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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.
- Smart homes and smart cities.
- Industrial Internet.
- Smart cars.
- Wearables.
- Home healthcare.
- 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 – Electronics
- Basic function and architecture of a sensor: sensor body, mechanism, calibration, maintenance, cost and pricing structure, legacy and modern sensor networks – 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 times. Legacy protocols like Modbus, relay and HART to modern-day Zigbee, Zwave, X10, Bluetooth, ANT, etc.
- Business drivers for sensor deployment: FDA/EPA regulations, fraud/tampering 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 such as temperature, pressure, vibration, magnetic field and 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 networks.
- 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, 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 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 these 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 art and review of existing technology in the marketplace.
- Suggestions for new features and technologies based on market analysis and patent issues.
- Detailed technical specifications 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 phased introduction of new features.
- Skill set for the development team and proposed project plan – cost and duration.
- Target manufacturing price.
Session 6 — Introduction to Mobile app platform for IoT
- Protocol stack of mobile apps for IoT.
- Mobile to server integration: what 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, tokens 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 files.
- 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.
- 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.
- Visualisation analytics.
- Structured predictive analytics.
- Unstructured predictive analytics.
- Recommendation engine.
- Pattern detection.
- Rule/scenario discovery: failure, fraud, optimisation.
- Root cause discovery.
Session 9 — Security in IoT implementation
- Why security is absolutely essential for IoT.
- Mechanisms 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.
- 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 databases.
- Available M2M cloud platforms.
- Cassandra: time-series data.
- MongoDB.
- Omega.
- Ayla.
- Libellium.
- CISCO M2M platform.
- AT&T M2M platform.
- Google M2M platform.
Session 11 — A few common IoT systems
- Home automation.
- Energy optimisation in the home.
- Automotive – OBD.
- IoT locks.
- Smart smoke alarms.
- BAC (Blood alcohol monitoring) for drug abusers under probation.
- Pet cams for pet lovers.
- Wearable IoT.
- Mobile parking ticketing systems.
- Indoor location tracking in retail stores.
- Home healthcare.
- Smart sports watches.
Demo: Smart city application using IoT
Demo: Retail, Transportation & Logistics use cases for IoT
Session 12 — Big Data for IoT
- 4Vs: 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 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
