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Course Outline
Session 1 — Business Overview: Why IoT is Crucial
- Case studies from Nest, CISCO, and leading industries.
- IoT adaptation rates in North America and how organizations are aligning their future business models and operations around IoT.
- Broad-scale application areas.
- Smart Houses and Smart Cities.
- Industrial Internet.
- Smart Vehicles.
- 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: Sensors and Electronics
- Basic function and architecture of sensors — sensor body, mechanism, calibration, maintenance, cost and pricing structure, legacy and modern sensor networks — covering all the essentials.
- Development of sensor electronics — IoT vs. legacy approaches, and open-source vs. traditional PCB design styles.
- Development of sensor communication protocols — from history to modern day. Legacy protocols like Modbus, relay, HART to modern protocols like Zigbee, Zwave, X10, Bluetooth, ANT, etc.
- Business drivers for sensor deployment — FDA/EPA regulation, fraud/interference 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 such as temperature, pressure, vibration, magnetic field, power factor, etc.
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: N to S — application of standards and common vendors.
- Zigbee and Zwave — advantages of low-power mesh networking. Long-range Zigbee. Introduction to various Zigbee chips.
- Bluetooth/BLE: Low power vs. high power, detection speed, class of BLE. Introduction to Bluetooth vendors and their reviews.
- Creating networks with wireless protocols such as Piconet via BLE.
- Protocol stacks and packet structure for BLE and Zigbee.
- Other long-distance RF communication links.
- Line-of-Sight (LOS) vs. Non-Line-of-Sight (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 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 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 & duration.
- Target manufacturing price.
Session 6 — Introduction to Mobile App Platform for IoT
- Protocol stack of Mobile app 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 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.
- 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 layers.
- 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 is better for your IoT application?
- Open-sourced vs. Licensed Database.
- 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 optimization in homes.
- 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
- 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 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 an 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
