
  • Pattern detection
  • Rule/Scenario discovery — failure, fraud, optimization
  • Root cause discovery

Session 9 — Security in IoT implementation

  • Why security is absolutely essential for IoT
  • Mechanism of security breach in 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-based IoT platforms

  • SQL vs NoSQL - Which one is good for your IoT application?
  • Open-source vs. Licensed Database
  • Available M2M cloud platforms
  • Cassandra - Time Series Data
  • Mongo-DB
  • Omega
  • Ayla
  • Libellium
  • CISCO M2M platform
  • AT&T M2M platform
  • Google M2M platform

Session 11 — A few common IoT systems

  • Home automation
  • Energy optimization in Home
  • Automotive - OBD
  • IoT-Lock
  • Smart Smoke alarm
  • BAC (Blood alcohol monitoring) for drug abusers under probation
  • Pet cam for Pet lovers
  • Wearable IoT
  • Mobile parking ticketing system
  • Indoor location tracking in Retail stores
  • Home healthcare
  • Smart Sports Watch

Demo: Smart city application using IoT

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 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 the Excel level).

 21 Hours

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