Course Outline
Session 1:Basic and Advanced concepts
- Basic -1: A brief history of evolution of IoT technologies
- Basic-2: Wearable, Edge computing, IoT wireless protocols ( Sigfox, Lora etc.) , IoT cloud platforms.
- Basic-3 : layered architecture of IoT — Physical (Sensors), Communication, and Data Intelligence
- Advanced-1 : Edge architecture, edge computation and database
- Advanced-2 : Next Generation IoT Gateways- edge and 5G
- Advanced-3: managed IoT services like diagnostics, maintenance of IoT infrastructure by bots and automation
Session 2:Sensing and Devices: Architectures and Examples
- 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.
Session 3:Well Known Communication Protocols for IoT Engineering
- What is a sensor network? What is 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 link
- 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 Standard and Advanced topologies in IoT
- Reviewing all the basic elements of an IoT system- sensors, automation, gateway, edge gateway, data visualization, data analytics, cloud computation
- Review of a standard gateway architecture- North and South bound system, critical process, IPC vs IPC internal communication protocols, Batch vs no-batch computation
- Edge computation and edge database- more detailed architectural lay-outs
- Gateway to cloud communication – MQTT, Web-socket etc.
- Real Time vs Near Real time vs Historical visualization
- Over the top (OTA) architectures for remote update of firmware and software
- Managing a distributed system and network from event logs more effectively
- Batch size vs process duty cycle- how to match them
Session 5:Data-Mining and 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
- 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
- Geo-fencing in IoT analytics
- Real Time Analytic/Stream Analytic
- Scalability issues of IoT and machine learning
- What are the architectural implementation of Machine learning for IoT
Session 6:Cloud computing and platforms for IoT
- IaaS vs PaaS
- SaaS models
- Hybrid IoT clouds
- On-premise cloud for IoT
- IoT event hub ( Microsoft)
- AWS IoT Platform ( with demo and architecture)
- Microsoft IoT platform (with demo and architecture)
- Basic concepts of Cloud apps for in IoT
- Basic concepts of different layers of security in IoT
- Detailed study of Azure IoT platform architrecture
Session 7:Hands-on building a IoT cloud system
- Build a IoT system using Microsoft Azure IoT central – example will be to build a 3 phase-voltage current sensor in Azure IoT central system
- Learn the basic concepts of IoT Web app- Fleet manager, data visualization, sensor onboarding, sensor mapping, sensor-system attribute mapping , digital twins - learn it via Azure IoT central and Machinesense Crystal Ball
- Computation /Machine learning of Data in Edge vs Cloud
- Concept of IoT Template for replicated IoT system design
- IoT system and connectivity diagnosis
Session 8:Emerging Research Areas and Case Studies for Federal grants in IoT
- Smart City : Structural health monitoring, Bridge health monitoring, Transportation Monitoring, Air and Water pollution monitoring, Smart Parking etc.
- Sustainable development goals ( SDG)- defining IoT Scopes in SDG1-16 as defined by UN
- IoT and Public Safety – Fire hazard, flash floods prevention
- IoT and 5G
- IoT in smart agriculture
- IoT in Oil/Gas
- IoT and water management
- IoT and Power management – energy and power quality
Requirements
- An understanding of IoT.
- Basic knowledge devices, electronics systems and data systems
- Basic understanding of software and systems
- Basic understanding of Statistics (in Excel levels)
- Understanding of Telecommunication Verticals
Target Audience
- Faculty members and research engineers who are applying for Govt grants in IoT areas- such as smart city, smart manufacturing, 5G-IoT
Testimonials (2)
The ability of the trainer to align the course with the requirements of the organization other than just providing the course for the sake of delivering it.
Masilonyane - Revenue Services Lesotho
Course - Big Data Business Intelligence for Govt. Agencies
The oral skills and human side of the trainer (Augustin).