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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 adaptation rates 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 of 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 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, 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 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 like temperature, pressure, vibration, magnetic field, power factor, etc.
Demo : Logging data from a temperature sensor
Session 3 — Fundamental 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 — 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 network.
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 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 — Conceiving a new IoT product—Product requirement document for IoT
- State of the present art and review of existing technology in the marketplace.
- Suggestion 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 of product concept.
- Release plan for phase-wise introduction of the 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 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 IoT
- Introduction to Machine learning.
- Learning classification techniques.
- Bayesian Prediction—preparing training file.
- Support Vector Machine.
- Image and video analytic for IoT.
- Fraud and alert analytic through IoT.
- Bio-metric ID integration with IoT.
- Real Time Analytic/Stream Analytic.
- 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 analytic.
- Visualization analytic.
- Structured predictive analytic.
- Unstructured predictive analytic.
- 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.
- 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 based IoT platforms
- 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.
- 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 store.
- Home health care.
- 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 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 (Excel level).
21 Hours
Testimonials (1)
The training was relevant to my needs and I would be able to apply the lessons learnt to meet my challenging needs
