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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 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 — all the basics about the sensors.
- Development of sensor electronics — IoT vs. legacy, and open source vs. traditional PCB design style.
- 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 driver for sensor deployment — FDA/EPA regulation, fraud/tempering detection, supervision, quality control, and process management.
- Different Kind of Calibration Techniques — manual, automation, infield, primary, and secondary calibration — and their implication 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 — 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 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 — 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 the Mobile app level?
- iBeacon in iOS.
- Window 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 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 standard 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 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
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The training was relevant to my needs and I would be able to apply the lessons learnt to meet my challenging needs
