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Course Outline
Session 1 — Business Overview: Why IoT is Critical
- Case Studies from Nest, CISCO, and top-tier industries.
- The 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 initiatives.
- The Industrial Internet.
- Smart Cars.
- Wearable Technology.
- Home Healthcare.
- Business Rule Generation for IoT.
- 3-layered architecture of Big Data — Physical (Sensors), Communication, and Data Intelligence.
Session 2 — Introduction to IoT: Deep Dive into Sensors and Electronics
- Basic function and architecture of a sensor — sensor body, mechanism, calibration, maintenance, cost and pricing structures, and legacy vs. modern sensor networks.
- Development of sensor electronics — comparison between IoT and legacy systems, and open-source vs. traditional PCB design styles.
- Development of sensor communication protocols — from history to modern day, covering legacy protocols like Modbus, relay, and HART, to modern protocols such as Zigbee, Zwave, X10, Bluetooth, and ANT.
- 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 power, and PoE (Power over Ethernet).
- Hands-on training with single silicon and other sensors such as temperature, pressure, vibration, magnetic field, and power factor sensors.
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: From N to S — application of standards and common vendors.
- Zigbee and Zwave — advantages of low-power mesh networking, long-distance Zigbee, and an introduction to different Zigbee chips.
- Bluetooth/BLE: Low power vs. high power, detection speed, and BLE classes. Introduction to Bluetooth vendors and their reviews.
- 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 (Line of Sight) vs. NLOS (Non-Line of Sight) links.
- Capacity and throughput calculation.
- Application issues in wireless protocols — power consumption, reliability, PER (Packet Error Rate), QoS (Quality of Service), and LOS.
- Sensor networks for WAN deployment using LPWAN. Comparison of various emerging protocols such as LoRaWAN and NB-IoT.
- 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 right 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 (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 — 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 Platforms for IoT
- Protocol stack of Mobile apps for IoT.
- Mobile to server integration — key factors to consider.
- 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, Token, and random password generation for gateway device authentication.
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 files.
- Support Vector Machine.
- Image and video analytics for IoT.
- Fraud and alert analytics through IoT.
- Biometric ID integration with IoT.
- Real-Time Analytics/Stream Analytics.
- Scalability issues of IoT and Machine Learning.
- Architectural implementation 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 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 (Intrusion Prevention Systems).
- Updates and patches.
Session 10 — Database Implementation for IoT: Cloud-Based IoT Platforms
- SQL vs. NoSQL — which is good for your IoT application?
- Open-sourced vs. Licensed Databases.
- 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 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
- 4Vs of Big Data — Volume, velocity, variety, and veracity.
- 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 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 proficiency 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
